Data Preparation FAQs
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A Business View is a logical data model. Consider a logical collection of tables that are linked by a common key (date, ID etc). When building a Business View, one has to build a dataset for modeling rather than creating a relational database.
The portion displayed under Data -> Business View will be downloaded as a single table.
A Business View is the logical data model used to drive Search, Vizpads, Insights, and Models. A Project is akin to a folder that contains a collection of Vizpads, Insights, and Models for a particular Business View. Once a project is shared with other users, all of its contents are shared automatically.
No, you can only add or remove columns in the existing dataset. A self-join of datasets is possible in some instances.
Column types can be measures or dimensions. Feature types can be categorical or continuous. Check out the documentation on and .
For this purpose, you need to use SQL or Python. Functions do not support reference to null values.
Only full replacement is available for local files. Incremental can be set up for databases.
The data is loaded into memory and also stored on disk.
This manipulation need to be done using SQL or Python.
Yes. SQL, Python, and advanced filter nodes can be modified in the middle of the data pipeline without having to modify the subsequent node. If a node is no longer needed, keep the node without a script.
It's recommended to remove the dollar sign, comma, and periods (for decimals) using find & replace via SQL or Python. Then, it needs to be converted into a number. Or, you could directly convert it into a number via SQL or Python.
Live datasets reside in the source, and they are not imported to Tellius. So for each query, the data needs to be fetched from the source, which could take a bit of time (when compared to non-live datasets). It can only be used for driving Search and Vizpads, but not Insights or ML models.
Redshift, Snowflake, Bigquery, Teradata work with Live query engines.
Yes. Data Pipeline contains the audit trail of all transformations done to a dataset. The pipeline is tied to a dataset. So, if a dataset is deleted, its pipeline will also be deleted.
It is absolutely possible to create formulas, nested queries, and complex joins, which can be used in search queries. New business KPIs and calculated metrics can also be created and used in Search and Vizpads.
Yes. Tellius supports live connections and loading in bulk. The speed depends on the size of the data, resources for the instance, and underlying data source.
In live connections, any SQL script, including a window function, will execute with each Search/Vizpad query run. To avoid this, consider creating a Materialized View on the source system and then load it to Tellius.
The SQL dialect for calculated columns is compatible with both Spark and the source system from which the data is loaded.
Enabling FQE on a live BV is not applicable. If toggled on, the system will not ingest the data into FQE; live connection status will be maintained. Please avoid using the FQE toggle for live BVs.
Measures are quantitative values (e.g., profit, sales, weight) for which you can apply aggregation. Dimensions are qualitative values (e.g., city, name) for which aggregation cannot be applied. Check out for more details.