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Turning data into information, better decisions, and stronger organizations
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Turning data into information, better decisions, and stronger organizations
478 kr
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The essential guide for data scientists and for leaders who must get more from their data science teams
The Economist boldly claims that data are now "the world''s most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource."
"These two authors are world-class experts on analytics, data management, and data quality; they''ve forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it."—Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy
"I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today''s issues, such as computational Big Data."—Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University
"Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University
Turning data into information, better decisions, and stronger organizations
478 kr
Läs direkt efter köp
The essential guide for data scientists and for leaders who must get more from their data science teams
The Economist boldly claims that data are now "the world''s most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource."
"These two authors are world-class experts on analytics, data management, and data quality; they''ve forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it."—Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy
"I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today''s issues, such as computational Big Data."—Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University
"Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University
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People and Data is an innovative exploration of the relationship between non-data professionals and data in an organization''s success, and why it is only when they work together that a business can unlock its full potential.This book explains how most companies are yet to take advantage of the value that data offers. Their structures and processes are unfit for data and their biggest mistake is that regular employees are not included in the data-driven effort. People and Data illustrates how to change this. It shows how and why improving data quality should be an organization''s first priority, how to tackle the tough organizational issues, such as departmental silos, that get in the way and how to upskill the whole workforce to get the best out of the organization''s data. It is a practical guide written by a global expert which explains how companies can put their data to work by building it into all aspects of the business including their structure, culture and workforce design. By infusing the whole organization with data in this way employees at any level can use insights from the data to improve business performance. Full of practical tips and advice, People and Data includes a Resource Centre featuring a curriculum for training employees, and eight tools that will help companies to leverage their data to meet their business goals and upskill their employees so that everyone can benefit from the power of data. With important takeaways and real-world examples from organizations including AT&T and Morgan Stanley, this book is essential reading for all those wanting to allow their people and data to reach their full potential but are not sure where to start.
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473 kr
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434 kr
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This book lays out the roles everyone, up and down the organization chart, can and must play to ensure that data is up to the demands of its use, in day-in, day-out work, decision-making, planning, and analytics.
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.
Everyone should see himself or herself in this book. We are all both data customers and data creators—after all, we use data created by others and create data used by others. And all of us must step up to these roles. As data customers, we must clarify our most important needs and communicate them to data creators. As data creators, we must strive to meet those needs by finding and eliminating the root causes of error.
Getting in Front on Data proposes new roles for data professionals as:
embedded data managers, in helping data customers and creators complete their work,DQ team leads, in connecting customers and creators, pulling the entire program together, and training people on their new roles,data maestros, in providing deep expertise on the really tough problems,chief data architects, in establishing common data definitions, andtechnologists, in increasing scale and decreasing unit cost.
Getting in Front on Data introduces a new role, the data provocateur, the motive force in attacking data quality properly! This book urges everyone to unleash their inner provocateur.
Finally, it crystallizes what senior leaders must do if their entire organizations are to enjoy the benefits of high-quality data!