Practical DataOps: Delivering Agile Data Science at Scale

Price: $18.33
(as of May 20,2023 23:51:34 UTC – Details)

DataOps is a new discipline for delivering Agile Data Science at scale. Inspired by practices at companies like Facebook, Uber, LinkedIn, Twitter, and eBay, this book introduces readers to DataOps and shows why organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into actionable intelligence and useful analytical data products.

This book provides an approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision-making. The goal is to optimize the data supply chain from raw data sources to the final data product, whether it’s a machine learning model or other data-driven output.

Practical DataOps helps 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.

In this book, readers will learn how to develop a data strategy for their 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, build trust in data via rigorous testing and effective data management, create a culture of learning and continuous improvement through monitoring deployments and measuring outcomes, and create cross-functional self-organizing teams focused on goals not reporting lines.

This book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production. It’s suitable for data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams.

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

Who This Book Is For:
Data professionals who want to dramatically increase the value their organization derives from data.