Databricks, the Data and AI company and pioneer of the data lakehouse architecture, today announced the Databricks Lakehouse for Retail, the company’s first industry-specific data lakehouse for retailers and consumer goods (CG) customers. With Databricks’ Lakehouse for Retail, data teams are enabled with a centralised data and AI platform that is tailored to help solve the most critical data challenges that retailers, partners, and their suppliers are facing. Early adopters of Databricks’ Lakehouse for Retail include industry-leading customers and partners like Walgreens, Columbia, H&M Group, Reckitt, Restaurant Brands International, 84.51°(a subsidiary of Kroger Co.), Co-Op Food, Gousto, Acosta and more.
“Gousto is a rapidly growing direct-to-consumer brand that provides our customers with the ability to make weekly choices from over 60 recipes on our menu that change each week, many of which can be customised,“ said Robert Barham, Director of Data at Gousto. “Enabling that level of flexibility for consumers requires the coordination of a complex supply chain, from locally sourced ingredients to delivery partners who ensure the freshness of ingredients. The Retail Lakehouse enables Gousto to deliver on that promise to customers by enabling real-time visibility and collaboration across our supply chain and delivery.“
“Databricks has always innovated on behalf of our customers and the vision of lakehouse helps solve many of the challenges retail organisations have told us they’re facing,” said Ali Ghodsi, CEO and Co-Founder at Databricks. “This is an important milestone on our journey to help organisations 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.”
Databricks’ Lakehouse for Retail delivers an open, flexible data platform, data collaboration and sharing, and a collection of powerful tools and partners for the retail and consumer goods industries. Designed to jumpstart the analytics process, new Lakehouse for Retail Solution Accelerators offer a blueprint of data analytics and machine learning use cases and best practices to save weeks or months of development time for an organisation’s data engineers and data scientists. Popular solution accelerators for Databricks’ Lakehouse for Retail customers include:
- Real-time Streaming Data Ingestion: Power real-time decisions critical to winning in omnichannel retail with point-of-sale, mobile application, inventory and fulfilment data.
- Demand forecasting and time-series forecasting: Generate more accurate forecasts in less time with fine-grained demand forecasting to better predict demand for all items and stores.
- ML-powered recommendation engines: Specific recommendations models for every stage of the buyer journey – including neural network, collaborative filtering, content-based recommendations and more – enable retailers to create a more personalised customer experience.
- Customer Lifetime Value: Examine customer attrition, better predict behaviours of churn, and segment consumers by lifetime and value with a collection of customer analytics accelerators to help improve decisions on product development and personalized promotions.
Additionally, industry-leading Databricks partners like Deloitte and Tredence are driving lakehouse vision and value by delivering pre-built analytics solutions on the lakehouse platform that address real-time customer use cases. Tailor-made for the retail industry, featured partner solutions and platforms include
- Deloitte’s Trellis solution accelerator for the retail industry is one of many examples of how Deloitte and client partners are adopting the Databricks Lakehouse architecture construct and platform to deliver end-to-end data and AI/ML capabilities in a simple, holistic, and cost-effective way. Trellis provides capabilities that solve retail clients’ complex challenges around forecasting, replenishment, procurement, pricing, and promotion services. Deloitte has leveraged their deep industry and client expertise to build an integrated, secured, and multi-cloud ready “as-a-service” solution accelerator on top of Databricks’ Lakehouse platform that can be rapidly customized as appropriate based on client’s unique needs. Trellis has proven to be a game-changer for our joint clients as it allows them to focus on the critical shifts occurring both on the demand and supply side with the ability to assess recommendations, associated impact, and insights in real-time that result in significant improvement to both topline and bottom line numbers.
- Tredence will meet the explosive enterprise Data, AI & ML demand and deliver real-time transformative industry value for their business by delivering solutions for Lakehouse for Retail. The partnership first launched the On-Shelf Availability Solution (OSA) accelerator in August 2021, combining Databricks’ data processing capability and Tredence’s AI/ML expertise to enable Retail, CPG & Manufacturers to solve their trillion dollar out-of-stock challenge. Now with Lakehouse for Retail, Tredence and Databricks will jointly expand the portfolio of industry solutions to address other customer challenges and drive global scale together.
For more information, visit the Databricks for Retail and Consumer Goods homepage.
Databricks is the data and AI company. More than 5,000 organisations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems.
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