Databricks launches the Lakehouse platform to help manufacturers harness data and AI

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Databricks, a company specializing in data lake technology, announced Tuesday a new platform designed for the manufacturing industry. The lakehouse platform for manufacturing aims to bring together data and artificial intelligence (AI) for various analytics use cases such as predictive maintenance, quality control and supply chain optimization.

The platform is based on Databricks’ core data lakehouse platform, which leverages Delta Lake, Apache Spark, and MLFlow, open source projects that enable scalable data processing and machine learning (ML) workflows. The platform also integrates with Model Servicing, a service Databricks introduced last month to simplify the deployment and management of ML models in production.

“Big data is a huge challenge for the manufacturing industry as more companies deploy sensors to connect workers, buildings, machines and factories,” said Shiv Trisal, global manufacturing industry lead at Databricks, in an interview with VentureBeat.

“Furthermore,” he said, “this data is growing exponentially, with an estimated 200-500% increase over the next five years.” Lakehouse’s architecture enables organizations to leverage all their data in one place to implement AI at scale while reducing total cost of ownership (TCO), a huge priority for every IT leader today.”


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The Lakehouse production platform is available to customers worldwide today. Databricks said it has already been adopted by several leading manufacturers such as DuPont, Honeywell, Rolls-Royce and Shell.

Industrial analysis of turbocharging through customized solutions

Lakehouse for manufacturing offers integrated AI capabilities and pre-built solutions aimed at accelerating the delivery of value for manufacturers and their partners, according to Databricks. It also includes use case accelerators that provide guidance and best practices to address common and high-value industry challenges such as predictive maintenance, digital twins, supply chain optimization, demand forecasting, and real-time IoT analytics.

By unifying all data types, sources, frequencies and workloads on a single platform, Databricks says it enables organizations to unlock the full value of their existing investments and achieve AI at scale. The platform also enables secure data sharing and collaboration across the manufacturing ecosystem, enabling real-time insight for agile operations.

“With the ability to manage all types of data and connect all data analytics and AI workloads, teams across an organization can work together on a single platform, increasing impact and reducing the cost of their data assets, ultimately enabling data and AI to become central.” in every part of their operations,” Trisal said.

Fast, efficient data-driven decisions

Databricks also said its partner ecosystem and custom-built brickbuilder tools offer customers greater choice and flexibility, real-time insights and impact across the value chain at a lower TCO than complex legacy technologies. This unique offering, Databricks said, helps manufacturers make data-driven decisions quickly and efficiently.

The company cited actual examples of the platform it uses. For example, Shell has used it to improve its historical data analysis, enabling the energy giant to run more than 10,000 inventory simulations across all its facilities. Shell’s inventory forecasting models, which now work within hours rather than days, have significantly improved replenishment practices, resulting in significant annual savings, Databricks says.

Rolls-Royce has used its platform to optimize inventory planning, ensuring that parts are available when and where they are needed, minimizing the risk of engine unavailability and reducing spare parts lead times. This optimization has resulted in more efficient stock turns, further increasing the overall efficiency of the manufacturing process, Databricks said.

What’s next for Lakehouse for production?

Looking to the future of Lakehouse for manufacturing, Databricks has partnered with industry experts to provide customized data solutions to manufacturing customers. Through its brick-and-mortar solutions program, the company recognizes partners who have demonstrated an exceptional ability to offer differentiated lake industry and migration solutions combined with their knowledge and experience.

Partners such as Avanade, Celebal Technologies, DataSentics, Deloitte and Tredence offer comprehensive solutions that leverage the full potential of Databricks’ lakehouse platform and proven industry experience;

  • Avanade Smart Manufacturing enables manufacturers to unlock the full value of their data, optimize connected manufacturing facilities and assets, and achieve interoperability throughout the manufacturing cycle.
  • Celebal Technology’s igrate offers a set of tools that ease the migration of legacy on-premises/cloud environments to the lakehouse platform, effectively addressing scalability, performance and cost challenges.
  • DataSentics Quality Inspector enables manufacturers to streamline quality control using computer vision, automated product segmentation and tracking, and real-time detection of defects and foreign objects during production.
  • Deloitte’s intelligent migration factory offering automated management monthly reports, providing dynamic insights and supporting the digital organization powered by an enterprise data lake and advanced analytics.
  • In addition, Tredence’s predictive supply risk management offers end-to-end visibility into order flows and supplier performance, combining granular data to assess risk factors and AI-driven recommendations for all supply chain functions.

“Lakehouse for manufacturing will continue to evolve alongside the Databricks platform, and we will continue to add new solution accelerators and partners throughout the year,” explained Trisal. “Customers can explore our production solution accelerators (free for platform users) and get started with a free trial.”

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