Table of Contents
Today we’re looking at the best big data analytics books of this year.
What is big data analytics?
Big data analytics is the process of looking at, or analyzing, large sets of data. It uncovers hidden patterns, correlations and other insights.
This leads to making better business decisions and more efficient operations.
🧠 Did you know? According to techjury, over 97% of organizations are investing in big data and artificial intelligence.
What does a big data analyst do?
A big data analyst does the following to data:
✅ identifies
✅ collects
✅ visualizes
✅ communicates
So in addition to conducting research, a big data analyst mines data for information and presents their findings.
And how can I become a big data analyst?
We’ve found some of the best big data analytics textbooks we think can help you get started on your journey today.
This post contains affiliate links. I may receive compensation if you buy something. Read my disclosure for more details.
TLDR: Big Data Analytics Books
🔥 Best Overall 🔥
Creating Value with Big Data Analytics
💥 Best for Newbies 💥
Data Science and Big Data Analytics
💸 Best Value 💸
Designing Data-Intensive Applications
Best Big Data Analytics Books This Year
Now let’s take a look at the best big data analytics books.
1. Creating Value with Big Data Analytics
↘️ Ideal for: students, data analysts, customer relations managers
↘️ Topics covered: leveraging big data analytics, creating value, data integration
Don’t let the boring cover fool you. This book is jam-packed with big data analytics nuggets.
➡️ Creating Value with Big Data Analytics by Peter Verhoef, Edwin Kooge and Natasha Walk is a roadmap to deal with the size and complexity of data.
You’ll start by observing challenges of big data. Then you’ll move onto the process of creating value using big data analytics.
After that, you’ll explore topics such as:
✅ data integration
✅ customer privacy and data security
✅ creating impact with visualization
And much more.
💡 Data integration combines data from different sources into a unified view.
2. Data Science and Big Data Analytics
↘️ Ideal for: aspiring data scientists
↘️ Topics covered: practical applications, analytic techniques and tools
Unlike Creating Value with Big Data Analytics, you’ll start by examining methods and tools used by data scientists such as MapReduce and Hadoop. Then using R programming, you’ll review basic data analytic methods.
💡 MapReduce is a programming pattern that accesses big data in the Hadoop File System (HDFS).
➡️ Data Science and Big Data Analytics by EMC Education Services is one of the best big data analytics books for beginners.
You’ll also observe how to approach data analytics problems by deploying a structured lifecycle.
Finally, you’ll discover advanced analytical theory and methods such as:
✅ clustering
✅ classification
✅ regression
And beyond.
What big data analysts are saying about Data Science and Big Data Analytics:
One of the best entry level books on big data analytics.
– LIU Bin
3. Machine Intelligence and Big Data Analytics for Cybersecurity Applications
↘️ Ideal for: students, researchers, engineers
↘️ Topics covered: machine intelligence, big data analytics, cybersecurity
The goal of this book is to bridge the gap between machine intelligence, big data and cybersecurity. You won’t find any other book like it on our list.
💡 Machine intelligence is the result of machines that are programmed with some aspects of human intelligence. Using learning and problem solving, a machine can solve complex problems.
➡️ Machine Intelligence and Big Data Analytics for Cybersecurity Applications is one of the best big data analytics books for cybersecurity.
Covering the latest advances in big data analytics, you’ll learn methods for:
✅ identifying cyber attacks early on
✅ cybersecurity intrusion detection
✅ malware analysis
And more.
4. SQL for Data Analytics
↘️ Ideal for: database and backend engineers, data scientists, business analysts
↘️ Topics covered: data types, preparing data, spotting patterns
You won’t find any other book on our list that gets as in-depth with SQL.
➡️ SQL for Data Analytics is one of the best big data analytics books for students with some SQL experience.
You’ll learn how to prepare data for analysis by using SQL queries and subqueries. You’ll also explore analyzing special data types with SQL.
Moving beyond the basics of SQL, you’ll discover how to spot patterns. Finally, you’ll become experienced working with different types of data:
✅ time-series
✅ text
✅ geospacial
And beyond.
5. Big Data Analytics for Internet of Things
↘️ Ideal for: aspiring data scientists
↘️ Topics covered: data analytics tools, privacy, security
Big Data Analytics for Internet of Things delivers an overview of data analytics in the Internet of Things (IoT) including:
✅ computing platforms
✅ big data analytics tools
✅ data compression and storage
✅ privacy and security
And much more.
💡 The Internet of Things is a network of physical objects that are connected with sensors, software and other technologies.
Using various big data concepts, you’ll discover ways to extract valuable insights. In addition, you’ll learn to make the best data extraction decisions with different techniques.
Big Data Analytics for Internet of Things is the only book on our list with a strong focus on IoT.
6. Big Data Analytics with R
↘️ Ideal for: aspiring data scientists
↘️ Topics covered: R programming, big data tools
Big Data Analytics with R is for aspiring data scientists.
➡️ Big Data Analytics with R is one of the best big data analytics books to learn R programming.
Unlike other books on our list, you’ll start by learning R fundamentals. Then you’ll explore R functions for data management. After that you’ll discover cloud-based big data solutions such as Amazon RDS.
Finally, you’ll work with big data tools such as Hadoop and MapReduce.
What data analysts are saying about Big Data Analytics with R:
…I don’t think there’s a better resource to learn R for data analytics…
– sbeltran
7. Big Data Analytics: Systems, Algorithms, Applications
↘️ Ideal for: data scientists
↘️ Topics covered: security, privacy, big data tools, algorithms
Big Data Analytics: Systems, Algorithms, Applications is ideal for data scientists.
➡️ Big Data Analytics: Systems, Algorithms, Applications is one of the big data books that covers techniques, technologies and applications of big data.
Similar to Data Science and Big Data Analytics and Big Data Analytics for Internet of Things, you’ll learn about the application of big data analytics in:
✅ recommendation systems
✅ Internet of Things
✅ financial services
And much more.
You’ll also look at plenty of machine learning algorithms.
8. Smart Grids and Big Data Analytics for Smart Cities
↘️ Ideal for: engineers, consultants, regulators
↘️ Topics covered: smart city infrastructure, IoT, big data analytics
💡 Smart infrastructure is data-controlled equipment that interacts with the physical world. This includes energy, transportation and more.
➡️ Smart Grids and Big Data Analytics for Smart Cities is one of the best (and only) big data analytics books for learning the elements of smart infrastructure.
You’ll start by exploring how smart city components work together and independently. Then you’ll examine standards, guidelines and recommended practices.
You’ll learn how smart grids, IoT and big data analytics work together to improve:
✅ safety
✅ healthcare
✅ low-carbon emissions
And much more.
9. Practical Big Data Analytics
↘️ Ideal for: aspiring big data professionals
↘️ Topics covered: big data, data science, machine learning
Practical Big Data Analytics is one of the best big data analytics books for aspiring big data professionals.
Similar to Data Science and Big Data Analytics, you’ll explore how to build big data and data science platforms using tools like Hadoop and Spark. You’ll also build machine learning dashboards using R programming.
💡 Spark is is a framework that can process and distribute very large data sets.
Finally, you’ll discover how big data analytics drives revenues for organizations.
10. Big Data Analytics in Supply Chain Management
↘️ Ideal for: engineering and business students
↘️ Topics covered: big data analytics, supply chain issues
Big Data Analytics in Supply Chain Management is one of the best big data analytics books for supply chain management.
You’ll learn how to apply analytical tools to extract insights to improve:
✅ quality
✅ speed
✅ reliability
And more.
You’ll also learn about best practices to resolve supply chain problems.
11. Mathematical Foundations of Big Data Analytics
↘️ Ideal for: aspiring data scientists
↘️ Topics covered: mathematics of big data analysis
Mathematical Foundations of Big Data Analytics is one of the best big data analytics books focusing exclusively on math.
You’ll apply mathematics to data analysis problems such as:
✅ brand loyalty
✅ portfolio selection
✅ credit investigation
✅ quality control
And beyond.
Mathematics covered include linear algebra, statistics and optimization.
12. Designing Data-Intensive Applications
Ready to put all this theoretical knowledge to use? Grab a copy of Designing Data-Intensive Applications.
With an insane number of 5-star reviews, this modern classic belongs on any data analyst’s bookshelf.
To quote author Martin Kleppmann, “This book is for software engineers, software architects, and technical managers who love to code.”
In Designing Data-Intensive Applications, you’ll learn how to efficiently operate systems you’ve already put into use. You’ll also discover modern databases and the distributed systems research they’re built on.
Finally, you’ll look at different technologies used for processing and storing data.
Big Data Analytics Books: Conclusion
Today we looked at the best big data analytics books including:
🔥 Best Overall 🔥
Creating Value with Big Data Analytics
💥 Best for Newbies 💥
Data Science and Big Data Analytics
💸 Best Value 💸
Designing Data-Intensive Applications
So regardless of your needs, we think these are the best big data analytics books of this year.
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What are the best big data analytics books?
Overall, we liked Creating Value with Big Data Analytics. For newbies, we think Data Science and Big Data Analytics is the way to go. And for value, Designing Data-Intensive Applications caught our attention. Check out today’s article where we look at these and other big data analytics books.
Is the book Designing Data-Intensive Applications worth it?
With an insane number of 5-star reviews, we think this modern classic belongs on any data analyst’s bookshelf. To quote author Martin Kleppmann, “This book is for software engineers, software architects, and technical managers who love to code.” To learn more about Designing Data-Intensive Applications, read today’s post.
What is big data analytics?
Big data analytics is the process of looking at, or analyzing, large sets of data. It uncovers hidden patterns, correlations and other insights. This leads to making better business decisions and more efficient operations. Learn more about big data analytics in today’s post where we look at the best big data analytics books of this year.
What does a big data analyst do?
A big data analyst does the following to data identifies, collects, visualizes and communicates. So in addition to conducting research, a big data analyst mines data for information and presents their findings. Learn more about big data analytics in today’s article where we look at the best big data analytics books.