› › Big Data Tools Which When And How

Big Data Analytics with Hadoop 3

Author : Sridhar Alla

Publisher : Packt Publishing Ltd

Page : 471 pages

File Size : 13,56 MB

Release : 2018-05-31

Category : Computers

ISBN : 1788624955

Get eBook

Book Description

Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.



Big Data Analytics

Author : Arun K. Somani

Publisher : CRC Press

Page : 484 pages

File Size : 12,74 MB

Release : 2017-10-30

Category : Computers

ISBN : 1315391244

Get eBook

Book Description

The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.



Big Data Analytics

Author : David Loshin

Publisher : Elsevier

Page : 143 pages

File Size : 32,41 MB

Release : 2013-08-23

Category : Computers

ISBN : 0124186645

Get eBook

Book Description

Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. - Guides the reader in assessing the opportunities and value proposition - Overview of big data hardware and software architectures - Presents a variety of technologies and how they fit into the big data ecosystem



Big Data Analytics

Author : Frank J. Ohlhorst

Publisher : John Wiley & Sons

Page : 176 pages

File Size : 11,36 MB

Release : 2012-11-15

Category : Business & Economics

ISBN : 1118239040

Get eBook

Book Description

Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantage Takes an in-depth look at the financial value of big data analytics Offers tools and best practices for working with big data Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.



Practical Big Data Analytics

Author : Nataraj Dasgupta

Publisher : Packt Publishing Ltd

Page : 402 pages

File Size : 13,32 MB

Release : 2018-01-15

Category : Computers

ISBN : 1783554401

Get eBook

Book Description

Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.



Big Data, Big Analytics

Author : Michael Minelli

Publisher : John Wiley & Sons

Page : 230 pages

File Size : 48,79 MB

Release : 2013-01-22

Category : Business & Economics

ISBN : 111814760X

Get eBook

Book Description

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.



Big Data Analytics with Spark

Author : Mohammed Guller

Publisher : Apress

Page : 290 pages

File Size : 46,23 MB

Release : 2015-12-29

Category : Computers

ISBN : 1484209648

Get eBook

Book Description

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert. Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics. This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources. The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. You’ll learn the basics of functional programming in Scala, so that you can write Spark applications in it. What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language. There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost—possibly a big boost—to your career.



Big Data Tools – Which, When and How? (Volume– IV)

Author : Dr. Poornima G. Naik Dr. Girish R. Naik

Publisher : Shashwat Publication

Page : 326 pages

File Size : 14,95 MB

Release : 2023-12-04

Category : Education

ISBN : 9390290244

Get eBook

Book Description

MongoDB is an open source cross platform document-oriented NoSQL (Not Only SQL) database management system that provides high performance and availability and easy scalability. It is particularly employed for high volume of data storage. Two key features of MongoDB which have made it popular are auto sharding for horizontal scalability and in-built replication mechanism for high availability both of which are inevitable for big data analytics MongoDB came into existence to address the large data size and unstructuredness of data which could not be handled by the traditional database management systems. Volume IV of 'Big Data Tools - Which, When and How (Hands on Sessions with MongoDB Basics)’ is intended for learners who have just migrated from SQL systems to NoSQL systems and keen in exploring the differences between the two. The book covers the basics of MongoDB such as MongoDB architecture, installation of MongoDB, modeling relationship between the documents, and managing collections. The key features of the books are in-depth coverage of structural differences between RDBMS systems, installation of MongoDB on Windows and Ubuntu operating systems, exposure to MongoDB complex structures, cursors in MongodB. MongoDB has a rich set of database management tools. Few prominent tools are focused with in-depth discussion on two MongoDB GUI tools having wide acceptance in industry viz. MongoDB Compass and RockMongo. Difficult to comprehend topics such as GridFS for storing multimedia content in MongoDB database, custom auto-increment field, data validation and bulk API are illustrated with suitable examples. The salient feature of the book is mapping of SQL Statements to MongoDB statements which enables the reader coming from SQL background to comprehend the alterations to be made for querying JSON-based systems.



Big Data Analytics

Author : Kim H. Pries

Publisher : CRC Press

Page : 564 pages

File Size : 25,92 MB

Release : 2015-02-05

Category : Computers

ISBN : 1482234521

Get eBook

Book Description

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif



Data Science and Big Data Analytics

Author : EMC Education Services

Publisher : John Wiley & Sons

Page : 432 pages

File Size : 28,59 MB

Release : 2014-12-19

Category : Computers

ISBN : 1118876229

Get eBook

Book Description

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!