Sisense Data Modeling Simplified 101

Ofem Eteng • Last Modified: December 29th, 2022

Sisense Data Modeling - Featured Image

Data models allow businesses to define how data is connected, processed, and stored within a system. Getting the right model in place enables them to surmount the diverse business requirements through an expression of the company’s metrics and measurements. Effective data models provide high-speed retrieval, ease of data access, data integrity, and data independence, they also provide more flexibility making room for possible extensibility in the future.

Sisense is a brilliant Business Intelligence solution that allows you to import data from several data sources and visualize it using stunning & informative dashboards. Using Sisense Data Modeling you can make an ElastiCube Model, Live Model, or even a hybrid of both. 

In this article, you will learn about Sisense Data Modeling. You will learn the concept of data models and then expand through the Sisense platform with various types of data models found in it. 

Table of Contents

What is Data Modeling?

A data model can be referred to as the logical interrelationships that exist between different data elements and the data flow; it also shows how data is being stored and retrieved. A data model can be a simplified diagram of a software system indicating the data elements contained in it by using text and symbols to represent the data and how the data flow works. 

Therefore, it is a visual representation of part or the whole of the information system highlighting the connections between data points and structures to illustrate the types of data used and stored within the system, the relationships that are shared amongst these data types, the way the data is grouped, and its formats and attributes.

The data model is very helpful when it comes to building or designing databases or reengineering an application through feedback obtained from stakeholders. It helps an organization put its data to effective use by meeting its business needs as the data model is built around your requirements following rules defined and incorporated into the design.

What is Sisense?

Sisense Data Modeling - Sisense Logo
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Sisense is a leading Business Intelligence (BI) software that is used in the collection of data from different sources where it is then unified into a single repository. It is easy to use with its simple interface and has a powerful visual reporting dashboard that can be used for smart analysis to explore, connect, analyze, and collaborate with team members to cater to your business needs.  

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What is Sisense Data Modeling?

Sisense Data Modeling is no different from the general idea of data modeling as previously explained. In Sisense, a data model simply refers to the way data is imported from various sources, stored in it, and how the data is being accessed for onward analysis, creation of reports, dashboards, and how such analytic insight can be infused into your applications for increased productivity.

You can classify Sisense Data Modeling into the following 3 models:

  • Sisense Data Modeling: The ElastiCube Model
  • Sisense Data Modeling: The Live Model
  • Sisense Data Modeling: Hybrid Models

Sisense Data Modeling: The ElastiCube Model

The ElastiCube model is Sisense’s high-performance analytic database designed for extensive querying. It has a super-fast data store and it is used for business intelligence applications.

With ElastiCube Sisense Data Modeling, you can import data from a variety of data sources, merge them, manipulate, and query the data into a single dataset. Data from Sisense Data Modeling ElastiCubes forms the database that supports your dashboard.

By bringing multiple sources of data together, ElastiCubes mashes up the data, creating fields where each value in one field has a corresponding value in another field and every field coming from every table can be analyzed in the context of any other. 

You can update ElastiCube as changes occur in your data source either manually or automatically, scale, modify the database source without the need to rebuild the entire dataset, and also connect to your data sources to design your schema.

Benefits of the ElastiCube Model

Performing Sisense Data Modeling using the ElastiCube Model has the following benefits:

  • Large amounts of data can be easily analyzed as it allows the querying of over hundreds of millions of rows of raw data returned in seconds with moderate hardware requirements. This is its main forte, the handling of large amounts of data. 
  • It carries out the analysis of large amounts of data without having to pre-aggregate and pre-calculate the data ahead of time and store it on the hard drive thereby reducing import/processing time and storage space.
  • It is very useful for data analysis when the data originates from multiple disparate sources.

For more on the Elasticubes data model, visit here.

Sisense Data Modeling: The Live Model

The Live data model runs queries directly against the data source producing near real-time data updates in the dashboard making the queries as fast as the data source except when an identical query is performed within the cache timeout period as the query will be served from the cache instead of publishing another query to the warehouse or database. 

With Live Sisense Data Modeling, you can refresh your dashboards manually or set them to refresh automatically every few seconds to provide near real-time updates, marking the major difference with ElastiCube models on how the load is managed in your dashboard.

In ElastiCube Sisense Data Modeling, the data is refreshed when the ElastiCube is built and queried and the data source does not define the Elasticubes but with the Live model, queries are run against the data source itself. However, the data source must be able to handle the potential load of multiple refreshes. 

After the Live model is created using connections and credential details to the data source, you can publish it where it will be added to a list of data models from which it can be selected when working with dashboards.

Limitations of the Live Model

The live model has the following limitations:

  • The Live model does not support certain analytical functions such as Mode and Standard Deviation.
  • It does not also support R formulas.
  • It does not allow the changing of Live data sources from dashboards.

For more on the Live model and the data types it supports such as BIGINT, BOOLEAN, FLOAT, DATE, INTEGER, etc, visit here.

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Sisense Data Modeling: Hybrid Models

The Hybrid model is a combination of the ElastiCube and Live models. This is done as dashboards support multiple data sources including ElastiCube and Live data models. The Hybrid models feed Live data into your dashboards while combining dashboards and analysis from historical data in the system, therefore, making it possible to link the ElastiCubes to your Live data. 

With this, you can build widgets on several data sources within a single dashboard and the widgets from the data sources will function independently of each other in the same dashboard. Sisense also supports filtering different widgets based on different data sources when the filter tables and columns are of the same name.

Working with ElastiCubes and Live Models

The ElastiCubes and Live models are managed from the Sisense Data page where you can view their current states. The Data page contains a list of created, shared, and recently worked on ElastiCubes and Live models. You can also display a list of all the models at once from the upper-right corner as shown in the figure below.

Sisense Data Modeling - Models
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Alternatively, ElastiCubes can be located by using the Search field on the upper-left side of the Data page and each tile contains the relevant information about the status of the ElastiCube and Live model ranging from its owner and who it is shared. When a tile is clicked on, the ElastiCube model can be managed by choosing Stop, Restart,  Cancel all queries, Create Dashboard, Schedule Build, etc.

To perform Sisense Data Modeling, follow these simple steps given below:

  • Step 1: On the data page, click on the +ElastiCube button or the +Live button present on the top right corner of your screen to create your desired data model.
Sisense Data Modeling - Model Buttons
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  • Step 2: For this article, the ElastiCube model is selected. Enter the name of your data model in the Add New ElastiCube Model dialog box and click on the Save button.
Sisense Data Modeling - Model name
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  • Step 3: You can also click on the sample data models provided by Sisense and customize them according to your business needs.
Sisense Data Modeling - Sample Models
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Data models are very helpful to enable you to organize the entire process of handling your data needs to improve the overall quality of your business. This article gave you a simplified outlook on Sisense Data Modeling. It stated that there are two basic types of the data model on Sisense, namely the ElastiCube and the Live model, but it also showed that a combination of the two types is possible, thereby yielding a Hybrid version. With this knowledge in place, it is believed that you will choose the right type of data model that suits your organization based on the complexity and size of your data, processing abilities and duration, data retention, and database availability requirements.

As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for a complete performance analysis of your business. However, it is a time-consuming and resource-intensive task to continuously monitor the Data Connectors. To achieve this efficiently, you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse or a destination of your choice. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.   

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Tell us about your experience of learning about Sisense Data Modeling! Share your thoughts with us in the comments section below.

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