Databricks Launches Analytics Platform for Retailers

“The vision of lakehouse helps solve many of the challenges retail organizations have told us they’re facing,” said Ali Ghodsi, chief executive and co-founder of Databricks.

The San Francisco-based company sells services based on open-source Apache Spark, a real-time data-analytics technology that Mr. Ghodsi helped create. Apache Spark emerged from the University of California, Berkeley, in 2009.

Lakehouse for Retail consolidates a variety of information in a single digital repository. In the past, such repositories, often called data lakes, required users to make a copy of the data so that it could be structured and analyzed in a separate environment, the company said. The newer concept of the “lakehouse” allows users to analyze data in the repository itself, according to Databricks.

The goal of Lakehouse for Retail is to “help organizations operate in real time, deliver more accurate analysis and leverage all of their customer data to uncover valuable insights,” Mr. Ghodsi said. The platform also is designed to facilitate data-driven collaboration and sharing among businesses and partners in the retail industry, he said.

Retail data is proliferating quickly and the ability to capture and analyze that data has emerged as a major source of competitive advantage.

“If you look at where [retailers are] putting their money, it’s into new ways of collecting and processing information,” said David Swartz, equity analyst in the consumer sector research group at research firm Morningstar Inc.

Privately held Databricks says it has raised $3.5 billion to date. The company had $425 million revenue in fiscal-year 2021, ending Jan. 31, 2021, and in August said its annual recurring revenue was $600 million. Databricks said its current valuation is $38 billion.

Investors include Morgan Stanley Counterpoint Global, Andreessen Horowitz, funds and accounts managed by BlackRock Inc., Canada Pension Plan Investment Board (CPP Investments), Tiger Global Management and Coatue Management, according to the company.

Lakehouse for Retail builds on services that Databricks already offers customers including the U.S. operations of pharmacy giant Walgreens Boots Alliance Inc. Until now, retail customers have had to create software and tools to draw more industry-specific insight from Databricks. Lakehouse for Retail has retail-specific tools built into the platform itself, potentially expanding adoption in the sector, according to Mr. Ghodsi. Retailers are looking to make greater use of data in managing their inventory and supply chains, forecasting demand and personalizing marketing campaigns for customers, he said.

Walgreens, based in Deerfield, Ill., has been using Databricks for four years and gained access to Lakehouse for Retail six months ago, said Luigi Guadagno, vice president, pharmacy and healthcare platform technology at Walgreens.

Mr. Ghodsi said the specialized offering will be most useful to new Databricks customers, who will now be able to skip some of the steps of writing their own code to do things like inventory forecasting.

Still, prewritten code can’t act as a full-blown solution for any given retail enterprise, said Dan Vesset, group vice president, analytics and information management at market researcher International Data Corp. “It’s very hard to go 100% prebuilt, because of the unique requirements of subsegments within an industry and also the very unique requirements of an individual company,” Mr. Vesset said.

The idea of the lakehouse combines elements of data lakes—which store structured, semistructured and unstructured data—and the earlier idea of data warehouses, in which users conduct data analytics, according to Mr. Vesset. The lakehouse concept is still relatively new, and most enterprises continue to use traditional data warehouses, he said.

Databricks is also looking to launch more industry-specific lakehouse offerings targeting the healthcare, media and financial sectors, according to Mr. Ghodsi.

Mr. Guadagno of Walgreens said Databricks’ platform is attractive because it is scalable, it collects data in real time, and it can be used by different parties that rely on different tools, including people who write software, people who mine data and those who create reports. The benefit is that Walgreens doesn’t have to spend money moving data and translating it for various groups and all the data stays in the same place.

“We understand more, and we know more,” when it comes to dealing with patients, Mr. Guadagno said, and “Databricks is the engine behind it for us.”

Write to Isabelle Bousquette at [email protected]