Databricks targets retail vertical with its first industry-specific lakehouse
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San Francisco headquartered Databricks, a company that offers the capabilities of a data warehouse and data lake in a single “lakehouse” architecture, today announced its first industry-specific offering: Lakehouse for Retail.
Designed specifically for enterprises dealing in the retail and consumer goods vertical, Databricks says Lakehouse for Retail is a fully integrated platform that aims to solve the most critical challenges retailers and their partners face while trying to leverage surging data volumes for AI and analytics projects.
The solution, which is generally available as of today, has already seen early adoption from major retail enterprises including Walgreens, Columbia, H&M Group, Reckitt, Restaurant Brands International, 84.51°, Co-Op Food, Gousto, and Acosta.
“With hundreds of millions of prescriptions processed by Walgreens each year, Databricks’ Lakehouse for Retail allows us to unify all of this data and store it in one place for a full range of analytics and ML workloads,” said Luigi Guadagno, the VP of pharmacy and healthcare platform at Walgreens.
“By eliminating complex and costly legacy data silos, we’ve enabled cross-domain collaboration with an intelligent, unified data platform that gives us the flexibility to adapt, scale and better serve our customers and patients,” Guadagno added.
Lakehouse for Retail: What’s special?
As explained by Rob Saker, the retail and manufacturing lead at Databricks, the new retail lakehouse is based on open source and open standards, which allows retailers to share data — such as inventory levels, consumer data, sales data — with their partners/suppliers and collaborate with them on white label joint analytics, even if they are on a different cloud platform.
In addition to this, the offering comes with a suite of free solution accelerators that offer a blueprint of data analytics and machine learning use cases, as well as best practices to help enterprises get started and prototype AI projects in days and weeks. This, Databricks says, would cover multiple aspects, starting from streaming data ingestion for real-time decision-making (a must for winning omnichannel retail), demand and time-series forecasting, ML-powered recommendation engines for streamlining buyer journey, customer lifetime value analytics.
Moreover, enterprises signing up for Databricks’ Lakehouse for Retail platform will also get access to pre-built analytics solutions, built by the company’s partners and tailor-made to address real-time customer use cases. Data science and AI engineering company Tredence and Deloitte are among the players offering these solutions.
“With Databricks, Tredence expects to meet the explosive enterprise demand for AI/ML and help navigate complex data ecosystems, monetize enterprise data, improve time to insights, and maximize ROI. The partnership launched the On-Shelf Availability Solution (OSA) accelerator in August 2021, combining Databricks’ data processing capabilities and Tredence’s AI/ML expertise to help Retail, CPG & Manufacturers solve the trillion-dollar out-of-stock challenge,” a spokesperson from Tredence said.
“Now, with Lakehouse for Retail, we expect to jointly help enterprises effectively manage current growth barriers, future disruptions and drive global scale together,” they added.
The move strengthens Databricks’ position in the data industry. The company, which was valued at $38 billion following its last fund-raise in August 2021, goes against the likes of players such as Snowflake, Dremio, and Google BigQuery. Snowflake, in particular, has been a major rival for Databricks. The Montana-based company also offers a retail-specific offering with data sharing, although Databricks claims that their solution requires both parties to be on Snowflake, which it claims is not necessarily economically viable for both parties.
“Databricks has always innovated on behalf of our customers and the vision of lakehouse helps solve many of the challenges retail organizations have told us they’re facing,” Ali Ghodsi, CEO and co-founder of Databricks, said. “This is an important milestone on our journey to help organizations operate in real-time, deliver more accurate analysis, and leverage all of their customer data to uncover valuable insights. Lakehouse for Retail will empower data-driven collaboration and sharing across businesses and partners in the retail industry.”
Both Databricks and Snowflake have been taking on each other over the last few months and have even had a PR battle over performance claims. Databricks, which was founded in 2013 as a data lake provider, has expanded its wings to cover more and more data warehousing features and transform into a lakehouse. Meanwhile, Snowflake, a data warehouse provider, has been adding data lake-specific features with the expansion to AI/ML use-cases and unstructured data.
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