Practical Dataops: Delivering Agile Data Science at Scale
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From the Back Cover
Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making.
Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles.
This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output.
You will:
Harvinder Atwal is a data professional with an extensive career using analytics to enhance customer experience and improve business performance. He is excited not just by algorithms, but also by the people, processes, and technology changes needed to deliver value from data. He enjoys the exchange of ideas, and has spoken at O'Reilly Strata Data Conference London, ODSC London, and Data Leaders Summit Barcelona.
Harvinder currently leads the Group Data function responsible for the entire data life cycle, including: data acquisition, data management, data governance, cloud and on-premise data platform management, data engineering, business intelligence, product analytics, and data science at Moneysupermarket Group. Previously, he led analytics teams at Dunnhumby, Lloyds Banking Group, and British Airways. His education includes an undergraduate degree from University College London and a master's degree in Operational Research from Birmingham University's School of Engineering.
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