Data Professionals At Work

Author: Malathi This is not a book that aims to teach any specific language or technique; instead it's a collection of interviews with "data professionals" who tell the author, with varying degrees of frankness, what their jobs are like.
Publisher: Apress
Pages: 376
ISBN: 978-1484239667
Print: 1484239660
Kindle: B07FY6HCZM
Audience: Developers interested in data science
Rating: 5
Reviewer: Kay Ewbank

This is not a book that aims to teach any specific language or technique; instead it's a collection of interviews with "data professionals" who tell the author, with varying degrees of frankness, what their jobs are like.

The interviewees come from a variety of backgrounds - administrators, developers, and people working on the analysis side, along with various CEOs, product managers, and even a 'database superhero'.

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Each interview starts with a couple of paragraphs saying who the person being interviewed is, where they work and have worked in the past, and what their qualifications are. This is then followed by around 10 pages of questions and answers, so the interviews are quite lengthy and go into some depth. The interviewer asks how the person being interviewed entered the profession, would they recommend it to other people, what a typical day looks like, what people in their role should follow as best practices. There are questions about favorite books, blogs, tools and techniques, along with some specific questions for that role. Each interview ends with a short section on 'key takeaways' that essentially summaries the things the interviewee said was important for the role, their favorite tools, books, and comments on training and conferences.

 

 

The list of interviewees is included on the book's cover even though due to its length I'm not repeating it here. Suffice it to say that I finished nearly all the interviews feeling it had been worth spending the time to read them. 

One point to note is that most of the people in the book have a Microsoft SQL Server background. I don't think this would be a reason to dismiss the book if you're working with some other database, but some of the suggested books and sources of information might be less useful.

Overall, though, this is a genuinely interesting book and I came away with some new insights into working with databases.


For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

 

 

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Deep Learning (No Starch Press)

Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
A book on deep learning wtihout an equation in sight?



Classic Computer Science Problems in Python

Author: David Kopec
Publisher: Manning
Date: March 2019
Pages: 224
ISBN: 978-1617295980
Print: 1617295981
Kindle: ‎ ‎ B09782BT4Q
Level: Intermediate
Audience: Python developers
Category: Python
Rating: 4
Reviewer: Mike James
Classic algorithms in Python - the world's favourite language.


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Last Updated ( Saturday, 02 November 2019 )