Views¶

A View is a space where you work on your Dataset in Mammoth. This is where you explore your data and transform it to generate meaningful insights.

When you add a Dataset and open it, you automatically get the first View. You start analysis in the View with the original data of the Dataset. You can create as many Views to get varied perspectives on your Data.

Organizing your View¶

When you open a new View, you see your original data as a grid.

Fig. 106 View¶

Your View port may contain lot more columns that you need for your immediate analysis. You can hide such columns using the Column Browser.

Fig. 107 Hide columns in a View¶

If you want to give a more relevant or meaningful name to any column you can change the name from Column Browser or clicking on name in column header.

Fig. 108 Rename columns in a View¶

You can also change the order of displayed columns by dragging and dropping column headers or by changing the order in the Column Browser.

Fig. 109 Change order of the column in a View¶

Mammoth tries to give a reasonable default format to numeric and data columns. This may not be to your liking. You can change the format by clicking on column menu in header row of any column.

Fig. 110 Changing the format of a column¶

Exploring your data¶

You can explore the data in View to get a quick summary and detect patterns using an Explore Card. It can be created on a column for a quick visualization of data, show statistics like sum, average, standard deviation, etc. and reveal how they connect with other columns. For a detailed guide describing the full power of explore cards - Click here.

Fig. 111 Explore Cards¶

Cleaning and transforming¶

More information may be hidden in your data which can potentially be arrived through filtration, extraction, labelling, categorization, ranking or correlating with another piece of data. Mammoth provides you a whole catalogue of powerful data operations to do such activities. These actions or calculations on the data are done using Tasks in Mammoth. A Task adds a layer of change over the original Dataset and each new Task then adds a fresh layer over the previous state, and so on. For more information about Tasks, Click here.

Fig. 112 Tasks¶

A number of Tasks can be used on a Dataset to get desired results. These Tasks are stored as a list in a sequential order in the Pipeline. Once a Pipeline of Tasks is created, any new data automatically follows the same path.

Fig. 113 Pipeline¶

Joining with another View¶

You may want to correlate the data in your View with data elsewhere. This could be typically be organized as facts and dimensions. You can join your data in your current View with data in another View to build a consolidated picture of the information. For more information, check Join.

Fig. 114 Join¶

Building multiple perspectives¶

A Dataset can give you multiple information from different sets of calculations. Thus, you can add a new View and perform a different set of calculations on the raw data. You can also duplicate a View with an existing Pipeline to further build a different perspective.

Fig. 115 Creating multiple Views¶

Saving your work for later¶

When you work on a View, you create Pipeline, Explore Cards, Metrics etc. These assets can be saved for later use on another Dataset. It can be downloaded as a template. The template gets downloaded with the .mammoth extension.

Fig. 116 Saving a View as a template¶

A saved template can be applied to a View. The View on which you want to apply the template should have the same column types and names as the View whose template was saved.

Fig. 117 Applying template in a View¶

Note

Some Tasks like Publish to database and Publish as a Report are not saved in templates.

Publishing your View as a DB¶

A View can be published on Mammoth’s Database as a Table and can be accessed later as a Data Source. See how.

Publishing your View as a report¶

A View can be shared as a report with teammates. The report retains the state of Explore Cards and is interactive. See how.