Worthington Industries is North America’s premier value-added steel processor, providing a broad set of capabilities, products and services for a variety of markets including automotive, construction and agriculture. Worthington is the leading global supplier of pressure tanks and cylinders. The company manufactures an array of pressure cylinders products for industrial gas and cryogenic applications, transportation and alternative fuel storage, oil and gas equipment, and consumer brand retail products, including Bernzomatic, Coleman and Balloon Time.
Worthington Industries began its data lake journey in early 2018, as part of an ongoing initiative to increase quality and reduce costs. With many plants, many machines and many processes, finding even incremental opportunities for improvement or cost savings makes a big impact.
They started with an internal pilot in their datacenter, using the commercial Hortonworks software (since acquired by Cloudera). But while the IT team could see the potential, they found the stack complex and time-consuming to manage. To be successful, Worthington realized they needed a data lake that was easier to use.
A local referral led the Worthington IT team to evaluate Cazena’s SaaS Data Lake as a Service on AWS. Cazena is a complete, end-to-end data lake delivered as private SaaS. That meant no new staff or skills would be required to manage or support the data lake, which was very appealing to the team.
The SaaS model for the data lake is important for us. My team previously spent a large portion of our time on troubleshooting platform performance, wrestling with security and connectivity issues, and managing upgrades. It was difficult to find qualified resources to help.
We can now focus our time on the data engineering and analytics activities that will drive real value for our business."
Machines and systems on shop floors produce massive amounts of data. The various formats and distributed systems meant that data often wasn’t collected or reviewed until months later, and only then if there was a problem. The data collection process was silo’d and manual, which limited it’s usefulness for analytics. Worthington hoped that a data lake would change this, with three goals in mind:
Use data and analytics for manufacturing optimization, predictive maintenance, quality improvement and cost reduction
Efficiently collect and analyze data from a wide variety of sources (machines, manufacturing plants, etc.)
Stand up a modern enterprise data lake for advanced analytics with limited skills and IT resources
The SaaS Data Lake was able to move into production quickly, paving the way for the migration of their DIY on-premises data lake to a Cazena SaaS Data Lake on AWS. Worthington used Cazena’s built-in tools and hybrid gateways to connect their SaaS Data Lake on AWS with their datacenters.
Then, the team easily migrated their data, workloads and applications. Cazena’s software, automation and AWS expertise accelerated the migration. The SaaS data lake requires very little administration from Worthington. IT manages user assignment and data governance. No other IT, DevOps or security resources are required, because everything is fully managed and monitored by Cazena.
The Cazena SaaS Data Lake embeds many AWS product including Amazon Simple Storage Service (S3), Amazon Elastic Block Service (EBS), Amazon EC2, Amazon RDS and standard services such as Amazon VPC, AWS Transit Gateways, AWS Route 53, AWS Key Management Service and others.
|Cloudera's best-of-breed PaaS capabilities are embedded, optimized and regularly upgraded to the latest version (EDH, CDP, etc.)|
Worthington teams use a variety of analytics tools and processes with the data lake. Some connect with their existing Tableau visualization software, or use built-in advanced analytics interfaces to power new applications and projects. Others use cases are more specialized, such as internal tools that support specific quality processes.
Collecting and storing everything in a single, unified SaaS Data lake provides a comprehensive view across the enterprise and delivers on critical goals.
Improved quality, productivity and throughput, by using data and analytics to optimize machines and processes
Empowers organizational agility, with a unified data lake supporting a variety of maintenance, operations, quality, and business functions.
SaaS model enables IT to support innovation efficiently and cost-effectively, with no additional staff or skills required
“For us, it’s all about outcomes: improving quality, accelerating productivity and reducing costs. A SaaS data lake and managed service in the cloud has helps our team work more efficiently to drive faster business outcomes from our data.”
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Migration success stories and fast outcomes have underscored Cazena’s leadership in cloud data lakes on AWS. Cazena was named among the first Amazon Web Services (AWS) Partner Network (APN) Partners for the launch of the ISV Workload Migration Program (WMP) in 2019.
The program helps companies migrate Independent Software Vendor (“ISV”) workloads to AWS so they can achieve business goals faster and accelerate their cloud journey. The WMP program provides additional resources to APN Partners, including technical enablement, migration funding to offset costs, and go-to-market support, making it easier to migrate more enterprise workloads to AWS.
The AWS WMP Program and Cazena address an increasingly common challenge in enterprise cloud migrations. Whether it’s a new project or part of an ongoing transformation initiative, the migration of ISV workloads from on-premises data centers to AWS requires significant domain expertise in planning, execution, and optimization. Such migrations require an understanding of workload dependencies, application customizations, and AWS deployment options.
As the first SaaS Data Lake, Cazena offers specific software automation and expertise for data and analytics migrations, which often require additional DevOps skills for connecting to data sources and tools, and optimizing performance. As part of the program, Cazena worked with AWS to build a repeatable migration process playbook. Enterprises use Cazena’s SaaS Data Lake to migrate and run millions of analytics workloads on AWS, including data science, machine learning (ML) and artificial intelligence (AI), data warehousing, data engineering, and more.