Keeping Up With Data — Week 24 Reading List

5 minutes for 5 hours’ worth of reading

Source: https://towardsdatascience.com/data-strategy-good-data-vs-bad-data-d40f85d7ba4e

he image above is taken from the article Data Strategy: Good Data vs. Bad Data. According to the article, Good Data is data integrated into a good data strategy aligned with the company strategy. The goal is to take better actions, which are made based on good decisions. For these you need good insights derived from good information. Having good data enables it to be transformed into information. Collecting good data is a result of an action. The process is not linear, it’s a never-ending continuous improvement loop.

Two topics this week — CDO and data observability and democratisation.

  • Chief data officers are useful. But their role is still murky. A CDO role is on the rise. But companies are still figuring out the details, so sharing best practices and lessons learnt is important. Equally important is to have an active discussion, especially when the participants don’t always agree. Great article packed with opinions from CDO thought leaders like Cindi Howson and Peter Jackson on questions like reporting lines, background of a successful CDO or what to do in the first hundred days. Assessing the data quality; data infrastructure; and, developing a data and analytics strategy are named as the first most important steps to have business impact. (Built In)
  • How TechStyle Used Agile Sprints to Roll Out a Modern Data Platform: We are reading about data platforms — supporting data needs across the organisation — a lot lately. But how does it look in real life when you decide to build one? One of the issues TechStyle wanted to solve with the data platform was getting new analysts up to speed with the data. We all know how data documentation typically looks like — obsolete and disconnected from the reality. But there seems to be a better way. It requires a modern tool like Atlan, an agile process and creating a culture of data documentation. Once you have that, you should be able to get more business value out of the data faster. (Prukalpa @ TDS)
  • Don’t Be “Data-Driven.” Be Analytics-Driven. While the discussion on whether an organisation should be data-driven, analytics-driven or insights-driven doesn’t get me started, I agree with the fact that asking business-level questions of analytics is superior to having data requests. So how do data analysts get from querying data for others to becoming thought partners? Three things are suggested: documenting (even) ad-hoc work; documenting data; and, setting up a central place for the documentation. I personally believe there is a bit more needed to break the circle. For starters, data should be democratised. I still see data teams in too many organisations guarding ‘their’ data from the rest of the organisation.(Robert Yi @ TDS)

The headaches are gone so I was able to spent a bit more time reading and learning. My quarantine is also officially over so I can go outside! I still feel very weak after what Covid has done to my body so no big cycling plans yet. But a nice walk with the family in the nature will do just fine.

Thanks for reading!

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

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Data scientist with corporate, consulting and start-up experience | avid cyclist | amateur pianist | CEO & co-founder at DataDiligence.com