Keeping Up With Data — Week 32 Reading List

Source: https://www.bearingpoint.com/en/our-success/insights/chief-data-officer-survey-2020/

Data literacy and cultural challenges are the biggest roadblocks for CDO’s success, according to a study by BearingPoint. In my experience it’s linked to the shift to complement a defensive data strategy (managing downside risks, security, gdpr) with offensive one (driving business outcomes and value). The later is not a technical discipline. Rather, it requires a broad variety of people to know when and how data can help, how to make data-driven decisions and how to turn business problems into analytical ones. Luckily, this topic is getting a lot of attention lately. Case in point is me being invited to speak at two events about data democratisation and a general ability to ‘speak data’.

Plenty of buzzing terms this week: data-driven organisations, self-service analytics and front-end of modern data stack.

  • The Bad Habits To Break Now: Data & Analytics Leaders: There are five problems preventing companies from being data-driven, according to the article. From not having a leader — a CDO; not having a data strategy aligned with the business strategy; ignoring the importance of data literacy; confusing everyone with tech jargon; all the way to responding with dashboards (not answers). I found the article slightly confusing in parts, but the full report (linked in the article) covers these topics exceptionally well. (Hyper Anna @ Geek Culture)
  • Why is self-serve still a problem? Many business users are calling for shortening the time to market for analyses needed for data-driven decisions. Self-service analytics should enable exactly that. However, the issue is that the self-service solution is often designed by analysts to ‘do what they do by non-analysts’. Why is that doomed to fail? Because analysts and non-analysts think differently. One are like scientists, the other like journalist. Analysts are diving into data, creating new hypotheses. Non-analysts typically want to extract main relevant metrics and overlay that with a story. An excellent, thought provoking article. (Benn Stancil)
  • The Changing Face of the Data Stack: Tristan Handy starts with a history lesson and data-analysis gaps of yesterday and today. The article quickly shifts to an expected ‘iPhone moment’ of data analysis. A moment, that will increase technological sophistication, but decrease end-user complexity. The term used is (again) self-service analytics. While traditional BI is thinking about data as a set of tables with rows and columns, it’s not how we naturally think. So, just like iPhone enabled people to physically point at the things, the future self-service analytics will need to design a UX around what’s more natural to us humans — a semantic approach to analytics. Let’s see what the front-end of the modern data stack will look like. The opportunities it will unlock are enormous for sure. (Mixpanel)

I noticed this week that I’ve picked up over 1,000 followers here on Medium! Nothing mind-boggling, but I’m very happy about this modest milestone. 🎉

Thanks to all of you reading these weekly blogs!

Thanks for reading!

Please feel free to share your thoughts or reading tips in the comments.

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Adam Votava

Adam Votava

2.5K Followers

Data scientist with corporate, consulting and start-up experience | avid cyclist | amateur pianist | DataDiligence.com