Top 6 Best Data

of November 2024
1
Best ChoiceBest Choice
Becoming a Data Head: How to Think, Speak and Understand Data Science,
10
Exceptional
View on Amazon
2
Best ValueBest Value
The Data Detective: Ten Easy Rules to Make Sense of Statistics
9.9
Exceptional
View on Amazon
3
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable,
O'Reilly Media
O'Reilly Media
9.8
Exceptional
View on Amazon
4
Storytelling with Data: A Data Visualization Guide for Business Professionals
Wiley
Wiley
9.7
Exceptional
View on Amazon
5
Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG,
9.6
Exceptional
View on Amazon
6
Storytelling with Data: A Data Visualization Guide for Business Professionals
Audible
Audible
9.5
Excellent
View on Amazon
7
Opera Electronica
Imports
Imports
9.4
Excellent
View on Amazon
8
Invisible Women: Data Bias in a World Designed for Men
9.3
Excellent
View on Amazon
9
Data Science for Business: What You Need to Know about Data Mining and
9.2
Excellent
View on Amazon
10
Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
9.1
Excellent
View on Amazon

About Data

Click here to learn more about these products.

Becoming a Data Head: How to Think, Speak and Understand Data Science, Statistics and Machine Learning

The Data Detective: Ten Easy Rules to Make Sense of Statistics

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Storytelling with Data: A Data Visualization Guide for Business Professionals

Wiley. Language english. Book - storytelling with data a data visualization guide for business professionals.

Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street

Storytelling with Data: A Data Visualization Guide for Business Professionals

Opera Electronica

Shrink-wrapped.

Invisible Women: Data Bias in a World Designed for Men

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Data Pipelines Pocket Reference: Moving and Processing Data for Analytics

Disclaimer