Every change that reached customers from June 2025 to November 2026, compiled from the code that went to production. Pick a month, browse what changed, open any item for the details.
174 new · 265 improved · 399 fixes · across 18 months · updated Nov 15, 2026
Each gap between rows has its own resize grip, a card alone in its row can be narrowed to leave an open slot for another card, and a note shows when a card is at its tallest or shortest. A table on a live board scrolls through its rows, up to 1,000, and undo or redo of a move is instant.
Ask is the read-only side of Mammoth for people who only need answers. Builders make rooms of chosen tables and invite colleagues or outside guests, who join free. People in a room ask questions and get answers with charts and sources, plus a Today page about their numbers each morning. Anything a room can't answer comes back to builders as a request. Ask is part of Enterprise agreements.
Mammoth detects Email, URL and Phone columns from their values, and the column's explore card shows Valid, Invalid and Empty counts that filter the grid. Filters can match an email or web domain or a phone country code, a data check can require a share of valid values, and Extract pulls out an email's domain, a URL's path or a phone's country code.
Confirming a workbook's sheets saves every sheet that still reads, instead of failing them all over one that changed since the preview, and the done message names the sheets left out with Review to reopen them. Sheets named or built like a summary, calculation or pivot start unticked with the reason, and a sheet refused at Create shows why.
Property Portfolio (occupancy, rent collected, arrears and NOI by building), Production Performance (output against plan, quality and lost time by line) and Call Center Performance (answer speed, abandoned calls and demand against staffing) join the template gallery.
Uploading a workbook can turn its formula columns into Mammoth steps, so next month's file is recalculated the same way. Each column counts as rebuilt only when every value matches what Excel saved, a strip says how many were rebuilt and which differ, and columns that weren't rebuilt keep Excel's values with the reason, or can be rebuilt by hand as a Math step.
The left navigation folds Datasets, Connections, Automations, Data map, Parameters and Monitor under Data, with an amber dot on Monitor when something needs you. Shared with you becomes a tab on Dashboards, Support and Trash move into your account menu, and the Activity log moves to Workspace settings with a Project filter.
A mic in the dashboard editor's AI Chat and in a connector's chat turns what you say into text in the message box, on a computer as well as a phone, for you to edit and send. Your project's table and column names help it spell them right, listening stops after a pause, a tap or two minutes, and the recording is not kept.
Picking a workspace from the menu opens the project you last had open there, instead of the one updated most recently.
mammoth bench runs one read command several times at once for a number of rounds and reports response times at the median and 95th percentile, with any errors. A new --workspace flag runs a command against another workspace without changing your profile. In mammoth-cli 2.4.5.
When sheets in an upload share columns, the save step shows both outcomes as cards: one table with a Source column, or a table per sheet, each with its row count and first rows, and you choose with the button on the card.
Monitor lists one row per view that is behind, naming the view and each source it reads through a join, with Apply now in place of Update. The outcome stays on the row with the reason if it fails, and joins inside views in the trash are left out and counted in a footnote with Open Trash.
If you own some workspaces and were invited to others, the workspace switcher lists them under Yours and Shared with you, with each shared workspace's admin named.
A connector AI built can take one value out of a column holding JSON, so a table keeps the fields you need while leaving the rest of the JSON out.
A new account whose email is not yet confirmed opens on a Confirm your email card with Resend the email and I've confirmed it, instead of empty pages.
A PostgreSQL, MySQL, SQL Server, Redshift, Hadoop or Snowflake connection's health on Connections now updates whenever you list its tables or preview a sample, so one that stops answering shows as unreachable without waiting for the daily check.
Date parameters show in the project's date format in the parameters list, the preview and the step picker, and each date parameter can have its own display format. The stored value is unchanged.
When an AI assistant or app that isn't set up to connect to Mammoth starts a connection, a page says it can't connect yet and links to the apps that can, before anyone is asked to sign in or create an account.
Signing up from a template page on mammoth.io opens straight into that template's board instead of Home. Connecting the template's source no longer fails when your plan doesn't allow a daily refresh: the board moves onto your data with a weekly refresh, or none, and the source strip says which.
Picking Notes or Report in a dashboard's Writing setting fills the preview with the text the AI writes from the board's figures, with no Save first. New boards have their words written in advance, so a level picked later shows them at once.
Xero's Profit and Loss and Balance Sheet arrive as one row per account per month, for the last 12 whole months, alongside Trial Balance, Bank Summary, an invoice summary, and Aged Receivables and Payables listing each open invoice with its days overdue and age bucket. Connections are named after the Xero organization, and Xero sign-in, table lists and previews no longer fail with a driver error.
A date range filter on a board opens a month picker, with presets from the data's own span (Latest month, Last 3 or 12 months, Year to date, All months) and a month grid by year. Arrows on the filter step to the previous or next period, and custom dates are one click away. Filters can be edited while a board is in edit mode, and the dashboard library has one Filter menu, with a new Shared with filter for the people a board reaches. A board with no date filter says which months its data covers.
A new connector table starts with every column the source returns, however wide, and the columns of a nested record can be ticked or unticked together as a group.
The separate Document format is gone. Every dashboard instead has a Writing setting: Glance, Notes or Report. Notes and Report add text the AI writes from the board's own figures, and its numbers change with the filters. Asking for a document or a report now sets a dashboard to Report.
When a refresh brings keys that find no match in a join, the join step in a view that feeds a dashboard says which keys and how many rows, and whether the join drops them or leaves their columns blank. Dismiss quiets a key while it keeps missing.
The users table fills the page with resizable columns it remembers, filters sit in one compact menu, No projects assigned filters on the projects a row shows, and long names and custom roles no longer overlap on narrow screens.
A dashboard exported to Power BI or Tableau carries every card's aggregation, not only sums, and an export that can't be made says why.
Settings has an Email notifications page that lists every email Mammoth sends you, each with its own switch, and marks the account emails that are always sent. Admins set the default for the whole workspace and can send pipeline and export failure emails to editors as one daily summary.
A folder upload shows how many of its files are done and moves through sending, queuing and reading each file, instead of sitting at full until the whole folder is read.
A Fulfilment & Throughput dashboard template for operations in any industry joins the template gallery.
Email groups are renamed Invite lists and moved under User management, and each list shows where it is used.
One dataset can read several accounts of the same connector into a single table, with a column naming each row's account. The dataset's Accounts card picks which accounts it reads, connections are grouped by connector, a failed account keeps its last rows, and column changes reach every account.
A dashboard's Share dialog is split into Settings, People and Embed tabs. On a public board, People offers to switch it to sign-in required before you invite anyone.
mammoth-cli 2.4.3 and the SDK keep dataset changes in an automation update and can move its schedule, send a view to a dataset as a replace or an append and run it straight away, list a join's unmatched keys across the whole view, and duplicate a dashboard under a new title. A change refused because the workspace has no active subscription now says so, instead of asking for an administrator.
A dashboard can be set to show complete months only. The month that is still filling in is left out of its charts and trends, so a half-finished month no longer looks like a drop.
Key insights you write yourself now change with the board's filters, the same way the ones Mammoth writes do, and the P&L template sums income correctly.
A shared dashboard's link preview in Slack, email and other apps now shows the lighter look. Previews already published were redrawn, and KPI rows, edit tools and embedded boards got their finishing fixes.
In the sheet picker, a sheet can be unticked while it is still loading. Unticked sheets are not read, so there is less to wait for before Looks right.
Large NetSuite pulls read in key ranges, so a pull that took hours now takes minutes, and a table over 100,000 rows is read in full instead of stopping at the first 100,000.
Boards on the stock styles drop their card boxes. Filters sit in a row of pills with More filters, the board's summary moves behind an ⓘ beside the title, bars are flat and rankings colour only the leader. Custom and brand styles keep their own look and can now choose Open as a card style, and Style › Look switches a board back to the old look.
Google Sheets and Drive list files from shared drives and search every file by name, and Google sign-in opens in a popup so the page stays where it is. Tabs of one spreadsheet that share a header can be added as one table with a Tab column, and new matching tabs join on refresh. A tab with a title row above its header now opens the Source Interpreter, and files from Drive, SharePoint, OneDrive, Dropbox and SFTP get the same header check. A sign-in that left Drive read access unticked is refused with a message saying what to tick. OneStream joins the connector catalog.
Select cells, ranges or whole rows and columns in the raw source and add them to your Source Interpreter instruction as a reference. The AI reads where the cells are and what they hold, so it finds them again when a later file's rows have moved.
Key Insights in the data editor open with one checked finding and a Show these rows button that filters the grid to the rows behind it.
A dataset made from a Mammoth sample file now behaves like an uploaded file: Add data instead of Get the latest, no Linked to card or link refresh, and samples no longer appear under Connections › Links.
Share in the data editor replaces Export and Publish. It makes a link to a one-page board where readers filter, sort and chart every row in their browser with no account, or only the people you invite, and the link stays up to date as the view changes. You choose the columns readers see, columns that may hold personal details are pointed out first, a link can ask for a password, and Stop sharing ends the address for good.
Signing in again to the same account updates the existing connection, instead of adding a second one, for Google, HubSpot, Shopify, Xero and the other sign-in connectors.
A view's steps can be saved as a template for the whole workspace or only you, then added to another view after a check that its columns fit, with Undo.
On the Pro plan, workspace admins create their own workspace and project roles under Settings › Roles & Permissions with New Role, choosing exactly which permissions each carries, and give them to people and invites like the built-in roles. Permissions your own role doesn't hold show locked, and a role someone holds can't be deleted.
On most database connections, SQL you run, preview or save is checked first, and anything other than a single read query is refused with the reason. The connection's own database permissions remain the final control.
Turning on cell editing asks once per view. While it is being enabled the banner says so and the grid waits for the rerun instead of reloading every 5 seconds, your first edit is kept, and if enabling doesn't finish you can try again. A cell changed back to its original value isn't sent, and a template whose Edit Cells step edits a joined column runs when applied.
Save a list of email addresses as a named group and invite it by name when sharing a dashboard or a collection; the group becomes its people, each with their own access. Typing two or more addresses in an invite field offers to save them as a group, and Settings › Email groups lists them. Anyone in the workspace can use a group, and its creator or a workspace owner or admin can change it.
NetSuite datasets pull all their rows, with column types read from the data, and a refused pull shows NetSuite's reason. Setting up a dataset lists NetSuite's tables with transactions first and loads samples quickly. Reconnecting updates the connection in place, signing in to a different account is refused with the reason, and Connections show the NetSuite role and warn when it can't read transactions or the sign-in is about to end, with Sign in again.
When the browser is signed in to Mammoth, the free tools' header shows Open Mammoth, and Login opens the app instead of the sign-up page. The app's account menu links to the Mammoth website.
When you pick Excel and the PDF has two or more tables, the free converter's Tables are ready email attaches one workbook named after your file, with a sheet per table in page order. Arriving from the PDF to Excel page, the tool starts with Excel picked.
Templates for Salesforce, HubSpot, Shopify, GA4, Meta Ads, Mailchimp, Google Ads and more open on a sample shaped like that source's data, then offer to connect it: sign in, pick an account if you have several, and the board switches to your own table, which refreshes on a schedule. Sources Mammoth can't sign in to yet, and Google Sheets, offer an upload instead, and template cards name the source each one connects to.
During a 14-day Pro trial the trial bar appears only in the last 3 days and only to people who can change the plan, and the left rail shows the days left. Trial emails carry a tip matched to how you signed up, and a trial that ends unpaid sends an email saying the workspace has moved to the Free plan.
On Connections, a dataset you are still setting up from a saved connection sits under that connection, with what is left to do and Continue, and the connection shows how many are in setup instead of No linked datasets. These drafts are named after the connector and table, duplicate drafts on one connection are folded into one, and a draft that reads the connection marks it healthy.
Every workspace now gets an email when a pipeline step or an export fails, and when a file can't be added to a dataset because its columns don't match. Each new dataset also gets its one-sentence AI summary on the Datasets page, written again only when its columns change.
Monitor opens as its own page on a phone, Settings has a phone index with drill-in pages, and the automation wizards, the scheduler, User Management and Plan & storage fit the screen. The data editor's pipeline cards give the error reason, a dashboard's cover lists its pages, and dialogs and menus open as bottom sheets with larger controls.
A Send to Dataset export can run on its own schedule from a Scheduled export automation, so a table can be appended once a week instead of on every upstream update. CSV downloads still run with the pipeline.
Webhook is its own item in the New dataset window again: give it a name and how often to add rows, and you land on its card with the URL, secret and an example request. Send a test row checks it end to end, and the keys in pushed JSON become columns even in a view whose owner keeps auto-run off.
mammoth view data aggregate takes MEDIAN on a number column, on its own or grouped, and returns the exact middle value over the non-blank values. In mammoth-cli 2.4.2.
A column's type can say more: ID or code, Currency, Percentage, or plain text or number. Mammoth detects subtypes from a dataset's values, you set them in the Column Manager and Schema Settings, and the grid header shows each column's type tag.
Connecting NetSuite, Zoho or DocuSign no longer asks for an account ID, data centre or server first: you sign in with the provider, and Mammoth reads it from there.
Rows sent to a webhook are added every 5 minutes, hourly, daily or by hand, and the keys in its JSON become columns. The Source card says whether the webhook is receiving, failing or waiting, when the last row arrived and how many came today, and why any pushes were turned away.
Upload macro-enabled Excel workbooks (.xlsm) like any other workbook. Mammoth reads their values and never runs a macro.
Tables from a connector AI built get number and date columns from the first pull instead of text, so amounts sum and dates filter. A pull no longer fails on a line break inside a value in the first row, failure emails are fewer and plainer, a source that ignores paging saves when it returns exactly one full page, and records read twice under page-number or offset paging are caught.
The API Keys page now starts with connecting an AI assistant over MCP and signing in to the CLI through the browser, neither of which needs a key, with setup steps for popular assistants; the key cards follow.
Every new dashboard gets an Explore page beside its overview and Q&A, where a signed-in reader slices, filters and drills the board's own rows, with highlights of what stands out, saved metrics and CSV or Excel downloads, and each reader's cards are kept. Explore is also a format of its own on the create screen. Boards with row-level security, a public or password link, or downloads turned off do not offer it.
A Financial Year step under Date Tools adds the financial year a date falls in: pick the month your year starts, and October 2024 to September 2025 becomes 2025, ready to group, filter or drill on.
The New Project dialog is ready to type in and suggests a dated name, and a project's date format is set from presets, UK / Europe, US or International, or left as Not set.
Answers in a dashboard's AI Q&A label date buckets the way the board does, such as Q2 2026, show the breakdown behind a figure, offer follow-up questions and no longer repeat the same caveat.
A live link can require a key as well as the link, stop working on a date, be turned off and on, and be rotated to a new address with a grace period for the old one. New links are served from a Mammoth address, and the link's settings show when it was last fetched and by which tool, with fetches and refusals over 7 days. Mammoth's From URL import can read a link that needs a key.
Starting a self-serve 14-day Pro trial sends an email with its end date, that no card is charged and what happens on day 15, with a Stop my trial link that keeps your workspace; another email comes before the trial ends.
mammoth-cli 2.4.1 and the SDK read the spec of a connector AI built, for a draft or a saved version, including its paging and record paths. A follow-on job that cannot be read in time is reported as unfinished, with a way to resume, instead of failed.
Through the Mammoth MCP server, an assistant can create projects and folders, rename things, check a job and upload files into a folder. Uploads and new exports wait until they finish and report what happened, unknown arguments are refused, a missing column is named alongside the real ones, and deleting views says what goes with them and keeps a dataset's last view.
The free PDF to CSV tool's Tables are ready email now comes from agent@mammoth.io with the biggest table attached as a CSV. Reply to it and the AI agent carries on with those tables in a workspace made for you; the tool's page says so, and suggests emailing your next file there instead of uploading it.
The free PDF and image converters email you the table as a CSV or Excel file, your choice, with a short note on what was pulled; opening it in a Mammoth workspace is the second way in. The email step no longer says the link starts a trial, and the offer after it is to save the steps free so next month's file runs through them on its own.
Press Enter in a field to press the form's main button in dialogs, panels, menus and the data editor's function panel, when that button is enabled. Text across the app that was 16px is now 14px.
mammoth-cli 2.4 and the SDK cover Repeat Rows, parameters in math rules, JSON key paths, datasets from a URL, downloading several datasets, moving a project and refining AI-written SQL. Recipes and schema find match more requests, and mammoth doctor says when the installed CLI is newer than the published one. Appends, deletes and job polls no longer report success before it happened, and an append can be undone.
mammoth dataset update-method sets whether a new file replaces a dataset's rows or adds to them, and file upload can set it for the upload it makes. An upload into a dataset reports the rows before and after and the batch it added. A workbook with several sheets or a password-protected file says what it is waiting for, with the command that picks the sheets or sends the password. A dashboard can be shared with a password from the CLI, and an automation's datasets can be added or removed without rewriting it.
A database connector opens on its connection form, and pasting a connection string or a block of details fills it in. Opening a table shows its query above the rows, editable in place, in a spreadsheet grid with type tags, and ticking columns rewrites the query. Tables show the database's row estimate, SQL Server, Oracle and SAP HANA list every schema's tables, and Save as a dataset says what you get and how it stays fresh. A connector draft whose save failed can be saved again, a rerun that failed partway no longer stays running, and Profile Settings is one page.
When a dataset's next file arrives, Mammoth adds it the way the last one was added: the same workbook tab, the same way of reading it, including a read Mammoth worked out on its own, and the same ignored columns, so a weekly replace goes straight through. Settings › How new files are added shows the tab, the read and the columns, with a switch to add files with the same layout without asking, and the panel says when a file was added the same way, with Undo.
Using a template with your own Excel workbook asks which sheet to use when the workbook has several, showing each sheet's row count, and starting from your own data no longer fails at random with a disabled-feature message.
Share a dashboard with anyone who has its link and its password. The password is 8 to 128 characters and is never shown again once set, and a viewer enters it once for the browser tab they have open.
Before emailing the Open tables link, the free converters say that opening it creates a Mammoth account and starts a 14-day Pro trial with no card, after which the plan moves to Free and the tables stay. Opened tables land in the workspace you pick, the Import into Mammoth link waits until the tables are extracted, and a download says which tables it left out.
When AI rebuilds a connector you reuse and the rebuild reads fewer fields than the saved version, the ready-to-save card lists the missing fields and offers to keep the saved version. A key you checked stays with the draft, connectors no longer cap rows you did not ask to limit, and a connector AI built can take another account through the API and CLI without a new chat.
Email a question or a file to agent@mammoth.io and the AI agent answers in the same thread, with tables set out as tables. Connect your address once from the link it sends to your login email; Profile Settings › Email the agent lists, moves and removes connected addresses. Attachments, pictures and scanned PDFs included, are filed in a folder in your project, and sending the same file again updates its table. Someone without an account gets a workspace of their own and an Open your workspace link.
Get the latest, Retrieve, Refresh and Run now show the pull on the control you pressed, from fetching to putting rows in with a progress bar, then say what changed, such as Added 8 rows or Nothing new, or why it failed, with Try again. The dataset's row in the list shows the same status, and Retrieve no longer asks you to confirm.
A new Repeat Rows step in Reshape, Group & Pivot copies every row a number of times, once for each value in a list you type, once for each date in a range (by day, week, month, quarter or year), or once for each number in a range, writing the value into a new or existing column. A range can start from Today or the start of this year, which move on each refresh.
Send to Dataset names its two modes by what each run does, keep this view's rows up to date or add a new copy of all rows, and lists the other views that already feed the chosen dataset. The workflow map shows each send's mode, and the column list fills the panel.
Select several datasets, or open a folder's menu, and download them as one zip of CSV files or one Excel workbook, optionally stacking tables that share columns. A single dataset's Download moves into its menu and names the view it will download.
The CLI keeps a record on your machine of every change it makes and how to reverse it. mammoth history list and show say what was done, history undo takes a change back, from restoring what went to the trash to putting a view's pipeline back as it was, and history resume picks up a multi-step run where a failure or an interruption stopped it.
mammoth recipe run does every step of a common task in one command: summarize or pivot a view, keep its top rows, find and replace, split or rename columns, fill blanks, remove duplicates, add a calculated column, look up a column from another view, export to CSV, Excel or S3, email a view, schedule a refresh, or build and share a dashboard. It asks once before it changes anything, --dry-run previews every step, mammoth recipe list shows them all, and mammoth how answers a goal with the recipe to run.
Repeated reads download only what changed since the last time, a write can be retried after a dropped connection without running twice, and a multi-step run can pass one step's result to the next. Every command describes the shape of its result, so scripts and assistants know what comes back before they run it. mammoth doctor also checks that the server is healthy.
Before your first dashboard, the Dashboards page starts from what you have: with no data it offers to upload a file, connect an app or paste a link and shows example dashboards, and once data is ready AI suggests dashboard ideas from your newest table to pick and build. The share dialog leads with people, with embedding on its own tab. When you change a view that sends to a dataset, an export or a dashboard, the data editor offers to pause those sends until you are done, and panels keep Cancel and Apply pinned to their bottom edge. A dataset's Summary shows the whole AI-written description of the file.
Email is an export destination: send a view to workspace members as a file, with a subject, a note, a choice of format, a preview and a test send to yourself, at most once a day or week if you like. Export schedules move to Automations as a Scheduled Export, and an export step says what sets it off. Motion stories export a 4:5 video for social feeds, and an embedded doc or deck keeps its own format, whole or one section, slide or chart. Connectors AI builds can read GraphQL sources, and a table saved beside the main one keeps its own columns.
Through the Mammoth MCP server, an assistant can change a dashboard by describing the change, rename and tag it, set its embed settings and get its embed code. Deleted views go to the trash, and the assistant can list the trash and undo a change.
Label/Insert, Find & Replace, Limit Rows and Smallest/Largest can take a project parameter instead of a typed value, so changing the parameter updates every step that uses it. Step cards show the parameter's name.
The Data Library, a dataset's data view with its pipeline and Explore, Dashboards, Templates, Monitor and Settings have phone and tablet layouts with one page bar that hides as you scroll, and editor links open in a read mode on a phone. The app downloads about a third less at startup, and dark mode covers the whole app.
A draft started from a saved connection that AI built reads its main table and can be saved again or widened; a refused pull says why, and datasets keep only the fields of the table you chose. Tables can be saved into a folder, and tables ready to save are marked.
From URL is back as its own item in the New dataset window: it reads the file first, shows its first rows, then asks whether the dataset should follow the link. A linked dataset gets Get the latest and can refresh on a schedule like a connector's, a copy behaves like an uploaded file, and either can switch later. The Datasets page marks linked datasets with a link badge, and Connections lists a project's linked datasets with when each was last fetched and any failure.
A PDF with several tables can now be automated: one rule sends each table to the dataset it fits, and a rule can watch files added at the project's top level, outside any folder.
A PDF that looks like one already read, by its name or by its tables' columns, offers Read it the same way, which adds its tables to the same datasets with the same instruction instead of making new ones, and the save step offers to add tables to the datasets they fit.
Send into a dataset checks columns before sending, lets you merge look-alike columns or choose where one goes, and skips sources that already send there; the result is pinned and opened beside the list, and rows say what they send to or are fed by. A dataset's summary card draws its workflow, joins included, and the panel's actions sit on a strip beside its main button.
While AI builds a connector, its question cards ask only what applies, mark optional answers and suggest a value, and an id a table's address needs is filled from your answers. A table listed under each row of another, such as invoices under each invoice run, is read row by row up to two levels deep, an empty table shows as empty instead of an error, and a scheduled pull refuses to save when part of the parent list failed.
The Source Interpreter preview shows up to 200 rows instead of 50 and says when you are seeing only the first rows; every row is still imported.
The Math step's Insert Parameter adds a number parameter to a formula or to SQL mode, and the step uses the parameter's current value each time it runs.
A chart that would have nothing to show is left off when a board is made from a template or a prompt, or a page is added from another table, and the reply names what was left off; the editor chat doesn't add one either. Templates whose charts would come out empty on your data are not suggested as a match, a table too small to chart starts its new page blank, and page tabs name only the page.
An automation's schedule sets a first run and an optional end date and lists the next runs, a monthly schedule can repeat every few months, and editing an automation keeps its start. A live link export can be edited.
The CLI and SDK can list every connection in a project and test one, cancel a step preview, see or cancel a pending plan change, and attach a file to a dashboard's chat.
The CLI and SDK can return the rows behind a dashboard figure and drill into it, on a draft or a published board, turn a chart description into a figure spec without saving anything, and list, create and delete your workspace's chart types. They can also read watched folders, their run history and where named files would go, change the order of a folder's rules, and add a held file anyway.
mammoth run reads one command per line from a file or standard input and runs them all in one process, with one sign-in and one connection, so a batch of reads takes about half as long as running each command on its own. Every line gets its own result, and a failing line stops the run unless you ask it to continue.
Commands start faster, a project command no longer looks up the workspace every time, the CLI remembers which dataset holds a view from one command to the next, and each view transform makes fewer requests to the server.
mammoth view export download saves a view as CSV, Excel, JSON, NDJSON, XML, YAML or Parquet. Reading a view's data can return only the columns you name, a column's display format can be set from the CLI, conditional formatting rules can be replaced in one call, and date conversion takes several input formats, with a strict mode that leaves an ambiguous day or month blank instead of guessing.
Create dataset works on every saved connection, including ones AI built, and opens the connector page with that connection already in use and each of its tables read. On a connector AI built, Refresh list has the AI look for more tables, optionally ones you name, and shows the new ones under Just found.
Through the Mammoth MCP server, an assistant can change, pause or restore one step of a view's pipeline and is told which later steps a change breaks. It can change, pause, restore or run an export and see its recent runs and their errors, list the tables of a database the project is already connected to, and work in every project you granted it when connecting. Its list of connected connectors now shows only the connected ones.
Tables opened from the free PDF to CSV tool land as ready datasets, with section headings and repeated header rows kept as data and dates that could be day- or month-first read in your project's order. With only one project to add them to they go straight in, and the Datasets page shows them arriving.
On the Datasets page, a folder an automation watches shows where its files go, and each file dropped in says whether it was added, with how many rows, or why not, such as new columns, a duplicate, a password or sheets to pick, with the next step. A duplicate can be added anyway, a file goes to the first matching rule in an order you set, the bell rings only when files don't go in, Monitor and each automation's History list the runs, and workbook passwords are not kept.
New dataset → Connect is one search box over every source, and a source Mammoth doesn't list yet can be built by AI from a name, a sentence or a link: the AI confirms what you meant, builds the connector, and its page shows each table it can read with sample rows. Tick the columns you want into Your table, and Save makes a dataset that refreshes daily.
Click a chart mark to filter the pages it reaches, see up to 500 rows behind it when signed in, or drill down one level with a breadcrumb back. A board can read a different table on each page, up to five, all from its own project, and new chart kinds include Icon stat, Pictograph and charts you describe, which can be saved as your workspace's own chart types.
A motion story can start at 0.5×, 1×, 2× or 4×, Ask about this moment stays on the moment you asked about, and title edits are saved. In the Dashboards library you can tick several boards, or shift-click a range, and add them all to a collection, and a collection that isn't shared keeps drafts as drafts until you share it.
Every page has one back arrow in its top-left corner that returns to where you came from and names that place on hover. Opened from a link or after a reload, it goes up to the page's parent instead.
The Dashboards library opens with its cards sooner, offers list or tile view, and sorts by last updated, most or least viewed, or date created. Cards keep the title readable, and a double-click opens a board directly.
Motion stories gain a weekly grain, a choice of date column and range, a line race chart, following one entity, pauses and pins on events, last year's values shown as ghosts, and Ask about this moment. Video exports in landscape, square or portrait.
The free PDF to CSV tool accepts any email address and sends one Open tables button, which opens the tables in Mammoth; a new address gets an account on that click, with no password to set.
A Data Consolidation automation shows Running, Needs review or Failed beside it while it works, so you can see when it is processing files or has stopped on files that don't match.
mammoth dataset list reports how many datasets the project has, and with names set to true returns every dataset's id and name in one call instead of page by page.
mammoth dataset refresh fetches a URL dataset's link again, and dataset and view lists show a URL dataset's source as its link's host. dashboard delete and dashboard share report what they did, and the SDK's embed settings call changes only the settings you pass.
Paste, drop or attach a picture, PDF, Word file or text in the editor chat of a dashboard, doc or deck. A screenshot can restyle the board to match its layout, chart types, colors and font once you approve a card showing what carries over, and a brief can steer a rewrite, and where a figure in it matches one in your data the two are shown side by side, while a figure your data cannot support is named as such; spreadsheets are pointed to Use my data instead.
Turning Explore filters into a pipeline task or a new view now opens from a menu beside the filters chip, shown whenever filters are on, and a column's value list says how many distinct values it has. Long names wrap inside delete dialogs.
Someone invited to a workspace, or added to one by an admin, signs in with a code emailed to them instead of setting a password first, and the email opens the workspace they were added to.
The Unpublished changes pill shows a count and opens a list of what changed since the last publish, who changed it and when, with Publish and Discard; Discard names colleagues whose edits would be lost and offers Undo. The embed panel asks one question, all pages, one page or one chart, and offers only what is published, which is what an embed shows.
The published dashboard viewer and Your dashboards show which account you are signed in as, note when the numbers you see are limited to your rows, and let you sign out or use a different account, which brings you back to the same dashboard.
mammoth how followed by a goal returns the commands to run, in order. An unknown command, option or column gets a did-you-mean suggestion, help lists every allowed value, mammoth capabilities lists known limits with their workarounds, and results suggest the next commands to run.
A Connections tab lists every connection a project uses, whether your own, Mammoth-managed or a live link, with what each one imports and exports. Every connection is health-checked daily, so a broken one shows up before a refresh fails, and an export's credentials link to the matching saved connection instead of being stored twice.
Download a view as JSON, NDJSON, XML, YAML or Parquet beside CSV and Excel. Exports to Postgres, MySQL, SQL Server and Redshift can append or upsert instead of replacing the table, Snowflake, Databricks and Google Sheets join the destinations, and a saved export can run on its own schedule, send only rows newer than the last run, and keep a run history with an email when it starts failing. One-off download files are removed after seven days.
On the REST API export form, paste a link to the API's documentation, with notes if you like, and AI fills in the form for you to review, along with what you'll need and any caveats. Nothing is saved or sent until you apply the form, credentials are never filled in, and Undo puts the form back.
Every function in the functions panel previews its result as soon as its settings are complete, in a window over the grid you can move, resize or minimize: rows and columns before and after, the columns it adds or changes highlighted, and tabs for changed values, removed rows, duplicates, groups and join matches. Smart fill previews when you click Run preview, and a new fill, top or bottom rows, or window step uses the sort it shows.
Bring in a JSON, JSON Lines or nested XML file by upload, link, connector or folder automation and Mammoth turns it into a table: the main repeating records become the rows, with nested fields as columns. When a file could be read more than one way, pick the list to use as rows or describe what you want, and the reading is saved and reused for later files.
Through the Mammoth MCP server, an assistant can total, count and average a view by group or by day, week, month, quarter or year, with Mammoth doing the arithmetic instead of the model. It can read each dashboard's KPI and chart values, link to the matching page in Mammoth, list the connectors your plan includes, and send you to Mammoth to connect one, so no password passes through the model.
mammoth auth login signs in to the CLI through your browser, or with a device code on a machine without one, instead of pasting an API token. Signing in again warns when it ends another stored sign-in, and signing out of one that has already ended says so plainly.
The Datasets page is redesigned, with a folder path and toolbar above one-line rows and a side panel you can drag to any width that opens on the dataset you just added or last had open. Its Summary card gives a one-sentence AI summary and what the dataset's tasks did, from rows in to rows out, and where the data goes; Explore opens the editor on suggested cards and Transform on the pipeline. A dataset with several views has a views switcher showing each view's health, and Move to trash can be undone.
Every upgrade button opens one plan picker inside the app, and a workspace on a trial can pay for a plan from it; backing out of checkout leaves the trial running.
Select pending batches in a dataset's batches list and delete them. Column mapping no longer needs a separate Validate step, because Apply runs the check itself, and the unmapped-column count is correct.
A dataset made from a web link keeps that link, and Refresh from URL fetches the file again and runs it through the dataset's recipe. It works on demand for a link to a single CSV file, and the new rows are added or replace the old ones according to the dataset's update method.
A dataset's activity history can include the events of its views, and search matches dataset and project names, so a view called View 1 can be found by its dataset. Exporting one object's history works, and the log pages reliably as you scroll.
The CLI and SDK gain commands for editing explore cards of every kind, exporting a card as an image and adding it to a dashboard, reading raw view data including the time in dates, and working with collections, the engagement report and templates with your own data. A schema diff compares two datasets before an append.
Settings > Connected apps has a Connect an AI assistant card with the MCP server address to copy and setup steps for popular AI assistants.
PDF extraction can run on your workspace's own AI provider key, picked from a list showing each key's provider and model.
When you connect an AI assistant over MCP, tick Read-only on the consent page and it can read your data but change nothing. Connected apps shows each app's access, and reconnecting never widens it.
Dashboard cards sit in full-width rows with no gaps: resize a row from a card's corner or the row's edges, drag a card into another row, reorder KPI tiles, and undo layout changes. A run of hand edits shows as one line in the editor chat, with the details on hover.
A SQL step generated from a description is checked against your actual rows before it is offered, so asking to blank some values no longer drops the column or deletes rows. You can refine a generated query, see how your request was read, and keep your prompt; a SQL step reads only its own view.
The Extract JSON rule can read a key nested inside objects and lists, such as a company's location country, in one rule instead of one rule per level. Suggested keys list every nested value, and key suggestions load again.
The engagement report opens on one sentence saying how many of the people a dashboard is shared with opened it, followed by three headline figures and views per day. The Audience tab is slimmer and the library's board panel uses the full height.
On the dashboard site, readers land on Your dashboards, which lists their collections and the dashboards shared with them, and a collection, a shared board and the no-access screen each link back to it.
Open the activity history of one dataset, view or automation, including events that used it as a source or destination, and search the Activity Log by name.
New CLI commands create one filtered view per value of a column, read and set a view's explore panel, add a chart to a dashboard, overwrite a column with an expression, take the first word of a text column, and return the public URL of a live link. A filter that removes no rows today can still be staged with an opt-in flag, and sending rows to a new dataset no longer needs a name.
Start a dashboard context by typing or dropping files, and review what was read before saving; the name and slots fill themselves in. A slider sets how strongly a background image shows in a title band or cover. Published dashboards open on their first page, then on the page each reader last viewed, and collections gain a Set order control and a collapsible shelf.
See how a shared dashboard is being read: how many of the people it is shared with opened it and came back, engaged time, which pages and tiles were seen, each person's visits, and the days and hours people read it. Send a reminder to people who have not opened it yet.
Connect an AI assistant or any other MCP client to your Mammoth workspace: add the server at mcp.mammoth.io/mcp and sign in with your Mammoth account. Available on every plan.
Upload your own file to a dashboard template and keep working while it is prepared; the board shows progress and a notification says when your version is ready. AI proposes your version of the template, including calculated columns added as pipeline steps and extra tiles for columns the template had no place for, and you review every change before applying it. When a file does not fit, you get options instead: reshape a month-per-column file, pick a template that fits, or build a new dashboard in the template's design.
Settings shows API tokens and external API keys in two lists, newest first, with who created each key, when, and its scope. A new key's secret is shown once when it is created.
New CLI commands and SDK methods cover dashboard embed usage, dashboard format previews and audiences, workspace search, folder paths, resuming a paid plan with a scheduled downgrade, checking what a delete will affect, copying a project, finding a dataset by name across projects, every explore card option, and reading several schemas in one call.
Group several dashboards into a named collection and share it as one; people invited to it can open every dashboard in it. Viewers get a home page of their own with their collections, and published dashboards open at a fixed width by default.
Deleting or restoring a task, view, dataset or folder first shows what changes downstream, including the exports and dashboards that depend on it, with links to open each one. Dashboards now go to trash and come back together with the views they are built on. Restoring from Trash also lists the exports that come back with an item, and a view can be restored without its dashboards.
When an uploaded file holds several sheets or several tables on one sheet, preview each one and create a dataset from every table you want, in one pass.
Apps that support OAuth can connect to your workspace once you approve them on a Mammoth consent page, choosing the workspace and project they may use. See and revoke the apps you have approved under Connected apps in settings, and workspace admins can register their own OAuth apps.
The sign-in pages and the sign-in code email fit a phone screen, with full-size fields and buttons; desktop and tablet are unchanged.
The duplicate check shows sample duplicated rows instead of only a count, variant spellings say how each one differs, a project check can run against a single view, and creating a dataset reports the final name it was given.
Appends, replaces, batch creation and database exports run from the CLI now check the destination first and refuse a mismatched column type, an incomplete column mapping or an unconfirmed table replacement. A dry run names the exports a pipeline rerun will fire and any columns they would leave blank.
Create one conditional-format rule that covers several columns, or the whole row, from the CLI using column display names.
Find datasets by name, column name or a sampled value with a new search command in the CLI and SDK.
Explore from the CLI and SDK can return a running total per bucket, figures are rounded for display, and dataset find can match on columns.
Send a chart from an explore card straight to a dashboard. Explore cards also gain a standard deviation measure and keep banded axes in their natural order, and your explore state is kept per user.
Read a project's Monitor Needs Attention list from the CLI and SDK, including pipeline errors, pending data and checkpoints awaiting approval, with the dataset each item belongs to.
List pending workspace invites, and revoke, resend, delete or change the role of an invite from the CLI and SDK. Removing a user from a project from the CLI works again.
While editing a dashboard you can see which colleagues have it open and where they are working, and a conflicting save names who made the other change. Before you publish, you see whose unpublished changes the publish will include, and they are told when it goes out.
The Python SDK is now asynchronous: calls to the API are awaited and the client works as an async context manager. This is a breaking change for scripts written against earlier versions; the CLI works as before.
AI-built custom connectors run their generated code in an isolated environment, and can now export an entire Elasticsearch or OpenSearch index rather than stopping after the first page.
See who reads your dashboards, documents and decks: where they are, what device they use, how far they get and what they ask. Editors get a summary in the editor header, notices about notable activity and a weekly digest.
A dashboard now belongs to the project of the data it was built on, and that project's roles decide access: Admins and Editors build and edit, Viewers see published boards. The Dashboards page shows each board's project and can be filtered by project; sharing with people outside the project stays view-only.
A dashboard's buttons each do one job: Sync pulls new data into your draft, Publish makes the draft live, Share sets who can see it, and Updates says which of these is waiting. The Share dialog is one column, and changing who can see a board no longer marks unpublished changes as published.
The Source Interpreter, which uses AI to read a messy file, reads messy spreadsheets more reliably, including timesheets, stacked headers and PDF-style numbers. Excel files no longer import as a single cell, and special characters are no longer garbled on import.
One click re-aligns a hand-arranged board so edges line up, widths are even and each row shares a height. Title band edits now stay put after a save, and the preview shows the look you saved.
Title bands gain a soft tone that suits light and dark styles, line and wash textures, and a short label above the title. The Editorial theme's headings use a more contemporary serif.
CLI commands that change data now report the resulting state, flag a change that has not settled or that broke a downstream export, and can hand back a still-running job instead of timing out. Data warnings point out values spelled several ways and condition values are checked against their column type before they are sent.
When a messy upload or Google Sheet is offered for reshaping, you can choose Import as is to keep the data exactly as it was read, and future files for that dataset are imported the same way.
The free PDF to table tool keeps numbers exactly as printed, keeps separate tables apart, gives tables readable column headers and drops footnote markers from labels. Tables are no longer lost when a page is hard to read, and a stalled extraction ends with a message instead of spinning.
Start a dashboard from a ready-made template inside Mammoth. Each template opens on sample data first, then moves onto your own dataset, with a rating that says how well your data fits it.
When you attach or edit the context the AI uses for a dashboard, a review shows exactly which items would change before anything is applied, and accepting it saves a version you can undo. Requests such as "lower is better" now land on the board, and suggested wording cannot introduce terms your board and data do not support.
Every chart's menu opens a panel listing the columns it reads and how each is used, including the filters applied to it. Editors also see the query behind the chart.
Five templates for venture-backed companies and their investors: SaaS Metrics, a startup board report, an investor update, a startup board deck and a portfolio KPI rollup. Each opens on sample data.
Moving a template from sample data onto your own is smoother: you can add new data without leaving the board, the preview draws your real numbers, and the fit rating says plainly when a dataset cannot fill the board. After the swap, insight text names your columns and charts that cannot trend on your dates are left out.
Opening a workspace link you cannot access now explains why and offers a workspace switcher, instead of silently redirecting. If you have no other active workspace, you can create a new one from that page or from the suspended-workspace page.
Summarize a view's data from the command line: group and aggregate, bucket dates and numbers, and explore a single column as a trend, distribution or list of top values.
Each command that changes data reports whether the change landed, with row counts before and after, and flags writes that empty a view or joins that match poorly.
Download a dashboard as a Power BI or Tableau file from the Python SDK or the command line.
The command-line tool can manage dashboard embedding: embed settings, keys, allowed sites and usage.
An API token can cover all projects in a workspace, including ones created later, and changing a token's project takes effect immediately. Members without permission to manage tokens see why the option is unavailable.
The New automation wizard starts with the destination, tracks which steps are complete, and keeps a running summary of your choices alongside, across all automation types.
Paste a list of addresses, such as an email's To: line, into a dashboard's invite field to share it with everyone at once; names and duplicates are cleaned up for you.
Set how dates are shown for a whole project; every new dataset's date columns follow it, whatever their source. New workspaces also start with US or UK date order based on where you sign up.
When a page is too large to extract, the free PDF converter keeps the tables from the other pages and explains which pages were skipped and why.
REST API connections can authenticate with OAuth 2.0 client credentials, using a client ID, client secret, token URL and scopes.
If a PDF page is too large to extract within the plan's limit, that page is skipped and the tables from every other page are kept, with a message saying which pages were skipped.
New projects read dates as day-first or month-first from your browser's time zone, turned on by default, and the setting folds to a one-line summary you can open to change.
API tokens are now a single token issued by Mammoth, shown once when created and sent as a standard bearer credential, replacing the earlier key-and-secret pair.
Dashboards can chart trends by day or week, and charts can show minimum, maximum and median values.
Signing up from the free PDF converter now brings every table you selected into your new workspace, not just the first.
Upload HEIC photos and TIFF images, including multi-page TIFFs, and extract tables from them like any PDF; the file keeps the name you gave it.
A PDF or Word document dropped into a dashboard's context is now read by the AI that builds the board, not refused.
HEIC and TIFF images can be previewed and converted in the browser.
The two-factor sign-in screens have a refreshed design, and sign-up can verify your email address with a one-time code.
When an appended file's columns do not match the dataset, it waits as a pending batch, and you can map its columns to the dataset's and check the result before adding it.
A new comparison page picks two meaningful groups from your data to compare, so it never opens empty. Presentation templates now preview with a sheet of their slides instead of just the cover, and chart slides no longer clip their axis labels.
Put a live dashboard, or a single tile of it, inside another website or app with an embed code; it keeps updating as the data does.
The free PDF converter has a refreshed design. With a personal email address, it now offers to open your extracted tables in a free Mammoth workspace instead of only rejecting the address, and the option to automate the extraction appears before the email step.
A view's Data In / Data Out menu now lists the dashboards it feeds, with a direct link to each one you have access to.
The connection-count limit is gone from the connector picker: you can create as many connections as you need, and every paid plan includes the full connector catalog.
Before you commit an uploaded file, PDF or Google Sheet, the review step lists each column with the type it was read as and its first values, and lets you choose manual or scheduled refresh.
Q&A answers are set at a readable width and can use paragraphs and bullet lists. The Q&A page fills the screen, fits on a phone, and redraws its charts as the window changes size. Saving a context no longer drops text still in the paste box.
New users land directly in their workspace after signing up, with no profile form to fill in first. Someone who chose a template from the public template gallery lands on that template.
The build screen names the format being created, publishing sits behind a single button with its options alongside, Q&A turns show when they were asked, and a data-failure banner can be dismissed.
Upload a messy CSV, Excel file or PDF and AI works out how to reshape it into a clean table, showing a preview before anything is committed. The steps you confirm are saved as a recipe and applied to each new batch of data that arrives.
Plans now price storage separately from the plan itself, so you can add storage without changing plans. Plan limits are applied in the product, with guidance on what to do when a workspace is over a limit, and the Change Plan window lays out the options without clipping.
Q&A understands relative periods such as "last quarter," chooses a sensible time grain for trends, and describes only the data its chart actually shows. Answer charts use the full width of the card in the board's own colors, and can be expanded to full screen.
Project settings now separate how ambiguous dates in uploaded files are read from how date columns are shown, and state the default when nothing is chosen.
Managing columns in a view and editing a dataset's schema now happen in one shared Column Manager, with a confirmation before a change that affects the source data.
Dark mode has been updated across the app.
The dashboard editor now fits the board to the screen the same way preview does, whether side panels are open or closed.
Stack several CSV files or Excel sheets into one table: pick which sheets take part, line up columns that don't match, preview the result, and receive the merged file as CSV or Excel by email.
Browse ready-made dashboard templates on mammoth.io without signing in, each with a preview picture and its own detail page.
Bulk Replace can match values with a dynamic condition, and the matched values are worked out each time the pipeline runs, so the step card shows what was actually replaced.
Set rules that automatically delete or suspend a dataset's older batches by age, by how many to keep, or by a condition you describe, with an optional approval step and email notifications.
Turn a connected, cleaned dataset into a dashboard, a presentation or a document, built by AI from your real columns and kept current as the data refreshes. Change the style, layout and focus by asking in plain language, add a Q&A page readers can question, and share it publicly, behind a password or with signed-in viewers.
Creating an API token no longer requires a description, and the project is picked for you when the workspace has only one.
Import failure emails for SQL Server, PostgreSQL, Redshift and MySQL sources now explain a lost connection in plain language instead of raw driver errors.
When you add a dataset by upload, URL, clipboard, sample file, webhook or connector, a placeholder row appears in the Data Library right away while it is processed.
A dataset pulled from a third-party connector now shows which saved connection it uses, alongside its query, in the dataset's properties.
Numbers written with regional decimal and thousands separators are read as numbers when data is imported or converted.
Pipeline errors in Monitor now show when the failure happened and where the view lives, so you can triage without opening it.
Automation options are grouped with a short description of each, the create wizard marks completed steps, the destination folder is shown from the start, and running an automation manually is easier to follow.
Empty and space-only values show as [blank] and [whitespace x N] in Explore cards, filter details and pills, condition suggestions and Bulk Replace lists, so you can tell them apart.
Datasets and files show which automations act on them and how those automations are doing, so you can see at a glance what is running and what needs attention.
Work with Mammoth from a terminal: install with one command, sign in interactively or from a credentials file, and create folders, load data and run other operations. Commands wait for the jobs they start, ask before destructive actions and explain any usage error.
Creating and editing an automation happens in one guided window, and automation summaries show a short preview you can expand instead of stretching the page.
Select several files by dragging across empty space, then drop them onto a folder or a breadcrumb segment to move them, with an undo right after the move. Folders can also be expanded to show their contents in place.
Rename a dataset or view from edit icons beside its name in the preview panel, or from Rename in the dataset's options menu.
Adding a data check starts by picking the check type from tiles that describe each one in plain language, then setting it up in a single card. The value range check can now require every value to be negative.
Errors and warnings on a pipeline step appear at the top of its card, and stay visible as an icon with a tooltip when the card is collapsed.
Column name changes in dataset settings register as you type, without pressing Enter, so an edit is no longer lost when you close the window.
Checkpoint approval and alert emails show the dataset name alongside the view name in their link to the pipeline.
Search on the Data page finds a dataset or view by its folder path as well as its name and tolerates near-miss spellings, and the dashboard list shows each dashboard's sync status.
A snippet can hold any reusable value, not only SQL. When you add one to a rule, choose to reference it so it stays linked or paste its current value, and hover a snippet in the SQL editor to see its details.
Files waiting to be added to a dataset appear as pending batches on that dataset, marked when they need your action, and several pending batches can be tracked at once.
Checkpoint approvals and data check items in Monitor's Needs Attention tab open the view they belong to.
Adding or using your own AI provider key gives specific messages when a key, model or plan cannot be used, picks a sensible default model for each provider, and sets web search per provider.
The Checkpoint panel has a cleaner layout, with clear cards for notify-only and pause-for-approval, tidier email and webhook rows, and a collapsible webhook payload.
Copy one or more pipeline tasks and paste them into the same view or another view's pipeline; pasted tasks open as a draft, and database export steps keep their saved credentials.
A view with no rows to show now says so plainly, and a view whose source has no data no longer shows the wrong message.
Premium connector cards show how many of your plan's premium connections are in use, and the limit applies across all premium connectors together.
Deleting a dataset, view, dashboard or automation moves it to Trash, where you can restore items one at a time or in bulk, or delete them for good.
Branch Out, crosstab and BigQuery export steps show whether they replace or combine data right on the step card, without reopening the step.
When a pull from a connected source fails, you get an email so you can act on the error.
Bulk Replace places its result column right next to the source column, so you can compare original and replaced values side by side.
Monitor opens as a window over the page you are on, so you can check pipeline status without leaving your work.
The Parameters panel no longer flickers on hover, its edit window sizes to its content, and parameters are always workspace-wide, so there is no scope to choose.
A column you drag to a new position stays highlighted until you drop it, so you can see which one is moving.
Connect a mailbox and bring in the CSV, TSV and Excel files attached to incoming emails, without downloading them by hand.
Every change to a pipeline is saved as a version you can browse with its timestamp and task details, and you can restore an earlier version or copy tasks out of it.
If a workspace is suspended and you belong to others, you can switch to another workspace straight from the suspended screen.
Ask the dashboard chat for several edits in a row: they queue and run one at a time, so one edit no longer undoes another, and a waiting request can be changed or removed before it runs. A refreshing dashboard shows a loader instead of flashing white.
Pull messages from Apache Kafka topics straight into a dataset, connecting with plain or SASL_SSL authentication.
Subscribe to topics on an MQTT broker and collect sensor messages into a dataset, with column types worked out from the message contents.
Send a dataset to any REST API endpoint with POST, PUT or PATCH, using no authentication, an API key, a bearer token, basic auth or OAuth2.
When a subscription or trial ends without renewal, the workspace moves to the Free plan instead of being scheduled for deletion.
Add your own API keys from several AI model providers to use with GenAI steps and other AI features, with clearer validation messages when a key is added or switched.
Write a data check rule as a plain-language description and have it turned into an expression; turning off notifications on an existing check now clears its recipients.
Highlight cells that match rules you define, including color scales, and see a clear notice when a rule refers to a column that is missing or has changed type.
When connecting Dropbox, choose which folders the connection can use instead of the whole account, and pick files without being asked to reselect them.
Have Mammoth collect files from your cloud storage on a schedule, filtered by folder, and bring them in without manual downloads and uploads; sources can also be removed from an existing collection.
When a column holds JSON, its column menu offers JSON extraction as the first action, including in files with only a few rows.
Preview a dataset in a resizable pane, or expand it to a larger view, before selecting it for a join, lookup or other step.
Pipeline step cards for SQL and AI-built filters, metrics and math show both the plain-language intent and the query or condition behind it.
Send a dataset to Tableau Server as an export destination.
A new AI dashboard shows its pages as each one is ready, with progress you can follow and a way to cancel, and starting a dashboard from a suggestion keeps your prompt. This was the earlier dashboard product, replaced in August 2026.
The in-app plan picker and comparison reflect the current self-serve plans, including a Free plan, and features a plan does not include open an upgrade prompt instead.
Dashboards can show values on a filled map of the world, US states or India states, and filters set to zero or false also include blank values. This was the earlier dashboard product, replaced in August 2026.
The Resource Finder opens with its search bar ready for typing, opens automatically when you add a Join or Lookup, and selects the dataset for you when only one matches.
A banner counts down to a scheduled app update so you can finish what you are doing first.
Import data from and export data to Azure Blob Storage.
The condition builder has an updated, easier-to-read layout for setting up conditions.
Connect to Microsoft Dynamics 365 and bring its data into Mammoth.
Set a new member's workspace-level permissions in the redesigned invite dialog, and see invited users more clearly in User Management.
The Parameters & Snippets panel has an updated layout; parameters set to 0 now display correctly and long names no longer overflow.
Notifications arrive as they happen, without waiting for the app to check for them.
Choose which SharePoint document library to import from, for sites that do not use the default one, with a notice when the chosen location has no files.
Move through every section of the transform menu with the Tab key.
A failed checkpoint or data check no longer stops you renaming, reordering, sorting, formatting or hiding columns; only a failed task step does.
Math, Metric and conditional Filter steps accept a SQL expression directly, or generate one from a plain-language description, and the result can be reviewed before it is applied.
Send a dataset straight to Microsoft OneDrive from the export destinations panel.
Dataset schema settings no longer let you remove every column: at least one must remain, or a new one must be added, before you can save.
Connecting to SFTP uses one connection dialog, with password or private-key sign-in, and the file picker leaves out hidden folders.
The Transform menu groups its tools by category, lists SQL beside them, and has one box that searches the tools or suggests steps for what you describe.
Connect the REST API connector to services that require OAuth authorization, and reauthorize a connection when its access expires.
A new finder for choosing datasets and views in Join, Lookup, Branch Out, Group & Pivot and other steps lets you browse folders and search; in Join and Lookup it opens at the current dataset's folder and no longer offers the current view as the other side.
When connecting Google Drive, pick the folders Mammoth may use instead of granting access to your whole drive; imports are limited to files in those folders.
Group & Pivot accepts several value columns when the Columns section is in use, so you can aggregate more than one field in a single pivot.
Import data straight from Microsoft OneDrive by browsing your folders and picking one or more files.
Drag columns into a new order in a dataset's schema settings, alongside renaming, removing and changing column types.
The REST API connector can now pull from an endpoint once for every record returned by another endpoint, passing each ID as a query parameter, so data that is only available per item (such as per project) is collected for all of them.
The Fill Missing Values step shows an illustration for each way of filling gaps, including filling from above or below within groups, to make the right option easier to pick.
Pipeline steps are reordered by dragging the handle on each card, so clicking elsewhere on a card no longer moves it by accident.
The Remove Duplicates step can compare only the columns you choose, instead of whole rows, when deciding which rows are duplicates.
Project Admins can invite people from outside the workspace straight into a project, and project settings are limited to project Admins. Workspace members see API keys as read-only, cannot use premium connectors, and no longer see the Activity Log.
Data Update is now called Auto-Sync throughout the app, with clear on and off states.
Add a checkpoint to a pipeline as an Alert, which notifies recipients by email or webhook and carries on, or as an Approval Gate, which pauses the pipeline until someone approves. Pending checkpoints can be approved without opening the pipeline, and Monitor is now split from a separate Pending Items view for everything awaiting action.
Download a dashboard as a PDF from the dashboard toolbar; each tab becomes its own page. This was the earlier dashboard product, replaced in August 2026.
Add a data check to a pipeline to test the data as it runs, using project parameters if you like. Checks awaiting attention appear in Pending Items and are sent by email.
Adding an export to a pipeline starts with a step that lays out the destinations, from Mammoth datasets to external databases and live links, before you configure one.
Automations can be scheduled to run every hour, and an automation's summary shows the schedule it runs on.
Define parameters and reusable SQL snippets once at project level and use them across pipelines. Changing a value marks the affected pipelines as stale and lets you rerun just those; deleting one keeps its current value in the steps that used it.
A minimized pipeline view keeps more of the grid in sight, pipeline cards are redesigned and expand or collapse one at a time, and the function picker gains search, categories and tooltips on function names.
Import data from SharePoint: browse its folders, select one or several files or a whole folder, and refresh the dataset with the latest file contents.
Columns created by a SQL step are placed next to the columns they were built from instead of at the end of the grid.
Plan & Storage settings show storage used by each dataset and, when you expand it, by each of its views. The tab is available to every workspace, whatever its plan.
Rename columns in bulk from Dataset Settings: standardize names to formats such as snake_case or camelCase, or have AI suggest descriptive names.
Profile Settings have a new layout, and the security section shows when two-factor authentication is already on instead of offering to enable it again.
Automations pick up files in nested subfolders, run as soon as they are created, and check connection details when a data refresh automation is added or edited.
Connect to an SFTP server with your own private key and username, with an optional passphrase for encrypted keys. Password connections no longer try key-based sign-in first.
Monitor has an Automations tab showing running and queued automations, with live progress through validating, appending and finalizing, and a countdown for queued runs. A data consolidation automation now targets a single destination dataset.
When a payment is due, retry it with the card already on file instead of going through checkout again, and plan status updates promptly after payment or a trial converting to paid.
Choose the file name an SFTP export writes, and decide whether each run overwrites that file or creates a new uniquely named one.
Duplicating a view and querying its rows run in the background, so very large datasets no longer freeze the screen while they work.
Pipeline steps run without blocking the screen, so you can keep building the pipeline while earlier steps are still processing.
Upload XML files, including XML files inside a zipped folder, and work with them like any other dataset.
SFTP folders load one level at a time as you expand them, so servers with many nested files open quickly, and folder counts stay correct when you search.
New projects use your browser's local date format by default; setting a project-specific date format is now an opt-in.
Import files from a Google Cloud Storage bucket using a service account: browse the bucket, pick a single file or a whole folder, and pull new files on later refreshes.
Create a new workspace from the sidebar and choose its plan and payment there. Plans, add-ons and billing are managed in settings, and reaching a plan limit or a premium feature shows an upgrade path instead of a request to contact sales.
Send a dataset to a SharePoint location as an export step in the Data Editor.
Importing many files from an SFTP folder at once runs in the background, and automations that append a folder of new files into one dataset handle them together in a single run.
The Data Library, its search and storage settings stay responsive in workspaces holding a large number of datasets and views.
API keys in Settings are shown masked rather than in full.
The Project Settings window has a cleaner layout with search and role management, matches the project creation flow, and lets you set access to only you, everyone in the workspace, or selected users, adding several people at once.
When you describe a transformation in plain language, separate Apply Now and Add to Pipeline actions make it clear whether the change runs right away or joins your pipeline.
Joins and lookups made in another view now show up in the Dependent Views menu of the view they pull from, so you can see what relies on it.
The Edit Cells header shows more clearly that you are in editing mode, with a tidier layout and buttons.
Edit a query directly without extra clicks, and run it straight from the keyboard when creating a dataset from a query.
If the app open in your browser is out of date, Mammoth asks you to refresh instead of leaving screens unresponsive.
Join on numeric or date key columns using an inclusive range instead of an exact match, so rows pair up when a value falls within a set distance of the other.
Set the date format for date columns from the preview panel and file details, and have it apply consistently to previews and future uploads. Edit Data Settings drops the automatic option and only asks about columns whose dates are ambiguous.
Converting text to a date suggests the source format it detects and lets you enter a custom one when none fits; converting a date to text lets you pick the output format. The pipeline step shows "Source format" when a custom format is used, and numeric-to-date conversions skip the source format setting.
Dataset settings and the preview panel have a refreshed design with clearer icons, spacing and navigation, making dataset details easier to scan.
The Functions panel reopens in the state you left it, including an unfinished step, and the pipeline keeps its scroll position and preview when you move between views.
The export menu in the Data Editor groups its options more clearly and has streamlined collapsed and expanded views.
The Data Quality view groups issues, warnings and recommendations more clearly, so you can judge a dataset's health faster. It is always on, with no separate setting to enable it.
The item selected in the preview panel stays selected as you move between the Data Library, Dashboards and Orchestrations pages, and the Data Library reopens where you last were.
When a change you describe in plain words can't be turned into a step, the message now explains why.
A search box in the connector list under Add Data lets you find a source by name instead of scrolling.
An empty Data Library has a new starting view, and dragging files onto it to upload works more smoothly.
Webhooks now have their own entry in the left sidebar of Add Data, so creating a dataset from a webhook is easier to find.
When pulling data from a third-party source into an existing dataset, choose next to the dataset name whether the new data replaces what is there or is combined with it.
A progress widget shows your uploads while they run, and long file names display cleanly in it.
Group and aggregate data and build a crosstab in one Group & Pivot step, including joining text values together within a group; it replaces the separate Crosstab, Group-Aggregate and Concatenation functions.
Share a dashboard publicly by link or invite people by email, who confirm their address before viewing; dashboard owners can see total views, average time spent and who viewed it. This was the earlier dashboard product, replaced in August 2026.
Transform opens a single window where you either describe the change you want in plain language or pick a transformation tool, and it remembers which you used last; the task's details are shown before you add it, and the pipeline opens so you can see pending changes.
Changes to a dashboard appear in place as they finish, without reloading the whole page. This was the earlier dashboard product, replaced in August 2026.
The Data Quality window shows the view's quality score, completeness, critical issues and recommended fixes more clearly.
Add Data has a new layout with redesigned connector cards, new sample datasets, and clearer feedback when you drag and drop a file.
Bulk Replace can reveal spaces and other whitespace in values so replacements match exactly what you expect, and its suggested replacements are more relevant.
Export now sits in the top-right of the Data Editor and opens in the same side panel as other functions, with one consistent layout for every destination.
A new Insights panel in the Data Editor uses AI to point out key observations and possible data issues in the view you are looking at, with no separate setting to switch it on.
Set a date format for a whole project so dates are read the same way across its datasets, and when a file has ambiguous date columns you are asked to confirm the format once and apply it to all of them.
Publish as Dashboard in the Data Editor suggests dashboards to build from your data, or lets you describe the one you want. This was the earlier dashboard product, replaced in August 2026.
Describe the dataset you need in plain language, including the fields you want, and Mammoth creates a structured dataset you can start working with.
Asking the AI Prompt to hide, show or sort columns now changes how the grid is displayed instead of adding a pipeline step.
Paste copied rows straight into Add Data to create a dataset, without saving a file first.
Leave a workspace from User Management or your profile settings; if you are its only owner, you are asked to transfer ownership first.
Start an orchestration right away with Run Now, and existing data refresh schedules are now managed as orchestrations rather than from the dataset preview panel.
Connect to Apache Hadoop with a host, port and credentials, browse its schemas and tables, and bring them into Mammoth.
The side navigation bar, folder breadcrumbs and the Transform and Export menus have an updated design, and breadcrumbs list only folders from the current project.
Describe what you want to analyze and Mammoth builds a dashboard from your data, choosing the charts, summary cards, filters, layout and theme. Preview it for desktop, tablet or mobile, choose how it stays in sync with the data, and share it by link. This was the earlier dashboard product, replaced in August 2026.
Sign in with a one-time code sent to your email and switch freely between that and your password. The sign-in and sign-up pages are redesigned with simpler forms, and bot protection runs in the background, falling back to an email code only when a sign-in looks suspicious.
A new Orchestration panel replaces Automation and brings workflow operations together: refresh third-party datasets manually or on a schedule, combine or replace data when new files arrive, and send automated notifications about workflow updates, with an unsubscribe link in each message. Switching a scheduled orchestration back to manual runs now works.
Open a data quality view from the Data Editor to see a score for your data along with completeness, critical issues and recommendations.
In Bulk Replace, move all or selected values from one group to another, and choose whether searching for values is case-sensitive and whether it uses fuzzy matching.
The Copy Columns function has a new design in line with the rest of the functions panel, and copying into an existing column now shows the result correctly.
The Activity Log records more kinds of events, shows its columns in a clearer order and filters by date more reliably. Entries for projects that have been deleted are no longer clickable and say why on hover.
Datasets brought in from third-party connectors now have data update settings you can review and change, as uploaded datasets do.
Hover over a task in the pipeline to see when it was last changed and by whom.
Switching between views keeps your search and scroll position in explore cards.
A copied or newly added column now appears right next to the column it came from instead of at the far right.
Upload a PDF or an image, including from a URL, and Mammoth pulls the tables out of it into a dataset you can prepare like any other.
The SQL query rule now accepts queries that use UNION to combine results.
Workspace owners can delete their workspace themselves, which also cancels its subscription.
Copy every column name in a dataset to the clipboard in one click from the column browser or dataset settings.
A task created by describing what you want is applied to the pipeline immediately, unless the pipeline is in Draft Mode.
Clear a column's decimal formatting from the number formatter, and the column menu shows when no formatting is applied.
Metric cards and the metrics panel have a cleaner layout that is easier to read, and metrics refresh when the view's data changes.
Delete your own user profile from your profile settings.
Files you upload, including additional files and profile pictures, are scanned for viruses, and if a file is rejected you are told which one.
Choosing a plan uses a redesigned page for comparing the available plans, and you can still switch workspaces from it when you belong to more than one.
See a workspace-wide log of what people did to datasets, views, projects and automations, with search, filters by timeframe and activity type, event details, and export.
Asking for a SQL query in plain language produces more accurate queries that need fewer manual corrections, and you see progress while the query is being written.
Rule and function panels have clearer dropdowns, illustrations and descriptions, better-aligned controls and smoother cursor behavior, so building a rule takes fewer steps to understand.
Profile a dataset to see its structure, completeness, consistency issues and key statistics, with generated charts and recommendations for improving it.
The sign-in, sign-up, password reset and email verification pages have a new, simpler design.
When you switch a join to another table, key and column selections carry over wherever the new table has columns with the same names, so you don't rebuild the join from scratch.
Deleting a workspace cancels its subscription and suspends it, and a suspended workspace can be restored.
Review and manage the column renames, format changes and other display changes you have made to the data grid in one place.
The preview panel shows a resource's options as buttons, including moving it, instead of hiding them behind a menu.
The free PDF converter makes it easier to explore the tables it extracts, and only offers the projects you belong to.
Choose a plan when you sign up, check out on your own, and pick or change your workspace's plan from settings; a workspace owner can also delete a workspace themselves.
When draft mode is on, the pipeline toolbar says so plainly, and the draft banner sits at the bottom of the pipeline out of the way.
Sessions that sit inactive past their timeout are signed out automatically.
Source cards in the pipeline show more information about where the data comes from and its current state.
Explore cards can show values by distinct count, alongside the existing aggregations.
Exports to BigQuery can be limited to the datasets and tables you allow, with more flexible export options and better handling of credentials.
Paste a list of email addresses separated by commas, semicolons, spaces or new lines when inviting users, and it splits into separate invites; other multi-value input boxes split pasted lists the same way.
The Data Library shows how much storage each dataset uses, and the sidebar shows your workspace's storage use at a glance.
Ctrl- or Shift-clicking an item that is already selected in an Explore card deselects just that item and keeps the rest of your selection.
Pin columns to the left from a column's header menu so they stay in view while you scroll; pinned columns are remembered per view, for you.
Publish a view to a BigQuery database that Mammoth manages for you, with access details to connect your own tools, progress messages while it runs, and clear errors when something goes wrong. Column names, including renamed ones, carry over cleanly, and the export contains only your data columns.
Add and remove batch columns directly from the Column Browser.
Workspace owners can turn access to alpha and beta features on or off for their workspace from the workspace settings.
Editing cells is smoother: add rows, see edited rows highlighted, keep your pipeline toggle setting, and read tooltips more easily.
Turn images into a PDF with the free Image to PDF tool, which also works better on mobile screens.
Import data from NetSuite into Mammoth.
Reports now opens from the vertical navigation bar into a workspace-wide reports page, and the explore section inside a report works again.
API tokens and external AI provider keys now live in their own API Keys section of Settings, separate from General.
Settings shows every workspace user with their role and the projects they are assigned to, lets you change a user's role per project, and invites new users from a redesigned invite window.
Add your own AI provider API key in Settings for generative AI features to use. If the key fails validation, runs out of quota or hits a rate limit, you see a clear message and the Gen AI rule cannot be applied until it is fixed.
Describe a filter or transformation condition in plain language and Mammoth builds the matching structured condition for you to review.
Upload or select files and choose whether to add them as a new batch, combine them with existing data, or replace it, with clear batch and column mapping options.
The browser tab icon shows whether the current view's pipeline is processing, has an error, or has finished, so you can follow progress from another tab.
Edit your profile and change your password from a dedicated profile and security window.
Leading, trailing and extra spaces are highlighted in the grid and in Explore cards, so stray whitespace is easy to spot.