Richard Winter

Richard Winter, CEO & Principal Architect


WinterCorp

Business Results from Data at Enterprise Scale

Richard Winter, CEO and Principal Architect of WinterCorp is not an ordinary consultant. Armed with the combination of his deep technical expertise in data warehousing at enterprise scale -- and his experience creating and building small businesses—he is transforming the data warehouse strategies of his clients, thereby helping them deliver major business results.

"Insight into best practices & products – We deliver unmatched insight into the issues that impede performance or scale and the technologies that enable success."

“At enterprise scale, we often find that clients face risks and obstacles not apparent in more modest analytic data projects. Just as a Himalayan ascent entails challenges and dangers you don’t see hiking in New England, a large scale data warehouse implementation can present risks in performance, cost and schedule that you don’t encounter in most database projects. Outright project failures are common and can put large and critical business investments at risk. When the scale doubles in any dimension, it can take ten times as long or cost ten times as much to load, integrate, analyze or query data. Some people mistakenly believe that the cloud has eliminated such risks, but the opposite is true: implementing in the cloud at enterprise scale brings new, and frequently unfamiliar, problems in engineering and cost management. In addition, many data warehouse and analytic systems now involve streaming data and near real time analytics – this raises the technical difficulties and involves yet other new technologies and skills.

Our teams are able to identify the key technical problems in data warehousing at enterprise scale, whether with batch or real time analytics, and guide the client to architectures and solutions that lead to success. We are able to help our clients clarify critical business issues and then tease out the technical capabilities they need in a data warehouse platform or solution,” says Richard. “Our teams help clients project their strategic technical requirements forward to deal with the business demands of the coming years.” He then applies engineering analysis and measurement, as well as the skills and knowledge of his unusually deep technical teams, to help clients select and implement the database platforms and architectures that will get them where they want to go.

WinterCorp’s consulting practice is focused on the architecture and engineering of the large-scale data warehouse, the data lake and the analytic data ecosystem. WinterCorp teams do platform evaluations, benchmarks, proofs-of-concepts and strategic analytic projects, supported by engineering analysis and measurement. “That, and closely related custom consulting, is all we do. Twenty-five years of focus in this particular area, in which I and my colleagues have special skills, interests and methods, has given us an ability to deliver exceptionally good insights and recommendations on decisions of great significance to our clients,” he adds. The company also works hard to couple their strategic technical insights with business relevance and clarity.

According to Richard, many customers are now doing a strategic reassessment of their data warehouse direction – as they prepare for artificial intelligence, machine learning, cloud architectures and other advanced analytic data technologies -- and finding that WinterCorp can help them build the foundation they need for the data and analytic challenges of the 2020’s. Those challenges often involve continued rapid growth in scale and data variety, and increased focus on data from new sources, such as sensors (e.g., Internet of Things), cameras, 5g and other newer technologies. WinterCorp has uniquely valuable capabilities to help customers create such data architectures – on premise and in the cloud – and Winter says, “We understand these new technologies,but we have something more: unmatched expertise with the engineering issues at enterprise scale and complexity”

In one instance, a fast-growing pharma company with a blockbuster drug was accumulating a large volume of data on the use of their drug – known in the industry as “real world evidence”. The most critical component of this was reports from providers of so-called “adverse events”—if a patient takes a prescription drug and then becomes ill, the doctor reports this as an “adverse event”—and the data was overwhelming their existing analytical capabilities. They had to be able to analyze new adverse events quickly in order to be able to stay ahead of any new issues, and wanted a data platform that was suitable for all of their analytic data needs for their entire pharma R&D operation. WinterCorp assessed those needs; developed a data architecture; and, recommended a data platform—consisting of a data warehouse for the real-world evidence and other structured data; and, a Hadoop cluster for their genomic data and certain other data that would not have fit their data warehouse. Now they can analyze adverse events promptly to better protect their patients and maintain the desired relationship with their regulators.

In the past WinterCorp has done primarily custom benchmarks for clients engaged in a data warehouse evaluation. But, now that they have a cloud database lab, and are creating and running their own tests to measure the fundamental performance, cost and scalability of popular cloud data warehouse platforms.

“At WinterCorp, we have the expertise, experience and methods to help our clients meet the data challenges of the 2020’s and to implement the exciting business advances and transformations available to them via large scale, enterprise data management and analytics. And, we can help our clients manage the risks and avoid the obstacles that are causing so many large scale data warehouse and data lake projects to fail,” says Richard.


Company

WinterCorp

Management

Richard Winter , CEO & Principal Architect

Description

WinterCorp is an independent consulting firm specializing in the architecture and engineering of the modern analytic data ecosystem. We work primarily with the modern data warehouse and the data lake: cloud, on premise, hybrid.


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