- Paperback: 302 pages
- Publisher: O'Reilly Media; 1 edition (August 14, 2015)
- Language: English
- ISBN-10: 1491916915
- ISBN-13: 978-1491916919
- Product Dimensions: 6 x 0.6 x 9 inches
- Shipping Weight: 12.6 ounces (View shipping rates and policies)
- Average Customer Review: 8 customer reviews
- Amazon Best Sellers Rank: #550,815 in Books (See Top 100 in Books)
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Creating a Data-Driven Organization: Practical Advice from the Trenches 1st Edition
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About the Author
Carl Anderson is the Director of Data Science at Warby Parker in New York overseeing data engineering, data science, supporting the broader analystics org, and creating a data-driven organization. He has had a broad-ranging career, mostly in scientific computing, covering areas such as healthcare modeling, data compression, robotics, and agent based modeling. He holds a Ph.D. in mathematical biology from the University of Sheffield, UK.
Top customer reviews
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The book covers the basics of a data-driven organization from data collection, data quality, data analytics & metrics design to insights and leadership that drive actions. These form the basis for a data-driven culture in which the analytics value chain - the flow of data to final impact on business - is realized. The author thoroughly explains the analytics value chain through interviews and examples from data scientists and analytics leaders in various industries. It is filled with practical advice from the industries. You'll learn what works and what doesn't, and how to build a data culture that works for your organization.
The book is well written and organized into bite-size pieces that are easy to understand. If you want to develop a data-driven culture with the desire to turn data into actions quickly and efficiently, you will find this book helpful and worth your time.
Anderson talks a lot about an "analytics value chain" (data drives reports, to deeper drives and further analyses that get to a decision maker who changes strategies). Anderson emphasizes the culture of the organization is very important in being able to implement this type of work, and recognizes that the culture shift may take a while to occur. He also covers storytelling with data, a/b testing, an ideal data-driven culture set-up, and privacy, ethics and risk. There are good number of references, although the visualization, decision making, and a/b testing are a little light. Another topic that is missing from the book is results-based accountability, which can be helpful for groups drowning in metrics or data and can't choose (or don't know how to) because there are so many potential options.
It's pretty conversationally written, so it's a pleasant enough read, and is definitely worth the time for leaders (or people who are managing up) to think about ways to really drive forth data to action.
But all that data is useless unless it can be presented in forms that ordinary people – managers, leaders, administrators, politicians, bureaucrats – can comprehend and use in constructive ways.
That’s the big issue: most people aren’t naturally comfortable with analyzing data or even making sense of data provided iin tabular or columnar form.
So author Carl Anderson sets out to help the custodians of data within organizations think about data as the foundation of a culture, the culture of the data driven organization. He says “[the data driven] culture is the dominant aspect that sets expectations of how far data is democratized, how it is used and viewed across the organization, and the resources and training invested in using data as a strategic asset”. If your eyes glazed while reading that extremely important declaration, don’t worry because the author takes eh reader on a marvelously told and illustrated tour of what data is, how it is collected and how it can be visualized for more or less ordinary people.
Explaining data and its meaning gets a lot of well-deserved attention.
This book is intended for the people within an organization who gather and analyze and present data as comprehensible information. It is without doubt one the best treatments of data as an asset that I read in a very long time. Highly recommended.