Keeping Up With Data #74
5 minutes for 5 hours’ worth of reading
I came across a PwC report asking why there is so few CDOs in this ‘age of data’ earlier this week. One of their findings, which makes the low number of CDOs even stranger, is the increasing number of companies talking about data (in their annual reports). This is in line with data getting into the focus of the investors, as we can learn from Bain’s Global Private Equity Report 2022. Investors are asking about data and analytics and companies need to have the answers. And be sure that the focus of the investors is more on value-creation opportunities, rather than defensive data strategies.
Tips dominate this week’s reading list — be it for data engineers, CDOs, or collaboration between data roles.
- Collaboration between data engineers, data analysts and data scientists: Releasing analytics products and industrialising machine learning pipelines typically requires a collaboration between data engineers and data analysts or data scientists. Using modern data tools, the collaboration can be smooth, but it’s not always the case. Dailymotion’s data team is sharing their blueprints for the smooth collaboration. “It all boils down to this. Data engineers, data analysts, and data scientists should work in a collaborative manner to deliver new products efficiently. ” (Germain Tanguy @ Dailymotion)
- 3 Things All Data Engineers Should Learn from Big Data: DataExpert offers three tips for data engineers: 1) Compute is cheap compared to the time of Data Engineers; 2) SQL is code, and should be treated as such; and 3) Centralizing logic saves everyone time. The data engineers often strive for technical perfection. But that’s not always the best approach for the business. Even in data engineering we shouldn’t forget that (business) outcomes are more important than (data) outputs. “Saving money by increasing spend on compute, treating SQL as code, and centralizing logic are within the control of every Data Engineer out there.” (DataExpert @ Medium)
- The Role of the CDO in the Data Mesh World: Many CDO positions were established to create order in data — to centralise it, defend it, meet the regulatory and compliance requirements. The next evolution step is about getting economic value out of the data. Data mesh is a concept growing in popularity and therefore the question what is the role of the CDO in data mesh world is very pertinent. Nazia comes with four advices for the CDOs: 1) Be strategic, transformational thinkers driving the data agenda forward; 2) be facilitators rather than doers; 3) be champions of a data culture; and 4) actually understand data. In my opinion, these are generally applicable (independently of data mesh) if one wants to be a value-creating CDO, not a data control freak. (Nazia Shahrin @ TDS)
And that’s it for this week. Now it’s time to rest and enjoy the weekend.