Gain a practical introduction to DataOps, a new discipline for delivering data science at scale
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.
What You Will Learn
- Develop a data strategy for your organization to help it reach its long-term goals
- Recognize and eliminate barriers to delivering data to users at scale
- Work on the right things for the right stakeholders through agile collaboration
- Create trust in data via rigorous testing and effective data management
- Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes
- Create cross-functional self-organizing teams focused on goals not reporting lines
- Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products
About the Author
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.