I stumbled across this book while browsing and it’s title obviously jumped out to me as I'm always interested in anything to help quantify analysis or build data driven approaches to what I do.
I wasn't entirely sure what to expect but in summary, it's a really enjoyable, easy read on how to build data-driven teams and the culture to support them in an organisation.
The book starts off by establishing what the author really means by data-driven, touching on some of the fundamentals of data quality, collection and analysis.
After these initial chapters the book really got interesting for me as it starts to look at the organisational and cultural consideration of building a data-driven program.
The author first outlines the different skillets required for a rounded data-driven analysis team, covering skillets like business skills, programming, devops, stats, visualisation, machine learning and big data analysis. I really liked how the author shows these as complementary skills across the team, but highlights that your team don't need to be experts at all.
One really nice aspect is that the need for strong visualisation is hishlighted immediately, specifically in relation to it’s role in not just performing data analysis, but selling it the rest of the organisation. This is further later on in the book through a whole chapter on visualation, including how it can/should be used effectively, covering a lot of the ideas from Tufte, etc in a really nicely summarised form.
The author then moves on to describe the different types of data-analysis, how they are used and then works through some discussion around metrics and A/B testing as core examples of how data analysis can be applied to business contexts.
The next three chapters cover what I think to be the most important aspect of the whole book; the approach of decision making and it’s effect on data-driven approaches, the key comments of a data-driven culture within an organisation and the role of the C-suite in establishing this culture. These chapters outline many of the key cultural challenges to moving towards a more data-driven approach and are great reads for anyone who may be pushing for more data analysis within their organisation, but it struggling to get traction.
The book finishes out with a chapter on privacy, ethics and risk, which obviously as a security guy I love to see. I particularly like the “ick” factor approach that the author outlines to dealing with data analysis and privacy.
Overall I think this book is a great introduction to a lot of topics relating to data analysis and data driven decision making, and incorporates some really good lessons on organisational structure, culture, skillets and challenges with adopting data-driven approaches within organisations.
The author highlights thoughout that this book doesn’t touch on the tools or technology used for data analysis, or details on data analysis approaches, as these are covered in many other books, which are referenced at needed. So if you're looking for this type of material, definitely go elsewhere.
However, if you’re new to applying data-driven approaches to your field (IT, business or otherwise) or if you’re a manager or leader looking to understand how you can affect change within your organisation towards a data driven approach, I'd highly recommend this.
Links:
Amazon: http://www.amazon.com/Creating-Data-Driven-Organization-Carl-Anderson/dp/1491916915
Safari: https://www.safaribooksonline.com/library/view/creating-a-data-driven/9781491916902/
I wasn't entirely sure what to expect but in summary, it's a really enjoyable, easy read on how to build data-driven teams and the culture to support them in an organisation.
The book starts off by establishing what the author really means by data-driven, touching on some of the fundamentals of data quality, collection and analysis.
After these initial chapters the book really got interesting for me as it starts to look at the organisational and cultural consideration of building a data-driven program.
The author first outlines the different skillets required for a rounded data-driven analysis team, covering skillets like business skills, programming, devops, stats, visualisation, machine learning and big data analysis. I really liked how the author shows these as complementary skills across the team, but highlights that your team don't need to be experts at all.
One really nice aspect is that the need for strong visualisation is hishlighted immediately, specifically in relation to it’s role in not just performing data analysis, but selling it the rest of the organisation. This is further later on in the book through a whole chapter on visualation, including how it can/should be used effectively, covering a lot of the ideas from Tufte, etc in a really nicely summarised form.
The author then moves on to describe the different types of data-analysis, how they are used and then works through some discussion around metrics and A/B testing as core examples of how data analysis can be applied to business contexts.
The next three chapters cover what I think to be the most important aspect of the whole book; the approach of decision making and it’s effect on data-driven approaches, the key comments of a data-driven culture within an organisation and the role of the C-suite in establishing this culture. These chapters outline many of the key cultural challenges to moving towards a more data-driven approach and are great reads for anyone who may be pushing for more data analysis within their organisation, but it struggling to get traction.
The book finishes out with a chapter on privacy, ethics and risk, which obviously as a security guy I love to see. I particularly like the “ick” factor approach that the author outlines to dealing with data analysis and privacy.
Overall I think this book is a great introduction to a lot of topics relating to data analysis and data driven decision making, and incorporates some really good lessons on organisational structure, culture, skillets and challenges with adopting data-driven approaches within organisations.
The author highlights thoughout that this book doesn’t touch on the tools or technology used for data analysis, or details on data analysis approaches, as these are covered in many other books, which are referenced at needed. So if you're looking for this type of material, definitely go elsewhere.
However, if you’re new to applying data-driven approaches to your field (IT, business or otherwise) or if you’re a manager or leader looking to understand how you can affect change within your organisation towards a data driven approach, I'd highly recommend this.
Links:
Amazon: http://www.amazon.com/Creating-Data-Driven-Organization-Carl-Anderson/dp/1491916915
Safari: https://www.safaribooksonline.com/library/view/creating-a-data-driven/9781491916902/
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