Top 10 Best Books to Read in Databases & Big Data - August 2021

Here are our top ten recommendations if you are looking for the best books to read in Databases & Big Data. We have made sure our list is diverse to cater to the interests of different types of readers.

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


Top 10 Best Books to Read in Databases & Big Data - August 2021

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

  • Author: Martin Kleppmann
  • Publisher: O'Reilly Media; 1st edition (April 18, 2017)
  • Genre: Computers & Technology, Databases & Big Data
  • ISBN: 978-1449373320
  • Dimensions: 7.01 x 1.24 x 9.17 inches

                 

2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems


Top 10 Best Books to Read in Databases & Big Data - August 2021

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and Tensor Flow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the Tensor Flow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets.

  • Author: Aurélien Géron
  • Publisher: O'Reilly Media; 2nd edition (October 15, 2019)
  • Genre: Computers & Technology, Computer Science
  • ISBN: 978-1492032649
  • Dimensions: 7 x 1.2 x 9.2 inches

                 

3. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are


Top 10 Best Books to Read in Databases & Big Data - August 2021

Foreword by Steven Pinker Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak , a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions. By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable. Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women? Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

  • Author: Seth Stephens-Davidowitz
  • Publisher: Dey Street Books; Reprint edition (May 9, 2017)
  • Genre: History, Americas

                 

4. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython


Top 10 Best Books to Read in Databases & Big Data - August 2021

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupiter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupiter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas group by facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples.

  • Author: Wes McKinney
  • Publisher: O'Reilly Media; 2nd edition (October 31, 2017)
  • Genre: Computers & Technology, Databases & Big Data
  • ISBN: 978-1491957660
  • Dimensions: 7 x 1.3 x 9.1 inches

                 

5. Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People


Top 10 Best Books to Read in Databases & Big Data - August 2021

Summary Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel. Continue your journey into the world of algorithms with Algorithms in Motion , a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/algorithms-​in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs. About the Book Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. What's Inside Covers search, sort, and graph algorithms Over 400 pictures with detailed walkthroughs Performance trade-offs between algorithms Python-based code samples About the Reader This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. About the Author Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io . Table of Contents Introduction to algorithms Selection sort Recursion Quicksort Hash tables Breadth-first search Dijkstra's algorithm Greedy algorithms Dynamic programming K-nearest neighbors.

  • Author: Aditya Bhargava
  • Publisher: Manning Publications; 1st edition (May 1, 2016)
  • Genre: Computers & Technology, Computer Science
  • ISBN: 978-1617292231
  • Dimensions: 7.38 x 0.4 x 9.25 inches

                 



6. The Ascent of Information: Books, Bits, Genes, Machines, and Life's Unending Algorithm


Top 10 Best Books to Read in Databases & Big Data - August 2021

Your information has a life of its own, and it ’ s using you to get what it wants. One of the most peculiar and possibly unique features of humans is the vast amount of information we carry outside our biological selves. But in our rush to build the infrastructure for the 20 quintillion bits we create every day, we’ve failed to ask exactly why we’re expending ever-increasing amounts of energy, resources, and human effort to maintain all this data. Drawing on deep ideas and frontier thinking in evolutionary biology, computer science, information theory, and astrobiology, Caleb Scharf argues that information is, in a very real sense, alive. All the data we create—all of our emails, tweets, selfies, A.I.-generated text and funny cat videos—amounts to an aggregate lifeform. It has goals and needs. It can control our behavior and influence our well-being. And it’s an organism that has evolved right alongside us. This symbiotic relationship with information offers a startling new lens for looking at the world. Data isn’t just something we produce; it’s the reason we exist. This powerful idea has the potential to upend the way we think about our technology, our role as humans, and the fundamental nature of life. The Ascent of Information offers a humbling vision of a universe built of and for information. Scharf explores how our relationship with data will affect our ongoing evolution as a species. Understanding this relationship will be crucial to preventing our data from becoming more of a burden than an asset, and to preserving the possibility of a human future.

  • Author: Caleb Scharf
  • Publisher: Riverhead Books (June 15, 2021)
  • Genre: Kindle Store, Kindle eBooks, Computers & Technology

                 

7. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy


Top 10 Best Books to Read in Databases & Big Data - August 2021

NEW YORK TIMES  BESTSELLER  •  A former Wall Street quant sounds the alarm on Big Data and the mathematical models that threaten to rip apart our social fabric—with a new afterword   “A manual for the twenty-first-century citizen . . . relevant and urgent.”— Financial Times   NATIONAL BOOK AWARD LONGLIST • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY  The New York Times Book Review  • The Boston Globe • Wired  •  Fortune  •  Kirkus Reviews  •  The Guardian  •  Nature  •  On Point   We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.   But as mathematician and data scientist Cathy O’Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination—propping up the lucky, punishing the downtrodden, and undermining our democracy in the process. Welcome to the dark side of Big Data.

  • Author: Cathy O'Neil
  • Publisher: Crown; Reprint edition (September 5, 2017)
  • Genre: Science & Math, Mathematics
  • ISBN: 978-0553418835
  • Dimensions: 5.14 x 0.6 x 7.89 inches

                 

8. Product Management's Sacred Seven: The Skills Required to Crush Product Manager Interviews and be a World-Class PM (Fast Forward Your Product Career: The Two Books Required to Land Any PM Job)


Top 10 Best Books to Read in Databases & Big Data - August 2021

Authored by 3 Product Managers at Facebook, Google, and Microsoft, Product Management’s Sacred Seven is a comprehensive resource that will teach you the must-know knowledge and applied skills necessary to become a world-class PM that can get hired anywhere. In writing this book, we interviewed 67 product leads and hiring managers from 52 top companies around the world. They ranged from all the usual FAANG suspects to darling unicorns such as Coinbase, TikTok, and Grab. We asked everyone two simple questions: What knowledge separates interview candidates you hire from those you don't? What hard skills help PMs advance their careers the fastest? Given that we talked to product leaders across the world who worked in various different countries and industries, we expected to see no clear pattern in our responses. We were shocked to find a common theme across all of our interviews. The knowledge and skills which separated exceptional PMs from the rest all boiled down to seven subjects: product design, economics, psychology, user experience, data science, law & policy, and marketing & growth. The average PM excels at 2 or 3 of these disciplines. A truly world-class product manager, however, thrives in all 7. Authored by the #1 bestselling authors of Swipe to Unlock, this book blends case studies, theory, and mental models to help you master these seven subjects and fast forward your product career! Inside Product Management’s Sacred Seven , you’ll find real-world examples from over four dozen companies, battle-tested interview tips, and free access to a library of bonus video content online. Topics Covered: Product Development, Hypothesis Testing, Market Selection, Prototyping, Product Strategy, Business Models, Market Entry Strategies, Unit Economics, Customer Economics, Product Segmentation, Pricing Psychology, User Motivation, Creating Product Stickiness & Habit, Gamification, Cognition & Mental Models, UX Principles, Product Usability, Light & Dark Patterns, Data Analysis, Experimentation Frameworks, Product Metrics, Storytelling with Data, Antitrust Policy, Intellectual Property, Platform Liability, Privacy, Employment Law, Accessibility, Brand Building, Advertising, Growth Hacking and much more! Featured Companies: Google, Facebook, Microsoft, Amazon, TikTok, Snapchat, Apple, Spotify, Uber, WeChat, Yelp, Tinder, Twitter, Tesla, ByteDance, OnePlus, PayPal, LinkedIn, Airbnb, Pinterest, Zillow, Visa, Salesforce, Asana, Robinhood, Adobe, Alibaba, Netflix, Bloomberg, Shopify, Trello, Workday, Notion, Nintendo, Glossier, Lyft, Telegram, Disney, and many more! Read Sacred Seven today to ace your PM interviews and become a better product leader!

  • Author: Parth Detroja
  • Publisher: Paravane Ventures (August 6, 2020)
  • Genre: Computers & Technology, Networking & Cloud Computing
  • ISBN: 978-0578740584
  • Dimensions: 6 x 1.72 x 9 inches

                 

9. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data


Top 10 Best Books to Read in Databases & Big Data - August 2021

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle —transform your datasets into a form convenient for analysis Program —learn powerful R tools for solving data problems with greater clarity and ease Explore —examine your data, generate hypotheses, and quickly test them Model —provide a low-dimensional summary that captures true "signals" in your dataset Communicate —learn R Markdown for integrating prose, code, and results.

  • Author: Hadley Wickham
  • Publisher: O'Reilly Media; 1st edition (January 17, 2017)
  • Genre: Science & Math, Mathematics
  • ISBN: 978-1491910399
  • Dimensions: 5.98 x 1.05 x 9.02 inches

                 

10. Don't Make Me Think, Revisited: A Common Sense Approach to Web Usability (3rd Edition) (Voices That Matter)


Top 10 Best Books to Read in Databases & Big Data - August 2021

Since Don’t Make Me Think was first published in 2000, hundreds of thousands of Web designers and developers have relied on usability guru Steve Krug’s guide to help them understand the principles of intuitive navigation and information design. Witty, commonsensical, and eminently practical, it’s one of the best-loved and most recommended books on the subject. Now Steve returns with fresh perspective to reexamine the principles that made Don’t Make Me Think a classic–with updated examples and a new chapter on mobile usability. And it’s still short, profusely illustrated…and best of all–fun to read. If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites. “After reading it over a couple of hours and putting its ideas to work for the past five years, I can say it has done more to improve my abilities as a Web designer than any other book.” –Jeffrey Zeldman, author of Designing with Web Standards .

  • Author: Steve Krug
  • Publisher: New Riders; 3rd edition (December 24, 2013)
  • Genre: Computers & Technology, Databases & Big Data
  • ISBN: 978-0321965516
  • Dimensions: 7.13 x 0.43 x 9.02 inches