Over the past eight or nine years, applying DevOps practices to various areas of technology within business has grown in popularity and produced demonstrable results. These principles are particularly fruitful when applied to a data analytics environment. Bob Eilbacher explains how to implement a strong DevOps practice for data analysis, starting with the necessary cultural changes that must be made at the executive level and ending with an overview of potential DevOps toolchains. Bob also outlines why DevOps and disruption management go hand in hand.
Bob Eilbacher is the vice president of operations at Caserta. An experienced operations and client services professional with a successful track record of providing technology solutions and services that focus on uncovering analytics insights and driving efficiency across an enterprise, Bob works directly with clients to develop strategies and implement solutions that transform structured and unstructured data into analytics-driven business insights. He has a strong background in technology and a deep appreciation for finding the right solution. Previously, he held executive roles at Verint and Ness Technologies.
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