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ACL Analytics, part of Diligent HighBond, is a powerful data analysis software primarily used for audit, risk management, and compliance. It enables professionals to examine and analyze large volumes of data to identify anomalies, trends, and potential risks or fraudulent activities.
CData Connect AI offers a dedicated cloud-to-cloud interface for Databricks, enabling analytics directly from live Databricks data within ACL Analytics, all without the need for data replication to a native database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to Databricks. This leverages server-side processing to swiftly deliver the requested Databricks data.
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 ACL Analytics is made possible through CData Connect AI. To work with Databricks data from ACL Analytics, we start by creating and configuring a Databricks connection in CData Connect AI.
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 ACL Analytics.
The steps below outline connecting to CData Connect AI from ACL Analytics to create a new Databricks data source. The CData Connect AI Virtual SQL Server allows you to establish a connection to your data from integration tools that support connections to SQL servers. The Virtual SQL Server mimics the behavior of a traditional SQL server, and it supports a range of query options.
ACL Analytics can now connect to live Databricks data directly through Connect AI, allowing you to analyze Databricks data without duplicating it.
To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your applications, try CData Connect AI today!
Learn more about CData Connect AI or sign up for free trial access:
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