Databricks Inc. says it is launching Databricks One, a new AI-powered business intelligence tool, and is trying to bring the power of big data analytics to all business workers.
The company sells a cloud-based data warehouse platform that provides a collaborative environment for data engineering, data science, machine learning and analytics. It is especially popular with companies that need to harness the power of data for artificial intelligence. But up until now, it has been limited to engineers and data scientists with the necessary Python and structured query language skills.
Databricks One change introduces a simplified user interface that allows business workers of all kinds of things to access the features of the platform.
“Our mission at Databricks is to democratize data and AI,” said Ali Ghodsi, co-founder and CEO of Databricks. “Everyone at any skill level needs to use AI and use AI with data. With DataBricks's, we want to create an experience for technology users that is as unsurprising as the experience of technology users.”
The company announced Databricks today at its annual Data+AI Summit in San Francisco, saying it will be available in a private preview ahead of the private beta scheduled for the second half of the summer. Although it is currently free to use, the company plans to implement a metered price model based on token consumption due to AI models and usage time.
It does because the entire platform is driven by a generated AI model. The interface is very similar to ChatGPT and other generation AI assistants, allowing users to explain the type of data analysis they want to perform. Then, a large-scale language model performs the technical tasks that require it to complete the analysis. The company said it could take actions such as deploying AI agents to data pipelines and databases to perform very specific and detailed analysis.
Before DataBricks, users will need coding skills to be able to create these types of requests, but LLM eliminates that need. Generate the required SQL code itself and run it in the customer's data warehouse, abstracting complexity from users.
Once the analysis is complete, DataBricks will display the results via appropriate visualizations that appear directly in the interface. Users can then dig into these visualizations with “AI/BI Genie” and ask more detailed questions using natural language.
Use cases vary. For example, marketing experts may want to run some analyses to see how effective the latest campaigns are, while legal experts may want to see overlapping business contracts that may compete with each other. Salespeople can use it to gather all the information they need prior to meeting new leads.
In an interview with Fast Company, Ghodsi said that customers have been seeking business intelligence capabilities with these types of AI for years. They hope that regular business workers can perform the same deep analysis that engineers already do. However, many customers, particularly those in regulatory industries such as finance and healthcare, highlighted concerns about data security and the possibility that business workers might misinterpret findings from their data.
So it took Databricks a very long time to build one Databricks platform, Ghodsi said. The company has designed GuardRails for over two years to ensure the security of its customer data. These guardrails make sure that the most sensitive data is sandboxed, and users may be restricted to read-only access, he said.
Databricks One was launched for the company on a busy day, and it also debuted a new agent AI platform called Mosaic Agent Brick. It provides tools to automate the construction of AI agents and customize them using customer private data and synthetic information based on their archives.
Additionally, the company has announced a new serverless database called LakeBase, based on the popular open source relational database software PostgreSQL. It handles over 10,000 queries per second, resulting in power demanding AI workloads.
Today's update shows Databricks' decision to take advantage of the demand for AI applications and become the leading provider of the data that drives them. Investors are strong in supporting the company, with venture capitalists putting more than $14 billion in the war chest, increasing its value to an astounding $62 billion in December 2024.
Image: DataBricks
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