Transform Datasets

Converting data to specific formats is challenging and time consuming. Therefore, Tellius has consolidated and simplified the transformation process.

In the transformation process, you can build your transformations, formulas and get your data ready before search. It is the process of cleaning and correcting your records from data.

Maintaining the quality of your data before performing any actions is highly critical for your explorations, discoveries and predictions. 

On the Dataset page, click the dataset that you want to load and prepare.

The Prepare page opens with the data loaded from the selected dataset.

The data prepare page looks is easy to read and looks like an Excel Sheet. The page allows you to preform all your transformations in the dataset with an interactive experience.

Data Transformation functionalities in Tellius includes:

  • Managing Columns where you can change the metadata of the columns.
  • Functions where you can add columns using Indicators (accommodate formulae) and Signatures (conditional statements)
  • Aggregate for standard, time series and pivot aggregations
  • Advance filters
  • Data Columns to change date category and synonyms
  • Relations between different datasets
  • Data Fusion for creating database from different datasets using unique identifier
  • Schedule for updating the dataset and VizPads

Mathematical functions are called as Indicators and logical expressions are called as Signatures. You can do all these function changes within the solution and you have an option to either save the new dataset in memory or database.

If you do not want to save the changes then you can revert the changes by clicking the Revert option. You can use these functions to visualize your data with certain calculations.

Transform Datasets – Python & SQL

Converting data to specific formats is challenging and time-consuming. Therefore, Tellius has consolidated and simplified the transformation process.

In the transformation process, you can build your transformations, formulas and get your data ready before a search. It is the process of cleaning and correcting your records from data.

Maintaining the quality of your data before performing any actions is highly critical for your explorations, discoveries, and predictions. 

Transformations in SQL and Python
  1. Click Data -> Prepare -> Data
  2. Click the dataset that you want to load and prepare.

The Prepare page opens with the data loaded from the selected dataset.

The data prepare page looks is easy to read and looks like an Excel Sheet. The page allows you to perform all your transformations in the dataset with an interactive experience.

  1.     Click the EDIT button.

  1.   Click the SQL / Python icon

  1. The Code Library and Column List are displayed in the left pane.
  2. Select the code from the list in the left pane.
  3. The code for transformation is available on the right side.
  4. In case you require help, then click Guidance and the extreme right pane displays the Sample Transformation code.

Data Transformation using SQL

Data Transformation using Python (Pyspark)

Data Transformation using Python (Pandas)

Did we help you?

Configure Datasets (Measure/Dimensions)

Create Business View

Contact