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Data Models

Guides for doing Data Modeling

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Data accumulation is SiSense's method for building ElastiCube data without completely refreshing a table. This post describes the data accumulation functionality and gives a user the ability to custo...
03-02-2023
Source data that is flattened may require some or all of the columns of a source table to be transposed, in order to work seamlessly with SiSense’s functionality. This post will outline the cause and...
03-02-2023
Part of having a successful BI tool is having your data refreshed on the time you need it. To ensure your builds are working as expected, you can follow the steps provided below. Step 1 - Set...
03-02-2023
Introduction This script exports to CSV a complete list of the front-end dependencies for each ElastiCube. It provides information about whether an ElastiCube is used for data security, hierarchie...
03-02-2023
Introduction This article describes how to enable an alert* when there is a risk of Many-To-Many relationship (M2M) between two or more tables. * This implementation involve the use of Pulse and ...
03-02-2023
Sisense supports floating-point numbers (IEEE 754 standard) and allows you to perform an arithmetic calculation on these numbers. Floating-point numbers suffer from a loss of precision when represe...
03-02-2023
 Analytical Need There are cases where our data arrives in aggregate form, like in Google Analytics (where the lowest granularity level is daily). If we wish to free up clutter in the dashboa...
03-02-2023

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