Snowflake enables every organisation to mobilise their data with Snowflake’s Data Cloud. Customers use the Data Cloud to unite siloed data, discover and securely share data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single data experience that spans multiple clouds and geographies. Thousands of customers across many industries use Snowflake Data Cloud to power their businesses.
Can you tell us more about Snowflake’s Data Cloud and how it enables organisations to mobilise their data?
Snowflake enables every organisation to mobilise their data with the Snowflake Data Cloud. Customers use the Data Cloud to unite siloed data, discover and securely share data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single data experience that spans multiple clouds and geographies. A unique group of technologies enable the Data Cloud: the near-unlimited scale and efficiency of a multi-cluster shared data architecture, the seamless interoperability of working with data across multiple public clouds as if they were one; baked-in security features that can’t be turned off; and modern data sharing, which allows virtually any number of organisations to share and receive live data with each other near- instantly and without having to move or copy data.
Customers use Snowflake’s platform to execute a number of critical workloads, including applications, collaboration, cybersecurity, data engineering, data lake, data science and machine learning (ML), data warehousing, and unistore.
Snowflake has a wide range of customers, including 573 of the Forbes Global 2000. What are some of the industries or types of companies that benefit most from Snowflake’s services?
Snowflake has customised its services for technology, retail & CPG, financial services, healthcare & life sciences, and advertising, media & entertainment verticals. Snowflake also recently launched an industry Data Cloud for the telecom sector back in February.
Notable customers include: ABB, Adobe, Age of Learning, Airbnb, Albertsons Companies, Anthem Inc., AT&T, Blackboard, BlackRock, Capital One, ConAgra Foods, Deliveroo, Doordash, Dropbox, Electronic Arts, Instacart, JetBlue, Kraft Heinz, Lionsgate, Logitech, McKesson, NBC Universal, Novartis, Office Depot, Okta, PDX, PepsiCo, Rent the Runway, Scania, University of Notre Dame, Western Union, Yamaha, and many more.
Snowflake is announcing something unique for the manufacturing industry at the Hannover Messe conference. Can you give us a sneak peek into what we can expect from this announcement?
As any manufacturer today can attest, the industry is undergoing significant transformation due to changes in our global economy and advancements in technology. In the wake of the pandemic, there is a real spotlight on improving supply chain performance and factory efficiencies.
Tackling these issues requires a convergence of data and that’s why Snowflake is announcing the Snowflake Manufacturing Data Cloud, which is our latest industry-specific Data Cloud.
How do Snowflake’s services help manufacturing companies address common data challenges, such as uniting siloed data or executing diverse analytic workloads?
As manufacturers look to improve supply chain performance and factory operations, they’re finding these efforts challenging because the data required to enable these efforts is siloed and difficult to access. We are helping manufacturers bring their data from the factory floor to the cloud where they have access to the scale and industry solutions they need.
The Snowflake Manufacturing Data Cloud is a global network that connects manufacturers to the data, applications, and services needed to enable industrial use cases at scale. With Snowflake, manufacturers can store and process huge volumes of near real-time data from enterprise systems, Industrial IoT, and connected products. This enables them to easily integrate vast amounts of siloed information technology (IT) and operational technology (OT) data, share data with customers and suppliers, establish a data foundation, and power smart manufacturing and supply chain initiatives. By collaborating with partners, suppliers, and customers in a secure and scalable way, manufacturers can drive greater visibility and agility across their entire value chain.
In your experience working with manufacturing companies, what are some of the biggest opportunities for leveraging data to drive business success in this industry?
The Snowflake Manufacturing Data Cloud gives manufacturers the data foundation they need to improve supply chain performance and power smart manufacturing. There are so many use cases that manufacturers can pursue once they’ve broken down data silos.
In the supply chain (outside the four walls of the factory), manufacturers can easily blend internal data with third-party industry insights from Snowflake Marketplace, including energy and raw material forecasts, near-real time supplier disruptions, and transportation forecasts to anticipate supply chain disruptions and mitigate impacts of adverse events.
When you focus on the factory performance, there is so much data generated during production on the factory floor that traditionally hasn’t been leveraged to make better production decisions. Data is often trapped in legacy equipment that traditionally has been difficult to access. With Snowflake’s Manufacturing Data Cloud, our partners are bringing to market an edge-driven solution that can connect to shop floor equipment, define a model asset, and stream that data into Snowflake where the data dynamically materialises for engineering analyses. Additionally, as smart manufacturing looks to augment traditional data with unstructured data (photographs or videos taken during the manufacturing process), they need a scalable platform and powerful machine learning to find insights that lead to performance and quality improvements.
Manufacturers can now use the Manufacturing Data Cloud to develop their own AI solutions or leverage proven solutions from Snowflake’s partners, solutions including predictive maintenance, cycle time analytics, measure yield and quality, and more. For instance, we have a solution with H2O.ai with video-based quality control and a solution from Dataiku that infers root cause of production issues and predicts quality of future production batches.
Snowflake offers a range of features, from collaboration tools to data science and machine learning capabilities. How do these features specifically benefit manufacturing companies?
The issues that manufacturers face in improving their supply chain and powering smart manufacturing initiatives are fundamentally data problems.
Historically, manufacturers have struggled to share data with suppliers and customers in near real-time. On the supply side, manufacturers are too often ‘surprised’ by supply shortages or late shipments, leading to expensive contingency plans or production delays. When fulfilling demand, manufacturers need reliable forecasts of future sales and visibility into product shipments so they can build the right products and ensure those products arrive at their customers at the right time. Collaboration with suppliers, customers, and other partners increases visibility throughout the supply chain with new data insights to business planning and operations management.
Or, in cases where manufacturers do have access to shopfloor (OT) data, they have been flooded with big data and have struggled to leverage it to improve the manufacturing process. These data sets are simply too big to analyse visually–machine learning is required to find the patterns to infer root causes of production issues and recommend corrective actions. Snowflake’s Snowpark enables manufacturers to run machine learning directly where the data lives in Snowflake.
Snowflake’s ability to support workloads like data sharing and machine learning are critical in helping manufacturers to build the data foundation that allows them to effectively improve supply chain performance, product quality and factory efficiency in today’s digital-industrial world.
As the Global Head of Manufacturing at Snowflake, what are your top priorities for helping manufacturing companies leverage data to drive innovation and growth?
Continuing to build out the Manufacturing Data Cloud ecosystem to support our customers’ needs is a top priority for Snowflake. We’re launching our Manufacturing Data Cloud with 50 partners that bring key, data-driven industrial use cases at scale, such as building a data foundation, improving supply chain performance, and powering smart manufacturing.
As the Manufacturing Data Cloud continues to grow, we will expand the partner ecosystem to provide critical, valued features and services that enable manufacturing customers to continue to find success on Snowflake.
Looking to the future, what trends do you see emerging in the manufacturing industry that will impact how companies approach data management and analytics?
The manufacturing industry as whole is very much in the midst of a transformation. At the height of the pandemic, manufacturing supply chains were in complete disarray with historic supply shortages and severe demand swings. When markets settled to a ‘new normal’, geo-political events, labour shortages and inflation continued to disrupt and challenge economics across the manufacturing value chain.
As manufacturers re-balance their global footprint, factories in higher labour cost regions are looking to advancements in technology, including big data and AI, to offset labour shortfalls, maximise factory throughput, and improve overall quality.
Data is going to be critical in all of these efforts. We’ll continue to see a demand and push to converge IT and OT data as manufacturers look to digitise their operations and add resiliency and efficiencies across their supply chain and factory operations.