Keeping Up With Data #83

Source: https://www.pwc.co.uk/private-equity/assets/data-driven-value-creation-in-portfolio-companies.pdf

The image above comes from a PwC report titled Data-driven value creation in portfolio companies. Data is slowly but steadily finding its way into private equity. Not only to support the deal origination, but also to drive post-acquisition value creation. Two years ago I’ve been explaining to my now-business partner that data can help companies to make better decisions, improve efficiency of their operations, and create new revenue streams. To which she said “that’s exactly what PE is after” and DataDiligence was born. I strongly recommend reading the report not only to PE professionals, but to executives, and data leaders alike.

Apart from the PwC report, there are two more articles I think are worth your time.

  • Graduating from ETL Developer to Data Engineer: Why should ETL developers using drag-and-drop ETL tools upskill to code-based data engineering? Because it reduces vendor lock-in for their companies, presents them with the best abstraction there is for software (code), enables easier CI/CD and scalability. Plus the industry expects them to do that. I agree that solid coding skills teaching to express oneself in a sequence of commands to a computer is opening a world full of possibilities, without very little limitations. And that’s a skill that is very handy no matter if you end up using a code or a GUI for the next ETL you’re building. (Eric McCarty @ Google Cloud Community)
  • Don’t just run your data team like a product team, run it like a company that needs to scale: Treating data and analytics as a product is a very good strategy. It puts the consumer and their problems into the centre. But it might be even better to run a data team like a startup. Which is not only about building a great product, but also about marketing, sales, finance, operations, or people management. In my experience, the best data leaders were often very entrepreneurial. Because data — as a nascent industry — typically needs to create its own agenda, tightly linked to the overall business strategy. (Data Leader’s Survival Guide)

What a crazy week. I’ve managed to write over 90% of the previous 82 weekly blogs on Thursday night. Now it’s past 10pm, I’ve just managed to put the kids to bed amidst a violent thunderstorm, and I’m trying to finish the blog before midnight. Observing a deadline nobody gave me.

In case you missed the last week’s issue of Keeping up with data

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 | Interim CDO at DataDiligence.com

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Adam Votava

Adam Votava

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

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