The data movement is in full swing. There are conferences (Strata +Hadoop World), bestselling books (Big Data, The Signal and the Noise, Lean Analytics), business articles (“Data Scientist: The Sexiest Job of the 21st Century”), and training courses (An Introduction to Machine Learning with Web Data, the Insight Data Science Fellows Program) on the value of data and how to be a data scientist. Unfortunately, there is little that discusses how companies that suc‐ cessfully use data actually do that work. Using data effectively is not just about which database you use or how many data scientists you have on staff, but rather it’s a complex interplay between the data you have, where it is stored and how people work with it, and what problems are considered worth solving.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.