Self-Service BI with Analytic Models

Kyubit Analytic Model is a Self-Service BI analytic feature that could be quickly utilized using your data from CSV files and SQL query results, without creating OLAP cubes. With analytic models, end-user can create pivot tables, analytic reports and dashboards, using measures, dimensions, slicers and many features similar to OLAP analysis.

Kyubit 'Self-Service BI' Overview

In many situations you have a set of data you wish to analyze, but you probably will not engage creating OLAP cubes, which almost always requires knowledge, time, tools, etc. With Kyubit Self-Service BI, end-user can quickly import data from CSV files and SQL query results and configure Analytic Models, which behaves almost like you have OLAP cubes ready for analysis. Set of values from CSV files or query results is transformed to analytic models and Self-Service BI tools are ready for all Kyubit users to use them in analysis and dashboards, while values from the same data sources could be scheduled to update regularly with new values based on our preference.

Self-Service BI Tools

End-User Experience

After Kyubit Self-Service BI 'Analytic Model' is processed, authorized end-users can start analysis, that will look the same as if they are analyzing OLAP cube structures (very similar). End-users can create analysis, reports and create dashboards based on created analysis the same way they are doing with OLAP based analyses. Most features, like drill-down, drill-through, expanding, slicing, ordering, isolating are included in Analytic model analysis.

Read Step-by-Step tutorials on creating and using Kyubit Self-Service BI 'Analytic Models'...

How it Works

After you import your data from CSV files or SQL query Results and process 'Analytic Model', Kyubit creates special structures in Kyubit internal "KyubitAnalyticModels" database, that are suitable for quick analytic SQL queries. While analyzing data Kyubit is creating SQL queries to bring analytic results from Kyubit Analytic Models database. In other words, Kyubit is using SQL technology, combined with ColumnStore indexes and some smart caching to bring data analysis. Only technology prerequisite is MS SQL Server, which is prerequisite for the whole product anyway.


  • Main reason to use 'Analytic Model' is for regular user to quickly add set of data for analysis, dashboard usage, scheduled subscriptions and sharing with other users.
  • CSV data format should be friendly to all users while preparing data to be used. Any set of data could be exported from Excel to CSV file (semicolon (;) delimited).
  • Great usage of Date filters (if data contains date values) that are much friendlier to be used than OLAP ‘date’ structures. Quickly select absolute or relative date filter values in analysis, report or dashboard filters.


There are limitations to Kyubit Self-Service BI 'Analytic Model' usage, that should be known before using new Kyubit technology. Kyubit Analytic Model is not created in mind to replace more serious analytic engines, like OLAP technology, but to bring simple solution for smaller data sets that should be analyzed quickly with very little knowledge of data analysis and structures.

  • 'Analytic Model' will perform great with hundreds of thousands of rows of data, while we would not recommend to be used with millions of rows of data. This question greatly depend on the hardware on which SQL server is running, but millions of rows of data should be used with in-any-case more robust and scalable OLAP technology.
  • There are no limitations to number of category members (rows) in grid analysis and reports, while analytic grid and report can contain maximum of 128 series (columns) of values in analysis for each measure in analysis.
  • On category axis there could be multiple category levels expanding (drill-down) to explore data in more details, while series members cannot be expanded.