Databricks, the lakehouse company, announced the Databricks Lakehouse for Manufacturing, the first open, enterprise-scale lakehouse platform tailored to manufacturers that unifies data and artificial intelligence and delivers record-breaking performance for any analytics use case.
Why is Databricks’ solution a game-changer?
The sheer volume of tools, systems and architectures it takes to effectively run a modern manufacturing environment makes secure data sharing and collaboration a challenge at scale, with over 70% of data projects stalling at the proof of concept (PoC) stage.
Databricks’ Lakehouse for Manufacturing breaks down these silos and is uniquely designed for manufacturers to access all of their data and make decisions in real-time. Databricks’ Lakehouse for Manufacturing has been adopted by industry-leading companies like Australian Rail Track Corporation (ARTC), DuPont, Honeywell, Rolls-Royce, Shell and Tata Steel.
Databricks’ newest industry-specific lakehouse goes beyond the limitations of traditional data warehouses by offering integrated AI capabilities and pre-built solutions that accelerate time to value for manufacturers and partners. These include solutions for predictive maintenance, digital twins, supply chain optimisation, demand forecasting, real-time IoT analytics and more.
A robust partner ecosystem and custom, partner-built Brickbuilder Solutions offer customers even greater choice in delivering real-time insights and impact across the entire value chain, and at a lower total cost of ownership (TCO) than complex legacy tech. It is built for a range of clients across the manufacturing, logistics, transportation, energy and utilities sectors.
What does the solution mean for Databricks?
“With rising costs, plateauing industrial productivity, and talent gaps, manufacturing companies are facing unprecedented operational challenges. At the same time, autonomy, connectivity and electrification are shaping a new approach of software-defined products that require a transformation of the business and operating model to remain competitive and innovative,” said Shiv Trisal, Global Industry Leader for Manufacturing at Databricks.
“In the next 5 years, the companies that outperform in this industry will be the ones that not only manage data but effectively operationalise value from data, analytics and AI at scale.”
“We are very excited to launch tailored accelerators that target the industry’s biggest pain points, and collaborate with leading partners to introduce Lakehouse for Manufacturing, enabling data teams to boost industrial productivity, gain nth-tier supply chain visibility and deliver smarter products and services at an accelerated pace,” Shiv Trisal further said.
What does Databricks’ solution bring to the sector?
With Databricks, firms can unlock their investments and achieve AI at scale by unifying all of their data – regardless of type, source, frequency or workload – on a single platform. The Lakehouse for Manufacturing has robust data governance and sharing built-in, and enables firms to deliver real-time insights for agile manufacturing and logistics, across the ecosystem.
Powerful industry solutions tailored for the lakehouse
The solution includes access to packaged use case accelerators designed to jumpstart the analytics process and offer a blueprint to help firms tackle critical, high-value industry challenges. Data solutions for Databricks’ Lakehouse for Manufacturing clients include:
- Digital Twins: Created from data derived from sensors, digital twins enable engineers to monitor and model systems in real-time. With digital twins, manufacturers can process real-world data in real-time and deliver insights to multiple downstream applications, including process optimisation modelling, risk assessments, condition monitoring, and optimised design.
- Predictive Maintenance: By leveraging predictive maintenance, manufacturers can ingest real-time industrial Internet of Things (IIoT) data from field devices and perform complex time-series processing to maximise uptime and minimise maintenance costs.
- Part-Level Forecasting: To avoid inventory stockouts, shorten lead times and maximise sales, manufacturers can perform demand forecasting at the part level rather than the aggregate level.
- Overall Equipment Effectiveness: By incrementally ingesting and processing data from sensor/IoT devices in a variety of formats, organisations can provide a consistent approach to KPI reporting across a global manufacturing network.
- Computer Vision: The development and implementation of computer vision applications enabled manufacturers to automate critical manufacturing processes, improving quality, reducing waste and rework costs, and optimising flow.
Databricks Partners deliver an ecosystem of purpose-built solutions
Clients across the manufacturing industry benefit from vetted data solutions from partners like Avanade, Celebal Technologies, DataSentics, Deloitte and Tredence, which are tailor-made to combine the power of Databricks’ Lakehouse Platform with proven industry expertise. Partner Brickbuilder Solutions and use cases for the Lakehouse for Manufacturing include:
- Avanade Intelligent Manufacturing: Avanade enables manufacturers to harness all types of data, drive interoperability and realise more value throughout the manufacturing lifecycle with a comprehensive look at connected production facilities and assets.
- Celebal Technologies Migrate to Databricks: A suite of proven tools from Celebal Technologies empowers organisations to easily migrate legacy on-premises/cloud environments to the Lakehouse Platform and addresses the key scalability, performance and cost challenges of legacy systems.
- DataSentics Quality Inspector: With DataSentics, manufacturers can leverage computer vision to automate quality control and easily detect defects, foreign objects and anomalies throughout the manufacturing process, from classification and detection to product segmentation and tracking.
- Deloitte Smart Factory: Deloitte offers automated Monthly Management Reporting to deliver dynamic insights and enable a digital organisation supported by an enterprise data lake and advanced analytics.
- Tredence Predictive Supply Risk Management: Tredence unifies siloed data and drives end-to-end visibility into order flows and supplier performance with a holistic view of the entire supply chain, coupled with real-time data to assess risk factors and prescriptive, AI-powered recommendations across all supply chain functions.
What are Databricks’ partners’ thoughts on the solution?
“Databricks Lakehouse empowers us to pioneer the digital transformation of Australia’s rail industry, and build a strong data foundation that has improved the resilience, availability and efficiency of our services to help deliver goods in a safe and efficient manner,” commented Andrew Simpson, National Applications Manager at Australia Rail Track Corporation.
“Shell has been undergoing a digital transformation as part of our ambition to deliver more and cleaner energy solutions. Databricks’ Lakehouse is central to the Shell.ai Platform and the ability to execute rapid queries on massive datasets. With the help of Databricks, Shell is better able to use its historic data set to run 10,000+ inventory simulations across all its parts and facilities,” said Dan Jeavons, VP Computational Science and Digital Innovation, Shell.
“Shell’s inventory prediction models now run in a few hours rather than days, significantly improving stocking practices and driving significant savings annually,” Jeavons further said.
Commenting on the product, Stuart Hughes, Chief Information and Digital Officer at Rolls-Royce Civil Aerospace, said, “We employed Databricks to optimise inventory planning using data and analytics, positioning parts where they need to be based on the insight we gain from our connected engines in real time and usage patterns we see in our service network.”
“This has helped us minimise risks to engine availability, reduce lead times for spare parts and drive more efficiency in stock turns – all of this enables us to deliver TotalCare, the aviation industry’s leading Power-by-the-Hour (PHB) maintenance program,” Stuart Hughes added.
“Avanade is delighted to partner with industry innovators like Databricks. As the leading Microsoft Partner for Manufacturing, we see manufacturers getting smarter about how they use digital tech – because they have to,” said Thomas Nall, Avanade Manufacturing Lead.
“Times are tough and innovations today must deliver more value more quickly across more of the organisation than ever before. The potential of lakehouse is truly exciting and will play a significant part in our Industry X and Smart Digital Manufacturing services,” said Thomas.
“Using the Lakehouse for Manufacturing, a business can utilise all data sources in their value chain so that the power of predictive AI/ML insights can be realised to identify inefficiencies in production, improve productivity, enhance quality control, and cut supply chain costs,” said Anthony Abbattista, Principal and Smart Factory Analytics Offering Leader at Deloitte.
“This data-driven manufacturing is where we see the industry going as companies seek to accelerate their Smart Factory transformations,” Anthony Abbattista further commented.
The Lakehouse for Manufacturing launch comes on the heels of the recent release of Databricks Model Serving, for fully managed production ML and a new, native integration with VS Code. For more information, visit Databricks’ Lakehouse for Manufacturing homepage.
