Data analytics is the science of analyzing raw data to make conclusions about that information. Data analytics is important because it helps businesses optimize their performances by Implementing it into their business models. It means that the companies can help reduce costs by identifying more efficient ways of doing business and help analyze customer trends and satisfaction, which can lead to new—and better—products and services. So, with respect to the skills required for this profession, we have listed the popular data analysis books in this article that will help you from getting started to making you career ready.
What does a Data Analyst do?
- Data analyst scrutinizes information using data analysis tools.
- Get meaningful results from the raw data.
- Typical duties include: using advanced computerized models to extract the data needed.
- Collect, process, and perform statistical analysis of data and translate it into layman’s terms.
- Identifying trends and making predictions, help companies make sense of how they work.
- Data analysts regulate, normalize, and calibrate data to extract that can be used to create charts, graphs, tables, and graphics to explain what the data mean across specific amounts of time or various departments.
What are top 3 skills for data analyst?
- A better understanding of artificial intelligence and predictive analytics as both of them are the hottest topics in the field of data science (Getting started with data science).
- Technical knowledge: Structured Query Language (SQL), Microsoft Excel, Statistics, R or Python programming, and Machine learning.
- Critical thinking: To help companies make better business decisions.
- Stay competitive: To get ahead in the field with excellent Data visualization and presentation skills.
How much is a data analyst paid?
- In the United States, the average salary for data analysts is about $62,453 (based on 18,600 salaries).
- The data analyst in India is getting paid in an average about ₹5,00,000 (based on 4,019 salaries).
- In Europe, the salary for a data analyst is nearly about €51,430 (based on 379 salaries submitted from Germany)
(Note: all the above information is obtained as of 2021 from glasdoor.com)
So, you could recognize from the above skills that being a Data analyst isn’t that easy. You need the appropriate resources for becoming a good data analyst. Probably books are the most conventional option for getting started. Later, you can continue to pursue a certificate course to enhance your skills.
There is more treasure in books than in all the pirate’s loot on Treasure Island.
– Walt Disney
But, choosing the right book for the same is where the real difficulty lies. Here are some best data analysis books which will succor your journey towards the Data Analyst.
I. Getting Started
II. Acquiring Technical Skills
- Python for Data Analysis
- Learning R: A Step-by-Step Function Guide to Data Analysis
- SQL in 10 Minutes, Sams Teach Yourself
- Naked Statistics: Stripping the Dread from the Data
- Master business modeling and analysis techniques with Microsoft Excel
- The Hundred-Page Machine Learning Book
III. Data visualization and Predictive analytics
I. Getting Started
If you’re just starting your adventure with Data Analytics, you should definitely try:
This book give the most gentle introduction to Data Analytics. You won’t find an easier book to read. Everything is laid out for beginners where you can learn about Data Analytics from scratch, I would say it is the best resource available among all other Data Analytics books.
With this data analysis book, you’ll learn:
- The case-lets from real-world stories at the beginning of every chapter, also you’ll get a running case study across the chapters as exercises.
- This data analysis book is designed to provide a student with the intuition behind this evolving area, along with a solid toolset of the major data mining techniques and platforms.
- An intuitively organized layout structured like a semester-long college course
- The book also includes a tutorial for R.
II. Acquiring Technical Skills
Following is the list of the most essential data analysis books required for acquiring the technical skills that any data analyst could need. After you acquire some experience with Python, R and SQL, then you can head over to Github to finish a bunch of projects. You are then ready to tackle new challenges.
You’ll get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. This book is really good to go deeper into data analysis, it can even work well for beginners but the learning curve might be steep. So, for for those who don’t have experience on python they can grab this book first on ‘Hands-on Python Crash course‘.
In this book on Python for data analysis, you’ll learn the latest versions of pandas, NumPy, IPython, and Jupiter in the process.
This hands-on guide gently teaches you how to use the essential R tools for analyzing data, including data types and programming concepts.
The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results.
Data Retrieval is one of the most basic skills which people forgo. A lot of business analytics professional does not know how to proceed.Data Retrieval is one of the most basic skills which people forgo. A lot of business analytics professional does not know how to proceed.
With the technical concepts explained in layman’s terms, the Naked Statistics by Charles Wheelan is considered as one of the best stastistics book for beginners. It is fun and easy to read when it comes to explaining the topics of descriptive, inferential statistics, probability, and regression.
Mastering excel serves as a great stepping stone towards your analytics career. This book is a hands-on, scenario-focused guide that shows you how to use the latest Excel tools to integrate data from multiple tables–and how to effectively build a relational data source inside an Excel workbook
6. The Hundred-Page Machine Learning Book
The Hundred-Page Machine Learning Book ofers a wealth of information to beginners without sacrificing quality information. It successfully retains the required amount of mathematical rigour without intimidating the newbies.
III. Data visualization and Predictive analytics
When it comes to data visualization, the tools at our disposal don’t make it any easier. Here are few important books that demonstrates how you can resonate your message to your audience through data visualization. Also, we have included predictive analytics in our list from a business perspective, predictive analytics is used to analyze current data and historical facts and to identify potential risks and opportunities for a company. Both, data visualization and predictive analytics are the most prominent business intelligence trends.
Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don’t make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you’ll learn how to:
- Understand the importance of context and audience
- Determine the appropriate type of graph for your situation
- Recognize and eliminate the clutter clouding your information
- Direct your audience’s attention to the most important parts of your data
- Think like a designer and utilize concepts of design in data visualization
- Leverage the power of storytelling to help your message resonate with your audience
Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it.
Practical Tableau is a perfect book for beginners to learn and become professional. In addition, author Ryan Sleeper is a qualified Tableau consultant and he has imparted his rich experience in the easiest manner possible.
This data analysis book is divided into 5 parts- Fundamentals, chart types, tips and tricks, framework, and storytelling. Each part has an in-depth explanation of concepts along with practical examples to go by. Practical Tableau answers questions like-
- Why are we creating this chart?
- How are we going to create this?
- What if you create this visualization
3. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
Eric Siegel’s data analysis book is an eye-opening read for anyone who wants to learn what predictive analytics is, and how predictive analytics can be deployed across a wide range of disciplines. It is easy to understand even for a layman, though there is some discussion of algorithms including linear regression or decision trees.
This book makes it clear that predictive analytics is not a sneaky procedure used by companies to sell more, but a significant leap in technology which, by predicting human behavior, can help combat financial risk, improve health care, reduce spam, toughen crime-fighting, and yes, boost sales.
To summarize, in this article on popular data analysis books, we have given information on about 10 relevant data analysis books that will help a Data analytics professional to improve his/her skills. However, if you are not able to find any of the above books through the given links then you should search them in the US store. Furthermore, if you want to explore your interests in business analytics, we recommend you check these courses.
Also, if you are interested in pursuing your career in Data Science, we have given here the list of Best Data Science Books to Get Started even we have listed courses here for comparison. I hope this article on data analysis books was fruitful. Comment your favorite data analytics books.