Agile data management has become a necessity for organizations that need to maximize
the value of their data. Demand for data outstrips the capacity of IT organizations and data engineering teams to deliver. New data management practices that adapt the practices DevOps to support data operations (DataOps) are the key to agility in data management. The vision of data management agility is real and the value is clear. The enabling technologies exist today and data management practices are moving quickly toward the future of DataOps.

Most organizations today don’t really reap the benefits of data science. They can’t deliver data quickly enough; they can’t hire enough data engineers, and the analytic models they build are rarely operationalized. Data delivery is the bottleneck that prevents business managers and decision-makers from getting the insights and knowledge they really need. To keep up with the growing demand for data, we need a new approach to data pipelines and data delivery.

Readers will learn:

• DataOps is a recently emerged set of technologies and practices for data management in the age of AI and data science. Learn what is involved in DataOps and how to prepare for the future of data management.

• Modern data ecosystems are fraught with challenges ranging from data volume and variety to difficulties of operationalization. Understand the challenges and see how DataOps helps to overcome them.

• Getting to DataOps is a journey, not an event. Learn about the components of DataOps and the steps along the path to making them part of your data management reality.

• And more...

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