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Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. Wondering which data science book to read?

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2021 Gift Giving Guide for Data Nerds

DataKitchen

Back by popular demand, we’ve updated our data nerd Gift Giving Guide to cap off 2021. We’ve kept some classics and added some new titles that are sure to put a smile on your data nerd’s face. Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, by Randy Bean.

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The Top 20 Data Visualization Books That Should Be On Your Bookshelf

datapine

Previously, we discussed the top 19 big data books you need to read, followed by our rundown of the world’s top business intelligence books as well as our list of the best SQL books for beginners and intermediates. Data visualization, or ‘data viz’ as it’s commonly known, is the graphic presentation of data.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

Does data excite, inspire, or even amaze you? Do you find computer science and its applications within the business world more than interesting? How do you get into this field? What does a profession in this field look like? BI is a varied and expansive field, with many different areas to focus on or specialize in.

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AI Product Management After Deployment

O'Reilly on Data

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed. I/O validation.

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10 DataOps Principles for Overcoming Data Engineer Burnout

DataKitchen

For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Add all these facts together, and it paints a picture that something is amiss in the data world. . Are they thriving or feeling the impact of failed projects?

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Cross-account data collaboration with Amazon DataZone and AWS analytical tools

AWS Big Data

Data sharing has become a crucial aspect of driving innovation, contributing to growth, and fostering collaboration across industries. According to this Gartner study , organizations promoting data sharing outperform their peers on most business value metrics. Data publishers : Users in producer AWS accounts.