No hype or jargon—become adept at asking good questions about the data and obtaining answers to add significant business value to analytics and artificial intelligence (AI).
We start by exploring fundamental topics, such as how data relates to your pain points, where to find the data, the skillsets involved in data work, and the two main data methodologies. Next, we cover high-level matters regarding data, expanding the scope of data initiatives and elaborating on the bigger picture of data work. Learn how to enrich your data assets, what professionals and technologies you’ll need to leverage, how data needs to evolve over time, the cost of data projects, and a process for evaluating when a data initiative is worth the investment. We conclude with a series of AI topics, from when AI is relevant in a data project to where you can find worthy AI professionals.
A well-thought semi-technical book with thought-provoking questions and answers on various data topics. Without getting too much into terminology and unnecessary details, the author covers all the key aspects of data work and makes the whole process seem feasible and even enticing to normal folk.
The book seems to be aimed at business people, but anyone can get something out of it, especially people who aren't interested in the technicalities of the subject. Although I've read it, I plan to keep it around so that I can reread it, when I get more involved in this kind of work for the company I work for.