Databricks, a leading firm in artificial intelligence and data analytics, has announced the release of SQL Analytics, a new offering designed to streamline how data analysts execute their typical SQL queries on data lakes. This advancement allows businesses to seamlessly integrate their business intelligence applications, such as Tableau and Microsoft Power BI, with these data repositories.

SQL Analytics will be publicly available for preview starting November 18.

SQL Analytics represents a key development Databricks has been working towards, effectively realizing its “lake house” vision. It successfully merges the efficiency of a data warehouse, which stores data following transformation and cleansing, with the flexibility of a data lake, where data is preserved in its original state. Data within the data lake, a concept strongly advocated by Databricks co-founder and CEO Ali Ghodsi, is generally transformed only when accessed. This approach reduces costs but can present challenges for users.

“Our intention was to promote Unified Data Analytics, meaning the unification of data processing and analytics. However, this message didn’t gain traction,” Ghodsi explained. “The term ‘lake house,’ however, resonated with the industry.”

“Databricks has consistently provided capabilities in data science and machine learning, and with Spark, we offer robust data processing functionality, including [extract, transform, load] processes. SQL Analytics now empowers users to perform data warehousing tasks directly, specifically business intelligence and reporting, on the data lake.”

The core benefit lies in maintaining a single data copy, supporting both traditional data analysis applications, like business intelligence, and the data science workloads Databricks is already known for. This consolidation aims to make both types of applications more affordable and straightforward.

The service leverages an enhanced version of Databricks’ open-source Delta Lake storage layer to ensure rapid query completion. Furthermore, Delta Lake incorporates auto-scaling endpoints to maintain consistent query speeds, even during periods of high demand.

Data analysts can directly query these datasets using standard SQL, and the company has also developed a suite of connectors for various BI tools. These partners include Tableau, Qlik, Looker, and ThoughtSpot, alongside data ingestion partners such as Fivetran, Fishtown Analytics, Talend, and Matillion.

“Organizations today require a data strategy that prioritizes speed and adaptability,” stated Francois Ajenstat, chief product officer at Tableau. “With the increasing migration of data to the cloud, we’re witnessing growing interest in analyzing data directly within the data lake. SQL Analytics provides a new experience for customers, enabling them to extract insights from large data volumes with the necessary performance, reliability, and scalability.”

During a demonstration, Ghodsi showcased the new SQL Analytics workspace. It presents a simplified version of the standard, code-focused Databricks environment. As expected, SQL Analytics offers a more visually oriented experience, emphasizing visualizations rather than Python code.

While Databricks already serves some data analysts, this new service significantly expands the company’s potential market – a development that will likely support its plans for an initial public offering in the coming year.