Introduction to Data Models
  • 01 Aug 2022
  • 2 Minutes to read
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Introduction to Data Models

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A data model refers to the way data is imported, stored, and accessed to support data analysis, including creating reports, dashboards, and infusing analytics into your applications.

Sisense provides two types of data models:

  • An “ElastiCube” model
  • A “Live” model

A hybrid approach can also be used that combines the two, where some of the data comes from an ElastiCube and some comes from a live data source.

Watch this video about the different model types:

The ElastiCube Model

ElastiCubes are Sisense’s proprietary, high-performance analytical databases. They're specifically designed to withstand the extensive querying typically required for business intelligence applications. Import data from a variety of data sources into a Sisense ElastiCube, which becomes the database that supports your dashboard. Update your ElastiCube as the data in your sources change. Sisense also supports auto-updating, scaling, and source database modification without the need to re-build the entire data set.

With ElastiCubes, you connect to your data sources, design your schema, and import your data (build). Sisense imports all of the relevant data from your sources into the ElastiCube.

To learn more about ElastiCubes and how to model them, see:

The "Live" Model

Unlike ElastiCube models, Live models run queries directly against the data source. This provides you with near real-time data updates in your dashboard, meaning that in a lot of cases the queries are only as fast as the data source. The exception is when an identical query is performed within the cache timeout period (configurable in System ConfigurationQuery). In this case, the query will be served from cache instead of publishing another query to the warehouse or database.

To create dashboards built on live connections to a data source, you create Live models. These data models include connection and credential details to the data sources. After you have created your live model, you publish it.

Publishing the live model adds it to your list of data models from which you can select when working with dashboards.

To learn more about Live models, and how to create and publish them, see Managing Live Models.

Hybrid Models

The Hybrid model combines the best of ElastiCube and Live models. Hybrid models feed Live data into your dashboards while combining dashboards and analysis from historical data in the system. This means you can link your ElastiCubes to your Live data and work with them together without reducing performance.

When you create a hybrid model, you add both ElastiCube and Live models to a single dashboard. For instructions on how to do this, see Creating a Dashboard with Multiple Sources.

Choosing the Right Data Model for You

The following are general guidelines to consider when deciding which data model works best for you:

  • Data complexity and size: ElastiCubes tend to be faster when working with complex dashboards and large data sets
  • Processing abilities and duration
  • Synchronization requirements (real-time vs. periodic) - Live models are preferred for near real-time updates
  • Production database load considerations
  • Pricing
  • Data retention and database availability requirements

For further details, see Choosing a Data Strategy for Embedded Self-Service Business Intelligence.


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