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Amazon QuickSight allows users to build interactive dashboards in the cloud. When paired with CData Connect AI, you get cloud-to-cloud access to Databricks data for visualizations, dashboards, and more. This article shows how to connect to Databricks in Connect AI and build dashboards in Amazon QuickSight with access to Databricks data.
CData Connect AI provides a pure cloud-to-cloud interface for Databricks, allowing you to allowing build visualizations from Databricks data in Amazon QuickSight. By importing your Databricks data into the Amazon QuickSight "Super-fast, Parallel, In-memory Calculation Engine" (SPICE), you can leverage the powerful data processing features of the Amazon ecosystem to build responsive dashboards. And with the ability to schedule refreshes of the data stored in SPICE, you control how up-to-date your dashboards are.
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Connectivity to Databricks from Amazon QuickSight is made possible through CData Connect AI. To work with Databricks data from Amazon QuickSight, we start by creating and configuring a Databricks connection.
To connect to a Databricks cluster, set the properties as described below.
Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.
With the connection configured and a PAT generated, you are ready to connect to Databricks data from Amazon QuickSight.
The steps below outline creating a new data set based on the connection to Databricks in Connect AI, importing the dataset into SPICE, and building a simple visualization from the data.
QuickSight users can schedule refreshes for data sets that are imported into SPICE, ensuring that data being analyzed is only as old as the most recent refresh.
At this point, you have a direct, cloud-to-cloud connection to Databricks data from your Amazon QuickSight dashboard. You can create new visualizations, build interactive dashboards, and more. For more information on gaining live access to data from more than 100 SaaS, Big Data, and NoSQL sources from cloud applications like Amazon QuickSight, refer to our Connect AI page.
Learn more about CData Connect AI or sign up for free trial access:
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