Beschreibung The Real Work of Data Science: Turning data into information, better decisions, and stronger organizations. 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
Wiley The Real Work of Data Science: Turning data into ~ The Real Work of Data Science: Turning data into information, better decisions, and stronger organizations Ron S. Kenett, Thomas C. Redman E-Book 978-1-119-57076-9 April 2019 $30.99 Paperback 978-1-119-57070-7 May 2019 $37.50 O-Book 978-1-119-57079-0 March 2019 Available on Wiley Online Library DESCRIPTION The essential guide for data scientists and for leaders who must get more from their .
The Real Work of Data Science: Turning data into ~ 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 Real Work of Data Science / Wiley Online Books ~ 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 real work of data science : turning data into ~ Get this from a library! The real work of data science : turning data into information, better decisions, and stronger organizations. [Ron Kenett; Thomas C Redman] -- "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.'
The Real Work of Data Science: Turning data into ~ The Real Work of Data Science: Turning data into information, better decisions, and stronger organizations - Kindle edition by Kenett, Ron S., Redman, Thomas C.. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading The Real Work of Data Science: Turning data into information, better decisions, and .
6 Ways to Transform Data into Real Information That Drives ~ When you understand the answer to that question, you will be in a better position to establish what data to collect and how to turn it into information you need to make decisions. 2. Use analytical tools. Use tools that help you analyze the information and data you have. Export the data from your system if necessary and load it into Excel.
What is Data Science? - UC Berkeley School of Information ~ Effective data scientists are able to identify relevant questions, collect data from a multitude of different data sources, organize the information, translate results into solutions, and communicate their findings in a way that positively affects business decisions. These skills are required in almost all industries, causing skilled data scientists to be increasingly valuable to companies.
Data-Driven Decision Making: 10 Simple Steps For Any Business ~ Data leads to insights; business owners and managers can turn those insights into decisions and actions that improve the business. This is the power of data. This is the power of data.
Big Data: 33 Brilliant And Free Data Sources Anyone Can Use ~ Data is ubiquitous â but sometimes it can be hard to see the forest for the trees, as it were. Many companies of various sizes believe they have to collect their own data to see benefits from .
10 Key Technologies that enable Big - Towards Data Science ~ Organizations still struggle to forge what would be consider a âdata-drivenâ culture. Of the executives who report starting such a project, only 40.2% report having success. Big transformations take time, and while the vast majority of firms aspire to being âdata-drivenâ, a much smaller percentage have realized this ambition. Cultural transformations seldom occur overnight. At this .
Towards Data Science ~ When you start your journey into learning and mastering the different aspects of data science, perhaps the first sub-field you come across is machine learning. Machine learning is the name used to describe a collection of computer algorithms that can learn and improve by gathering information while they are running. Any machine learning algorithm is built upon some data. Initially, the .
Achieving business impact with data / McKinsey ~ Translating data into business value. With a solid operating model in place, organizations can begin the process of turning data into value. A systematic approach maps a series of actions to the insights value chain described above. The first two action areasâdata collection and data refinementâcomprise the tech-heavy upstream activities .
Data Analytics Definition ~ Data analytics is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical .
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information system / Definition, Examples, & Facts ~ Information system, an integrated set of components for collecting, storing, and processing data and for providing information, knowledge, and digital products. Business firms and other organizations rely on information systems to carry out and manage their operations, interact with their customers and suppliers, and compete in the marketplace. Information systems are used to run .
POLICY MAKING IN THE REAL WORLD - The Institute for ~ IN THE REAL WORLD: Contents 2 Contents . About this report 3 Executiv e summary 4 1. Introduction: The Instituteâs Better Policy Making theme 15 2. Why look at policy making? 16 3. The drive to professionalise policy making 22 4. The gap between theory and practice 30 5. Process 38 6. Qualities 46 7. Structures 64 8. Politics 80 9. Improving policy making 100 10. Annex A: Methodology for .
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Data vs Information - Difference and Comparison / Diffen ~ While "information" is a mass or uncountable noun that takes a singular verb, "data" is technically a plural noun that deserves a plural verb (e.g., The data are ready. The singular form of "data" is datum â meaning "one fact" â a word which has mostly fallen out of common use but is still widely recognized by many style guides (e.g., The datum proves her point.
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What is Data Warehouse? Types, Definition & Example ~ The decision support database (Data Warehouse) is maintained separately from the organization's operational database. However, the data warehouse is not a product but an environment. It is an architectural construct of an information system which provides users with current and historical decision support information which is difficult to access or present in the traditional operational data .
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