Get data into Mammoth: choose how to bring data in

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Compare the ways to create a dataset

Each method also handles versions differently. Upload and connectors keep a history of batches (each load is one batch). Paste, AI data and From URL start as a single snapshot. A webhook dataset can combine or replace its rows. See Batches: see and fix what arrived.

The best method can change as your needs grow. If you start with file uploads and later need automation, move to a connector or a webhook.

Upload a file from your computer

Drag and drop or browse for files. Use it for one-time analysis and files you already have.

• Handles: CSV, Excel (.xlsx, .xls, .xlsm), TSV, JSON, XML, archives, PDF and images.
• Size limit: 50 MB per upload. A folder counts as one upload.
• Several files: each file becomes its own dataset, whether you pick files one by one or upload a folder. A folder upload recreates the folder in the Data Library.

See Upload files.

Paste cells from a spreadsheet

Copy cells from Excel, Google Sheets or any spreadsheet, then paste them into Mammoth. It handles tab-separated or comma-separated text. The practical limit is your browser's memory. See Paste data.

Connect a database, app or drive

Connectors (also called Live Connections) reach databases, APIs, business applications and cloud drives. You add one from the Connectors launcher and pick your data in the connector workspace. Sources include SQL Server, PostgreSQL, MySQL, Snowflake, BigQuery, Salesforce and more.

Datasets from databases, apps and APIs can refresh on a schedule with a Dataset Refresh automation. Files from drives and file servers (Dropbox, Google Drive, Google Cloud Storage, SFTP, SharePoint, OneDrive, Email) are saved once. To bring in new files from them, use a File Collection automation. If your analysis must update on its own from a database or application, use a connector rather than file uploads.

See Connect a database or app. If a connection fails, see Troubleshooting.

Generate test data with AI

Describe the dataset you need in plain language, and AI creates realistic sample data. No source data is needed. You set the size (1 to 500 rows) or let the AI decide. Use it to test pipelines, prototype dashboards and train people. See Create data with AI or a sample file.

Import a file from a URL

Paste a file URL (a public link or a signed URL) and click Read file to preview it. For a CSV, TSV or TXT file you choose Keep it linked or Copy it once. A linked dataset fetches the file again when you click Get the latest, or on a Dataset Refresh automation. It takes the same file types as Upload. Only a CSV, TSV or TXT file can keep following its link; other files are added once, and a dataset made from a JSON file can't take new rows from its link.

Use it for public datasets, open data portals, API exports and shared cloud storage links. See Import from a URL.

Load a built-in sample

Pick one of the sample datasets that come with Mammoth, grouped into Business, Technology, Finance & Real Estate, and Healthcare & Entertainment. Use them to explore Mammoth, train people and run demos. See Create data with AI or a sample file.

Receive data from another system by webhook

Other systems push data to a unique webhook URL. Choose Webhook in the New Dataset dialog, or find it in the Connectors launcher under Push.

• Handles: JSON or form data sent in a POST request, or query parameters in a GET request, from apps, automation tools or custom event triggers.
• Timing: rows that arrive wait until they are added, on the schedule you pick under Add new rows (5 min, Hourly, Daily or By hand), or straight away when you click Add now.
• Data shape: with Turn JSON keys into columns on, each JSON key becomes a column. Otherwise each payload is stored as raw JSON.

See Receive data by webhook.

Choose a method: four questions

Is this one-time or recurring?

• One-time analysis: Upload or Paste.
• Recurring analysis: Connectors.
• Automated, event-driven loads: Webhooks.

How big is the data?

• Small tables: Paste from Clipboard.
• Files up to 50 MB: Upload.
• Larger data: Connectors.

Where is the data now?

• An Excel file you have open: Paste from Clipboard.
• A file on disk: Upload.
• A database or API: Connectors.
• A file URL: From URL.
• You don't have data yet: Generate with AI or Sample Files.
• An outside system that sends events: Webhooks.

Do you need real data?

• Testing or prototyping: Generate with AI.
• Real analysis: the method that fits your source.

Common situations and the method to use

What to do after you create a dataset

• Explore it. Use Explore Cards, the Metrics Panel, Filter Pills and the Data Quality Report. See Explore cards.
• Transform it. Build a pipeline to clean, combine and prepare your data with transformation functions or AI Prompt. See How the pipeline works.
• Share or export it. Export to Excel or CSV, create Live Links, send to destinations, or publish a dashboard. See Download data.
• Automate the refresh. For datasets from connectors or From URL, set up a scheduled refresh with email notifications and activity logging. See Refresh a dataset.
• Manage Views. Create, name, duplicate, reset and template Views, and control Auto-sync. See Views: create, rename and delete.