Data Driven

by D.J. Patil, Hilary Mason

Succeeding with data isn’t just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt.

You’ll not only learn examples of how Google, LinkedIn, and Facebook use their data, but also how Walmart, UPS, and other organizations took advantage of this resource long before the advent of Big Data. No matter how you approach it, building a data culture is the key to success in the 21st century.

You’ll

Data scientist skills—and why every company needs a SpockHow the benefits of giving company-wide access to data outweigh the costsWhy data-driven organizations use the scientific method to explore and solve data problemsKey questions to help you develop a research-specific process for tackling important issuesWhat to consider when assembling your data teamDeveloping processes to keep your data team (and company) engagedChoosing technologies that are powerful, support teamwork, and easy to use and learn

Genres: Business, Technology, Nonfiction, Programming, Engineering, Technical, Software

34 pages, Kindle Edition

First published January 1, 2015

Reviews

[Maya Senen · Rating 3 out of 5]

If you are reading this book, chances are you are already at least data adjacent, if not a data science practitioner of sorts. The most valuable lesson here though, is not in tooling or technique. In fact, the key to effectively becoming data driven, is one’s ability to think critically and completely about data. Be able to understand and articulate the problem, come up with specific and clear questions which address it, collect your data, do your calculations or otherwise process, and have a system for validation. This recipe applies to more than data science.

[Ed Barton · Rating 4 out of 5]

Data Driven Principles

Data access, data democracy, open data driven discussions, dashboards, asking the right questions and using accessible tools and accurate sources of clean data are critical to true data driven organizations. As data becomes easier to gather and analyze, the approach to its use is critically important. This series is a good business oriented approach to data science. Good read.

[Daniel Aguilar · Rating 3 out of 5]

Sort of a manifesto claiming a culture change within companies to embrace a data-driven spirit at all levels. Didn't feel like getting truly new insights, but it's well articulated and useful as a reminder of some important points.

[Prateek · Rating 4 out of 5]

This short book communicates effectively what it means for an organization to be data driven and the role of data scientist. Author also has shared some insights in building a data culture into your organization. I enjoyed reading it. I feel there should've been more case studies about how data influenced the decisions big organizations made, and also some discussion on opportunities for people as well as startups in field of Data science. Overall it was a good read.

[Eren Avşaroğulları · Rating 4 out of 5]

Building data-driven culture is one of the main requirements for present organizations. It is important for monitoring the product development and runtime pipeline, improving product efficiency as end2end, detecting runtime anomalies fastly, defining the product roadmap and gaining a competitive advantage in the industry. However, it should not be forgotten that it also requires dedication and patience for success.

[Kevin Leung · Rating 4 out of 5]

Short but precise

This is pretty short paper, but it highlighted some key elements on how to implement data strategy in an organization. Key takeaway is that this is not a technology implementation but a business driven transformation in an organization for all levels.
Good introductory piece of work.

[Pablo · Rating 4 out of 5]

Good ideas and super easy reading

A good kick off for you and your company to take the advantages that Data can bring. It’s short and clear on the concepts that could help into bringing data to the whole company

[Vish Agashe · Rating 3 out of 5]

Quick and easy read

Covers basics of what it takes to democratize the data and build data driven culture across the org. Some good tips on how to break down organizational tendencies in weaponizing data for political purpose.

[Nirmalendu Mohapatra · Rating 3 out of 5]

Makes a nice reading experience. Explains the new data culture in simplest of words, citing concrete examples. was expecting it to be a little more elaborate treatment of the problem. Overall a fine piece.

[Daron Yondem · Rating 4 out of 5]

I love the emphasize on the culture shift instead of the toolset.

[Shyam Sundaram · Rating 5 out of 5]

Good Book must read

Good book for senior management to get a grasp of data relevance in current context. Many lessons can be taken to real world and implemented

[Kyi · Rating 5 out of 5]

Nice book

If you want to know why your boss is talking about “data driven decisions”, you should read it. That is my reason to read it.

[Ashish Om Gourav · Rating 5 out of 5]

Gets you the inside workings of a Data driven organisation, familiarises you with data tools & methodologies and above all, gives you a proper direction to be data driven professional.

[Dr. Tathagat Varma · Rating 2 out of 5]

I read it once again for some time, and found some interesting insights that I seemed to have missed out the last time! Orerall, a surprisingly good slim boo packed with some good insights.

[Akshat · Rating 3 out of 5]

High level discussion and needs a follow up read

Quick read for a high level discussion but gets you going and leaves you askimg for more. A good weekday read.

[Kathy Amores · Rating 4 out of 5]

Quick read on creating data driven cultures. Would be better if there had been more examples.

[Trajano Lima · Rating 5 out of 5]

Great introduction in the data science world. Recommended for entry level data scientists and managers who want to take their organizations to the next level in data driven performance.

[Tomas Moser · Rating 5 out of 5]

Simple yet very powerful thoughts

I found this surprisingly short essay very powerful. I work for a data analytics software vendor. All our customers should read it.

[rig_gles · Rating 2 out of 5]

A few good takeaways. Lots of well-trodden thoughts.

[Matt Mitchell · Rating 5 out of 5]

Easy Read with A LOT of Great Information to Chew On

I'm wrapping up a data science degree and really want to have an impact on the data culture where I work. This book is a short read with A LOT of GREAT information to take away and discuss with management. I'm even considering stepping out of my comfort zone and buying several copies to distribute to leadership in the hopes of sparking discussion.

[Reza K. · Rating 3 out of 5]

Although it was a really small book (less than 30 pages), it gave me a great insight about Data Science. Up to now I (as a data scientist, somehow) had only focused on the technical aspects of this world. In this book (actually in the second half) it was well demonstrated that the importance of taking data seriously in the business, is more than ever in the history. And also it's not enough for a company just to hire a few data scientists and the more important part is the culture that should be accepted.
Also, the first half of the book was a great introduction to the world of data.

[Jörn Dinkla · Rating 3 out of 5]

This book is nice, but too optimistic. Where are the dangers? What are the traps and pitfalls? What are the common mistakes? For internet companies where the data is generated by computers, data quality is not a big issue. But for other industries it is. And here erroneous data will lead to wrong conclusions. And without a solid background in statistics of how to interpret the data and how to avoid wrong conclusions, data science will be a desaster. See for example the book "the flaw of averages" by S. Savage.

[Craig Citro · Rating 4 out of 5]

if you're at all interested, it's short and FREE enough to be worth your time.

doesn't say anything earth-shattering, but it's the kind of thing i could imagine having a positive effect if handed to a manager or TL.

[Alex · Rating 2 out of 5]

Primarily a rehashing of what is starting to feel like boilerplate coverage of the business-integration side of data science -- not bad ideas, but not particularly novel.

[Vladimir · Rating 5 out of 5]

22 pages of awesomeness on how to build data pipeline in the company

[Tyer · Rating 4 out of 5]

concise and to-the-point, with some good use-cases and examples to support its claims and ideas

[Sean · Rating 4 out of 5]

High-level booklet by some leading data science thinkers. Brief, but with good content and big-picture thinking.

[Greg Belanger · Rating 5 out of 5]

clear concise brief actionable. If you're getting into big data or data driven decision making you need to read this.

[Paul C Powell Jr · Rating 5 out of 5]

Concise and well written

Very well written and concise. Many usable points included in this book. Can tell the authors have actual experience with business intelligence

[Mms Mamdouh Al Shamy · Rating 2 out of 5]

Didnt add much but contains mind opening ideas