Model Context Protocol (MCP) finally gives AI models a way to access the business data needed to make them really useful at work. CData MCP Servers have the depth and performance to make sure AI has access to all of the answers.
Try them now for free →
Create SSAS Tabular Models from Elasticsearch Data
How to build a SQL Server Analysis Service Tabular Model from Elasticsearch data using CData drivers.
SQL Server Analysis Services (SSAS) is an analytical data engine used in decision support and business analytics. It provides enterprise-grade semantic data models for business reports and client applications, such as Power BI, Excel, Reporting Services reports, and other data visualization tools. When paired with the CData ODBC Driver for Elasticsearch, you can create a tabular model from Elasticsearch data for deeper and faster data analysis.
Create a Connection to Elasticsearch Data
If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.
Set the Server and Port connection properties to connect. To authenticate, set the User and Password properties, PKI (public key infrastructure) properties, or both. To use PKI, set the SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword properties.
The data provider uses X-Pack Security for TLS/SSL and authentication. To connect over TLS/SSL, prefix the Server value with 'https://'. Note: TLS/SSL and client authentication must be enabled on X-Pack to use PKI.
Once the data provider is connected, X-Pack will then perform user authentication and grant role permissions based on the realms you have configured.
About Elasticsearch Data Integration
Accessing and integrating live data from Elasticsearch has never been easier with CData. Customers rely on CData connectivity to:
- Access both the SQL endpoints and REST endpoints, optimizing connectivity and offering more options when it comes to reading and writing Elasticsearch data.
- Connect to virtually every Elasticsearch instance starting with v2.2 and Open Source Elasticsearch subscriptions.
- Always receive a relevance score for the query results without explicitly requiring the SCORE() function, simplifying access from 3rd party tools and easily seeing how the query results rank in text relevance.
- Search through multiple indices, relying on Elasticsearch to manage and process the query and results instead of the client machine.
Users frequently integrate Elasticsearch data with analytics tools such as Crystal Reports, Power BI, and Excel, and leverage our tools to enable a single, federated access layer to all of their data sources, including Elasticsearch.
For more information on CData's Elasticsearch solutions, check out our Knowledge Base article: CData Elasticsearch Driver Features & Differentiators.
Getting Started
Creating a Data Source for Elasticsearch
Start by creating a new Analysis Services Tabular Project in Visual Studio. Next create a Data Source for Elasticsearch in the project.
- In the Tabular Model Explorer, right-click Data Sources and select "New Data Source"
- Select "ODBC" from the Other tab and click "Connect"
![]( "Selecting ODBC as the connector")
- Select the DSN you previously configured
![]( "Selecting the DSN (Salesforce is shown)")
- Choose "Default or Custom" as the authentication option and click "Connect"
![]( "Connecting to the DSN (Salesforce is shown)")
Add Tables & Relationships
After creating the data source you are ready to import tables and define the relationships between the tables.
- Right-click the new data source, click "Import New Tables" and select the tables to import
![]( "Importing the tables (Salesforce is shown)")
- After importing the tables, right-click "Relationships" and click "Create Relationships"
- Select table(s), and choose the foreign keys, cardinality, and filter direction
![]( "Configuring relationships between tables (Salesforce is shown)")
Create Measures
After importing the tables and defining the relationships, you are ready to create measures.
- Select the column in the table for which you wish to create a measure
- In the Extensions menu -> click "Columns" -> "AutoSum" and select your aggregation method
![]( "Creating measures (Salesforce is shown)")
Deploy the Model
Once you create measures, you are ready to deploy the model. Configure the target server and database by right-clicking the project found in the Solution Explorer and selecting "Properties." Configure the "Deployment Server" properties and click "OK."
After configuring the deployment server, open the "Build" menu and click "Deploy Solution." You now have a tabular model for Elasticsearch data in your SSAS instance, ready to be analyzed, reported, and viewed. Get started with a free, 30-day trial of the CData ODBC Driver for Elasticsearch.
Ready to get started?
Download a free trial of the Elasticsearch ODBC Driver to get started:
Download NowLearn more:
Elasticsearch ODBC Driver
The Elasticsearch ODBC Driver is a powerful tool that allows you to connect with live Elasticsearch document databases, directly from any applications that support ODBC connectivity.
Access Elasticsearch like you would a database - read, write, and update through a standard ODBC Driver interface.
