Why is data governance so ineffective? The truth is, data governance programs aren't designed for the way we run our data teams. They aren't even designed for a modern organization at all. They were designed when reports still came through inter-office mail.

Businesses own more data than ever before, but it's of no value if you don't know how to use it. Data governance manages the people, processes, and strategy needed for deploying data projects to production. But doing it well is far from easy: Less than one fourth of business leaders say their organizations are data driven. In Designing Data Governance from the Ground Up, you'll build a cross-functional strategy to create roadmaps and stewardship for data-focused projects, embed data governance into your engineering practice, and put processes in place to monitor data after deployment.

By now, everyone knows that bad data extorts an enormous toll, adding huge (though often hidden) costs and making it more difficult to make good decisions and leverage advanced analyses. While the problems are pervasive and insidious, they are also solvable! As Tom Redman "the Data Doc" explains in Getting in Front on Data, the secret lies in getting the right people in the right roles to "get in front" of the management and social issues that lead to bad data in the first place.

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory but made accessible through numerous real-world examples - ready for immediate application to your next graph or presentation.

We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale.

Bill, an IT manager at Parts Unlimited, has been tasked with taking on a project critical to the future of the business, code named Phoenix Project. But the project is massively over budget and behind schedule. The CEO demands Bill must fix the mess in 90 days, or else Bill’s entire department will be outsourced. With the help of a prospective board member and his mysterious philosophy of the Three Ways, Bill starts to see that IT work has more in common with manufacturing plant work than he ever imagined.

Agile, Lean, and DevOps approaches are radical game changers, providing a fundamentally different way to think about how IT fits into the enterprise, how IT leaders lead, and how IT can harness technology to accomplish the objectives of the enterprise. But honest and open conversations are not taking place between management and Agile delivery teams.

How can we apply technology to drive business value? For years we've been told that the performance of software delivery teams doesn't matter - that it can't provide a competitive advantage to our companies. Through four years of groundbreaking research to include data collected from the State of DevOps reports conducted with Puppet, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance - and what drives it - using rigorous statistical methods.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

Data Driven Business Transformation is the practical guide to harnessing your data to compete and thrive in today's dynamic marketplace. This essential resource provides the insight, knowledge and focus you require to transform your business - unlocking the power of data and revealing its hidden value. Delivering step-by-step instructions to every stage of data transformation, this book enables you to strengthen your data literacy and make effective data-driven decisions.

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.

Team Topologies is a practical, step-by-step, adaptive model for organizational design and team interaction based on four fundamental team types and three team interaction patterns. It is a model that treats teams as the fundamental means of delivery, where team structures and communication pathways are able to evolve with technological and organizational maturity. In Team Topologies, IT consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help listeners choose and evolve the right team patterns for their organization.

Veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data.

A practical guide to the EU General Data Protection Regulation (GDPR). GDPR is no quick fix, nor a project with a timeline that ends on May 25, 2018. GDPR is an ongoing process that should lead organizations to achieve and maintain a high level of data-protection compliance and culture.

Product management has become a critical connective role for modern organizations, from small technology startups to global corporate enterprises. And yet the day-to-day work of product management remains largely misunderstood. In theory, product management is about building products that people love. The real-world practice of product management is often about difficult conversations, practical compromises, and hard-won incremental gains.

Why is data governance so ineffective? The truth is, data governance programs aren't designed for the way we run our data teams. They aren't even designed for a modern organization at all. They were designed when reports still came through inter-office mail.

What is data governance? And what are the principles and techniques you can leverage as a business or IT professional to make data governance successful within your organization? Data Governance will answer these questions and provide you with insights and approaches to improve the "data fitness" of your organization. Gain control of your data and assign responsible parties to ensure the data remains well-understood and protected, by applying the content within this book's six chapters: Chapter 1, Understanding Data Governance, looks at the broad definitions of data governance along with ...

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale.

By combining relentless optimism with a brutally honest reflection on common data strategy mistakes and what it takes to fix them, Tiankai provides CxOs to operational staff, data experts to business users, and students to experienced leaders, a refreshing take on turning advocates into active change-makers to create a sustainable data strategy. People are emotional, irrational, and impulsive, but they also play a crucial part in any data strategy work. Yet why is the people part of data strategy so difficult? Tiankai decodes the human aspects of data strategy into an actionable framework, ...