Big Data is a massive amount of constantly growing data, and I find it fascinating due to its complexity. Traditional data systems struggle to handle it. For instance, the New York Stock Exchange generates a terabyte of new trade data daily. Facebook's systems receive a whopping 500 terabytes of fresh data every day from activities like posting photos and videos.
To learn more about Big Data, I've found Big Data books helpful. They cover various aspects, including management, analytics, and ethics. This article provides insights into these books, and if you're interested, you can also get certified through Big Data certification online courses.
Top Big Data Books for Beginners
1. Big Data: Concepts, Technology and Architecture
For data scientists, engineers, and database managers, Big Data is the best book to learn big data. It belongs in the bookcases of business intelligence analysts as well because they have to make decisions based on a ton of data. Executives and supervisors that supervise teams tasked with managing or understanding massive databases will also find this book to be helpful.
- Author Name: This book is written by Balamarugan Balusamy, Nandhini Abirami R, Seifedine Kadry and Amir Gandomi.
- Publisherās info: Wiley
Overview: For a wide range of business executives, academic researchers, and students, Big Data: Concepts, Technology, and Architecture provides an in-depth overview of the vocabulary, techniques, and technology around big data. After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle.
This big data book for beginners covers the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. With Tableau, which focuses on big data visualization, you can create scatter plots, histograms, bar, line, and pie charts. Big Data also emphasizes the application of big data in research.
Key Benefits and Takeaways
Big Data is laid out and includes explanatory case studies all through the content to demonstrate how the concepts have been used in practical situations in this big data book. Some of these ideas consist of:
- Big data technology and technologists deal with a number of similar problems, such as data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns.
- Relational and non-relational databases, such as RDBMS, NoSQL, and NewSQL databases.
- Leveraging Apache technologies like Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive to encapsulate, split, and isolate Big Data and virtualize Big Data servers.
- Examining business cases, preparing, extracting, transforming, analyzing, and displaying data are steps in the big data analytics lifecycle.
2. Spark: The Definitive Guide: Big Data Processing Made Simple
One of the best big data books, this comprehensive handbook produced by the creators of the open-source cluster-computing platform will teach you how to use, implement, and maintain Apache Spark. The writer's Bill Chambers and Matei Zaharia divide the subject of Spark into many sections, each with a particular aim, with an emphasis on the enhancements and new capabilities in Spark 2.0.
- Author Name: This book is written by Bill Chambers and Matei Zaharia
- Publisher's Info: O'Reilly
Overview: MLlib, Spark's scalable machine-learning library, is one of the best big data books that developers and system administrators will use to investigate machine-learning techniques and situations. They will also master the essentials of monitoring, adjusting, and debugging Spark.
Key Benefits and Takeaways
- Learn the basics of big data with Spark.
- Learn about the fundamental APIs of Spark: DataFrames, SQL, and Datasets using practical examples
- Explore Spark's low-level APIs, RDDs, and SQL and DataFrame execution.
- Learn how Spark functions on a cluster.
- Debug, track, and fine-tune Spark applications and clusters.
- Learn about the capabilities of Spark's Structured Streaming stream-processing engine.
- Learn how to use MLlib to solve various issues, like categorization or recommendation.
3. Big Data For Beginners
This big data book recommendation is to understand smart big data, data mining & data analytics for improved business performance, life decisions, and many more.
- Author Name: Vince Reynolds
- Publisher's Info: Createspace Independent Publishing Platform
- Published Date: 16 May 2016
Overview: This is one of the perfect books for a beginner who wants to know and understand the concept of big data from the ground level. In this book, the introduction starts by letting the reader know the world of IT or business where big data is a common concept. The book will make you revolve around various concepts of ābig dataā by making you understand big data analytics and why big data matters, it will make you aware of the key challenges of big data, how to generate business value through data mining, etc.
Key Benefits
After reading this book, it will enable you to analyze data from different data sources and create your datasets. It will also make you proficient with important industry terms and applications and tools to prepare you for a deeper understanding of other various areas of big data.
4. Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
Here this book will let you know the practical use of big data from each company profile. And from each profile, you will get learn what data was used, what problem it solved and the processes put into place.
- Author Name: Bernard Marr
- Publisher's Name: Wiley
- Release Date: May 2, 2016
Overview: Big Data's best-selling author is back, this time with a distinctive and in-depth perspective on how particular businesses use big data. Big data is a topic that everyone is talking about. Everyone is aware of its strength and significance, but many people are unaware of the concrete steps and materials needed to use it to its full potential. The knowledge gap is filled by this book, which provides a first-hand account of how big businesses use big data daily.
Learn the actual strategies and processes being used to learn about customers, improve manufacturing, foster innovation, increase safety, and much moreāfrom technology, media, and retail to sports teams, governmental organizations, and financial institutions. Each chapter is set up so that you can easily dip in and out and follows a similar format to help you find the information you need. Find out what information was used, what issue it resolved, and the procedures put in place to make it work for each company profiled. You should also learn the technical specifics, difficulties, and lessons from each scenario.
Key Benefits
- Learn how predictive analytics aids in customer understanding at Amazon, Target, John Deere, and Apple.
- Learn about the success of companies like Walmart, LinkedIn, Microsoft, and more, thanks to big data.
- Learn how big data transform banking, law, hospitality, fashion, and science.
- To create your big data strategy, utilize the additional reading provided at the end of each chapter.
5. Ethics of Big Data: Balancing Risk and Innovation
This book explores the ethical issues brought up by the big data phenomenon and explains why businesses must reevaluate their privacy and identity-related business decisions.
- Author Name: Kord Davis with Dong Patterson
- Publisher's Name: OāReilly Media
- Release Date: 16 October 2012
Overview: The authors of this book offer strategies and tactics to support your company's ethical investigation into your current data practices in a clear and beneficial manner.
It is in everyone's best interest to understand how data is handled, whether they are individuals or organizations. The quality and profitability of your brands can be directly impacted by how you use data, as Target, Apple, Netflix, and a large number of other businesses have found. With the help of this book, you'll discover how to maintain the trust of your stakeholders while aligning your actions with the stated company values.
Key Benefits
- Review your data handling procedures and ensure they adhere to your company's fundamental principles.
- Clearly state your organization's positions regarding the use of big data.
- Develop strategies to close gaps between principles and actions, and learn how to keep alignment as circumstances change over time.
- Balance the advantages of innovation with the dangers of unintended consequences.
Top Advanced Big Data Books
1. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
This book is best for people curious about big data from a social perspective and how Google searches may reveal so much about the psychology of individuals.
- Author Name: This Book is written by Seth Stephens-Davidowitz
- Publisher's Info: Harper Luxe
- Release Date: 9 May 2017
Overview: "Everybody Lies" does not entirely cover the technical side of big data, unlike other books on this list. Instead, it offers a social viewpoint by examining what information about human behavior can glean from Google search data.
In this big data analytics book, former Google data scientist Stephens-Davidowitz argues that information obtained from Google searches shows the fundamental characteristics of the human psyche. He bases his arguments on studies and tests in the fields of sociology, psychology, economics, medicine, sex, gender, and crime.
This exemplifies how advances in analytical technologies and big data affect how individuals view the world. The book's central thesis is that everyone lies, even when answering an anonymous survey. As a result, the author concludes that not everything we believe to be true about people is true.
Key Takeaways
Numerous honors have been awarded to "Everybody Lies," including New York Times Bestseller, Entrepreneur Top Business Book, Amazon Best Book of the Year in Business and Leadership, and Economist Best Book of the Year.
2. Designing Data-Intensive Applications
Software developers who want to understand the principles of creating data-intensive applications, the benefits and drawbacks of the various accessible technologies, and the critical ideas required to succeed in the process should read this book.
- Author Name: This Book is written by Martin Kleppman
- Publisher's Info: O'Reilly
Overview: It isn't easy to manage data in its entirety, especially when it comes to system design. Scalability, consistency, stability, efficiency, and maintainability are just a few of the obstacles this business faces frequently. It also has to deal with the sheer volume of software and technologies on the market.
With this concept in mind, author Martin Kleppmann seeks to provide readers with a technical yet thorough explanation of these buzzwords and technology.
Key Takeaways
The book "Designing Data-Intensive Applications" offers an expert viewpoint to help readers understand the process rather than a step-by-step manual on creating a distributed system. By outlining the key ideas, discussing the benefits and drawbacks of the different tools and technologies, and guiding the reader through the entire data processing and storage landscape.
3. Big Data Marketing: Engage Your Customers More Effectively and Drive Value
This book uses the insights from big data to enhance customer service and guarantee business success.
- Author Name: Lisa Arthur
- Publisherās Name: Wiley
- Published Date: 7 October 2013
Overview: Many modern businesses are paralyzed by internal silos, mired in a maze of internal data, and using outmoded marketing strategies. Customers are growing impatient, shareholders demand growth and differentiation, and marketers are left scrambling to sort through the enormous mess. Big Data Marketing offers a strategic road map for executives looking to organize the chaos and start generating competitive advantage and top-line growth. This book will assist you in learning about the solution provided by data-driven marketing by using practical examples, everyday language, additional downloadable resources, and a healthy dose of humor.
Key Benefits
- How marketers can use data to get the information they need
- How to adopt metrics as your motto
- The five essential elements of a winning strategy
- Methods for enhancing marketing relevance and Return On Marketing Investment (ROMI)
- methods for managing marketing expenses, the biggest variable costs for a business
- How to use relevant marketing to drive value
- Proven techniques for improving customer experiences
Improve your overall strategy and marketing techniques by improving your market understanding. Patterns in your customers' behavior are revealed by big data marketing, and there are tested strategies to improve customer experiences.
4. Big Data, Big Analytics: Emerging Business Intelligence and Analytics Trends for Todayās Businesses
This book on big data provided a unique perspective on the big data analytics phenomenon for both business and IT professionals.
- Author Name: Michael Minelli
- Publisher's Name: Wiley
- Released Date: 11 January 2013
Overview: A unique period in business history has resulted from the accessibility of Big Data, affordable commodity hardware, and new information management and analytics software. We now have the skills necessary to analyze astounding data sets quickly and affordably for the first time in history thanks to the convergence of these trends. These abilities are neither merely hypothetical nor unimportant. They represent a real advancement and a great chance to achieve significant increases in effectiveness, productivity, income, and profitability.
Key Takeaways
Big Data is here, and we are living in truly revolutionary times. This timely book examines forward-thinking businesses that are supporting an intriguing new class of business analytics.
- Find out more about big data trends and how they affect the business world (risk, marketing, healthcare, financial services, etc.).
- explains this new technology and how businesses can utilize it to collect the data they need and gain important insights efficiently.
- examines timely subjects like data privacy, data visualization, unstructured data, data scientists hired from the crowd, cloud computing for big data, and much more.
5. People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent
Predictive analytics are used throughout all phases of workforce management in this book.
- Author Name: Jean Paul Isson
- Publisherās Name: Wiley
- Released Date: 15 April 2016
Overview: The book People Analytics in the Era of Big Data offers a step-by-step guide for using data analytics to make the most of your talent pool. This book, written by the global vice president of business intelligence and predictive analytics at Monster Worldwide, is brimming with practical advice for finding, acquiring, engaging, retaining, promoting, and managing the top talent your company needs. This comprehensive guide offers the crucial viewpoint that integrates analytics into HR in an actual beneficial way, using a special approach that applies analytics to every stage of the hiring process and the entire cycle of workforce planning and management.
Why not mine the disparate employee data you already have for insights that will benefit your business and bolster your workforce? With ground-breaking illustrations of workforce analytics in action across the United States, Canada, Europe, Asia, and Australia, this book offers a useful framework for real-world talent analytics.
Key Takeaways
- Utilize predictive analysis at every stage of the hiring process.
- Apply analytics methods to improve workforce management.
- Discover the benefits of people analytics for businesses of all sizes and across industries.
- Integrate analytics fully and systematically into HR practices.
Corporate executives require information-based forecasts of what will happen to their talent. Whom do you want to hire? How should someone be promoted? Who are the top or bottom performers, and why? Who is most likely to give up, and why? These questions can be answered by analytics, which can also give you insights based on quantifiable data as opposed to intuition and subjective evaluation. The essential manual for optimizing your workforce with the resources already at your disposal is People Analytics in the Era of Big Data.
Preparation Tips for Big Data
- Deep Comprehension of Data's Predicted Answers to Current and Future Business Concerns: Knowing the business sectors where big data analytics will be used creates a business context for the data and aids in establishing the data collection and implementation strategy. This phase aims to determine which of your company's data are important to important business questions and which aren't. It is important to narrow the data focus at first, but you can extend the business questions and the data you seek as business needs alter.
- Combining Data: Data needs to be standardized to be uniform and used by everyone inside the company. Because of this, storing all analytics data in a centralized, IT-maintained repository is crucial, even if you decide to populate distinct subsets of this master data for other business sectors.
- Identifying Data Sources that must be Incorporated into Main Analytics Information Store: Following the definition of business cases and questions, datasets and sources that may be used collectively to address the business's pressing issues should be located. These data sources may originate from within or outside the company.
- Identifying Potential Future Relevant Data Sources: At the same time, it is not too early to start identifying additional data sources or sets that the company might require in the future. These data sources won't have any prepared data, but identifying them will give instructions for future data preparation.
More Ways To Learn Big Data
There is this age-old technique of learning big data through books. On the contrary, there are new intuitive ways, learning techniques and methods that have been devised lately. One of them is KnowledgeHutās Big Data certification online. With explanatory classes from experts who will solve all your doubts about all the required material for the course present in a single place, you can get acquainted with big data while sitting at home. Visit the website today to get more information on various similar courses.
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Conclusion
Big Data is a crucial aspect that can significantly impact how well a firm performs, and I believe having experts proficient in using the tools is essential, sometimes with the help of big data books. As someone well-versed in big data, I understand how to gather data, interpret it, choose insights, and influence major business decisions, drawing knowledge from the best big data books of 2023.
I've discovered valuable Big Data courses offered by KnowledgeHut, designed to enhance the skills needed to succeed in a big data employment role.
Obtain certification in the newest and most well-liked systems used in the industry, like Hadoop, Apache, Hive, Pig, and others. Use the cross-functionality of the area to apply it to machine learning, and use your newly acquired knowledge on real projects. Use the cross-functionality of the area to apply it to machine learning, and use your newly acquired knowledge on real projects. Interviews with your desired employers, such as Meta, Amazon, Apple, Netflix, Google, and more, will go well for a well-rounded individual with skills outside of technology. Check KnowledgeHutās Big Data courses for a big career ahead.
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