Introduction
How many of you would agree / disagree with this statement?
Does Google know and understand you better than yourself?
Let me know your views through the comments below..
I've been thinking about the above statement for some time and it can be difficult to take an absolute stance, but the very fact that you need to think about it means the importance of data. Think about it, our opinion of ourselves is biased by what we want to be. Our view of ourselves is influenced by emotions, the actuality and limitations of human memory. But Google doesn't have these limitations!!
Companies are now more aware of our lifestyle, choices and daily routine that we. Thanks to our data stored by smartphones, wristbands, fitness tracker, purchase invoices, etc.
But, What use will my data be to these companies? I asked myself the same question until I read one of the books listed below. Technologies like Hadoop, MapReduce, Apache Spark have brought about a revolution in the ways of analyzing big data. Spark, being the last, promises ‘lightning fast cluster computing’.
This is probably the best time to make a career in Big Data. I think nothing beats books when it comes to learning a concept at its core. In this article, I have listed the best beginner books on Hadoop, Apache Spark y Big Data.
Who is this article for?
This article is for complete beginners in Big Data. Does not assume any prior knowledge of big data.
To simplify the learning experience, I also divided the books into 2 groups:
- Big Data para Layman
- Big Data for technology experts.
As the name suggests, the first cluster introduces the huge world of Big Data to ordinary people. These books will not teach you the techniques for developing Big Data capabilities., but they will allow you to understand the domain.
The second group of books is intended for technology experts: people looking to develop a career in Big Data. These books are treasures of technical knowledge, that should allow you a shiny Driving a career ahead.
Big Data para Layman
The human face of Big Data
This book is written by Rick Smolan and Jennifer Erwitt. In this book, learn about interesting ways big data makes life healthier for children and older people. It has 10 essays and stunning infographics published by leading industry writers. Connect big data with real stories of human life and its transformation. I'm sure this book will definitely add to your current perspective on big data..
Big Data: a revolution that will transform the way we live, we work and think
This book is written by Kenneth Cukier and Viktor Mayer Schonberger. This book takes you on a global tour of the values added by big data in all industries.. This book will help you stay ahead of the key trends that will define businesses for years to come.. Jeff Jonas, Chief Scientist, IBM Entity Analytics, said: “The book is packed with great insights into new ways of harnessing information and offers a compelling vision of the future. It is essential reading for anyone who uses, or be affected by, big data ‘.
Datacylsm: about us (when we think nobody is looking)
This book is written by Christian Rudder. It's a New York Times best seller. Do i need to say anything else? Well! here's a quick look. This book covers some of the best cases of big data and its profound impact on our lives.. It presents a world that is primarily based on numbers and data that only humans. Definitely a must to keep the book in your own book.
Signal and noise: why so many predictions fail, but some don't
This book is written by Nate Silver. It is made up of interesting cases driven by statistics, economy, predictions. It also makes one aware of common mistakes to avoid when making predictions and offers a wealth of knowledge on forecasting and forecasting.. This is a must-read book for data scientists, analysts, statisticians and anyone who admires the power of data.
The second era of machines: job, progress and prosperity in an age of brilliant technologies
This book is written by Erik Brynjolfsson, Andrew McAfee y Jeff Cummings. Before you start reading it, you should know that it is an audiobook. This book takes a giant leap into the future and shows the indomitable reign of machines and computers in humans.. Defines the era of the industrial revolution and the next one too (maybe next). Presents a realistic version of digital advancements in various facets of human life.
Big Data for Technicians – Hadoop
Hadoop for dummies
This book is written by Dirk Deroos. This book is easy to read and understand, and is intended for beginners (as the name suggests). Makes the reader understand the value of big data and hadoop. Explain the origin of hadoop, its benefits, functionality, practical applications and makes you feel comfortable when handling it. It also familiarizes you with the hadoop ecosystem, cluster, mapreduce, layout patterns and many more Hadoop operations.
Hadoop: the definitive guide
This book is written by Tom White. Describes useful methods for building, maintain reliable systems, scalable and distributed with Apache Hadoop. Explains the concept of HDFS and Mapreduce in great detail. This book offers excellent results when read with discipline. Beginners will find it difficult to understand at first. But, as you read the chapters, will start to love them.
Hadoop operations
This book is written by Eric Sammer. As the name suggests, This book will teach you the methods for maintaining large and complex hadoop groups. Eric hasn't just covered the essentials of Hadoop, it has also provided some invaluable approaches that can help a person to perform these tasks efficiently. You will find chapters dedicated to maintenance, the backups, the supervision, problem solving, etc. Covers all possible Hadoop components that a big data engineer should know about.
Agile data science: building data analytics applications with Hadoop
This book is written by Russell Jurney. This book provides you with the knowledge you need to build powerful analytical applications using Hadoop in an enterprise environment.. Use tools like Python, Apache Pig, D3.js to create an agile environment for data exploration using examples. These sample codes are available on github. This book is suitable for intermediate users who have a good understanding of data analytics.
Hadoop in practice
This book is written by Alex Holmes. This is probably the best practice book on Hadoop. It has 85 Hadoop examples in question and answer format. Using these problems, you will explore the hidden aspects of hadoop and learn the ways to build and implement a specific solution based on the needs served. More than just examples, it will also introduce you to the methods to integrate MapReduce and R. Author has effortlessly explained complicated concepts in plain, plain English. It is highly recommended for beginners.
Professional Hadoop solutions
This book is written by Boris Lublinsky, Kevin T Smith, Alexey Yakubovich. This book is a detailed guide that explains how to integrate the Hadoop framework and APIs to provide real-world solutions.. What's more, exposes the inner workings of APIs to allow architects and developers to better leverage and customize them. More than just an implication, teaches the best scenarios in which these codes should be used (Java and XML).
MapReduce design patterns: creating effective algorithms and analytics for Hadoop
This book is written by Donald Miner. This book assumes the reader has a basic understanding of hadoop. It is best suited for advanced beginners who want to master map reduction algorithms. Describes various uses of MapReduce with Hadoop. Contains several useful methodologies to quickly solve many hadoop problems. Summarize these concepts with interesting examples.
Big Data for Technicians: Apache Spark
Learning Spark: Lightning-Fast Big Data Analysis
This book is written by Holden Karau, Andy Konwinski, Patrick Wendell and Matei Zaharia. This is more suitable for people new to Spark. Explains difficult concepts in simple, easy-to-understand English. I recommend this book for beginners. This book teaches you how to take advantage of Spark's powerful built-in libraries, incluidas Spark SQL, Spark Streaming y Mlib. Above all, will allow you to master topics like data partitioning and shared variables.
Spark: Learn Spark in a DAY!
This book is written by Acodemy. Another book for beginners. This book covers the basics of Spark and its related component. It's good enough to get started with Spark, but can't wait any longer than that. Follow a step-by-step method to explain abstruse theories and concepts. In the end, This book will teach you the methods to use to generate Spark to its fullest potential..
Advanced analysis with Spark: patterns to learn from data at scale
This book is written by Sandy Ryza, Uri Laserson, Sean Owen y Josh Wills. Once you have read any of the books mentioned above, this is the natural next step. Time to increase your spark knowledge. This book highlights the procedure for approaching large-scale data analysis with Spark. Along with Spark, covers statistical methods to teach the ideal analytical approach. This book offers a basic understanding of machine learning, statistics, Java, Python or Scala.
Divulgation: The Amazon links in this article are affiliate links. If you buy a book through this link, they will pay us through Amazon. This is one of the ways we can cover our costs as we continue to create these amazing items.. What's more, the list reflects our recommendation based on the content of the book and is in no way influenced by the commission.
Final notes
In this article, I have listed some of the best books (what do I perceive) about big data, Hadoop y Apache Spark. These books are a must have for beginners who want to build a successful career in big data..
Books require discipline and perseverance. I had none. Until I picked a book and read it cover to cover. If you haven't already, now it's your turn. The books listed above comprise all the essential knowledge to take the first step in big data. Technologies like Hadoop, Apache Spark are in great demand all over the world. Companies have data, they even have technologies, but they don't have skilled labor to work on them.
Did I leave out a useful book on Big Data, Hadoop o Apache Spark? Share your thoughts in the comment section below..
