Keeping Up With Data — Week 17 Reading List

5 minutes for 5 hours’ worth of reading

Source: https://ex.pegg.io (including a video covering the cheat sheet)

rtifitial Intelligence is making more and more decisions in our lives, so naturally we need to make sure these systems are making the right decisions for the right reasons. Especially in the high-stakes decisions related to lives, health, or large amounts of money. That’s why explainable AI is important. The cheat sheet above is from Jay Alammar and it’s accompanied with a short video that provides a fantastic overview in just 15 minutes.

And if you have another 15 minutes, I recommend you reading the following three articles.

  • What is the Open Data Ecosystem and Why it’s Here To Stay: Open data ecosystem is characterised by openness, modularity and diversity. Many companies are realising that “going with a data stack with open standards and open-source technologies makes your approach to data much more future proof”. But why is it easier now? The article suggests four reasons: (1) rise of cloud-based data lakes; (2) open-source data formats; (3) ecosystem of cloud-based vendors; and (4) the right level of abstraction for users. Having started my career during the Hadoop and big data boom I can attest that — despite myriads of possibilities and creeping choice paralysis — it has never been easier to ‘sort out’ infrastructure quickly and focus on unlocking the economic potential of data. (Casber Wang @ Sapphire Ventures Perspectives)
  • Gartner Top 10 Data and Analytics Trends for 2021: From mainstream trends like responsible AI or composable data and analytics, to growing popularity of graph forms. I was pleased to see trend no. 7: data and analytics becoming a core business function. And despite following the data industry from the front row, I’m always intrigued to find new terms in Gartner’s reports — like ‘data fabric’, ‘XOps’ and ‘X Analytics’ this time. Is it me or them? (Gartner)
  • Business Intelligence Strategy: How to Develop and Document your BI Roadmap: BI — turning raw data into useful insight — is used in many companies. However, it is easy to get lost in the technicalities and focus too much on various graphs that nobody knows how and why to use. Having a BI strategy can help prevent this. Covering three elements of the BI strategy — vision, people and process, and tools and architecture — should set us up for success. But most of all, we should always keep the following question in mind: “How will BI help you achieve your business goals?” (AltexSoft Inc @ Medium)

And that’s it from me this week. Enjoy the weekend!

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