Books: 29

Data Analytics

This book examines the Internet of Things (IoT) and Cyber-Physical Systems (CPS) from a technical, economical and application point of view * Examines cloud computing, data analytics, and sustainability and how they relate to IoT/CPS * Covers the scope of both consumer IoT and enterprise/government more » CPS applications * Includes best practices, business model and real-world case studies « less
Analytics for Data Scientists
Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 2016 places a powerful analytical more » processor into an environment most developers are already comfortable with – Visual Studio. This book walks even the newest of users through the creation process of a powerful R-language tool set for use in analyzing and reporting on your data. As a SQL Server database administrator or developer, it is sometimes difficult to stay on the bleeding edge of technology. Microsoft’s addition of R to SQL Server 2016 is sure to be a game-changer, and the language will certainly become an integral part of future releases. R is in fact widely used today in statistical and related applications, and its use is only growing.Beginning SQL Server R Serviceshelps you jump on board this important trend by providing good examples with detailed explanations of the WHY and not just the HOW. * Walks you through setup and installation of SQL Server R Services. * Explains the basics of working with R Tools for Visual Studio. * Provides a road map to successfully creating custom R code. What You Will Learn * Discover R’s role in the SQL Server 2016 hierarchy. * Manage the components needed to run SQL Server R Services code. * Run R-language analytics and queries inside the database. * Create analytic solutions that run across multiple datasets. * Gain in-depth knowledge of the R language itself. * Implement custom SQL Server R Services solutions. Who This Book Is For Beginning SQL Server R Services is for any level of database administrator or developer, but specifically it's for those developers with the need to develop powerful data analytics applications quickly. Seasoned R developers will appreciate the book for its robust learning pattern, using visual aids in combination with properties explanations and scenarios. Beginning SQL Server R Services is the perfect “new hire” gift for new database developers in any organization. « less
KEY FEATURES * This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. * Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and more » SparkR. * Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. BOOK DESCRIPTION Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. WHAT YOU WILL LEARN * Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop * Understand all the Hadoop and Spark ecosystem components * Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx * See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming * Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. ABOUT THE AUTHOR Venkat Ankam has over 18 years of IT experience and over 5 years in big data technologies, working with customers to design and develop scalable big data applications. Having worked with multiple clients globally, he has tremendous experience in big data analytics using Hadoop and Spark. He is a Cloudera Certified Hadoop Developer and Administrator and also a Databricks Certified Spark Developer. He is the founder and presenter of a few Hadoop and Spark meetup groups globally and loves to share knowledge with the community. Venkat has delivered hundreds of trainings, presentations, and white papers in the big data sphere. While this is his first attempt at writing a book, many more books are in the pipeline. TABLE OF CONTENTS 1. Big Data Analytics at 10,000 foot view 2. Getting Started with Apache Hadoop and Apache Spark 3. Deep Dive into Apache Spark 4. Big Data Analytics with Spark SQL, DataFrames, and Datasets 5. Real-Time Analytics with Spark Streaming and Structured Streaming 6. Notebooks and Dataflows with Spark and Hadoop 7. Machine Learning with Spark and Hadoop 8. Building Recommendation Systems with Spark and Mahout 9. Graph Analytics with GraphX 10. Interactive Analytics with SparkR « less
KEY FEATURES * A quick way to get started with Spark – and reap the rewards * From analytics to engineering your big data architecture, we've got it covered * Bring your Scala and Java knowledge – and put it to work on new and exciting problems BOOK DESCRIPTION When people want a way to process more » big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it's unsurprising that it's becoming popular with data analysts and engineers everywhere. Beginning with the fundamentals, we'll show you how to get set up with Spark with minimum fuss. You'll then get to grips with some simple APIs before investigating machine learning and graph processing – throughout we'll make sure you know exactly how to apply your knowledge. You will also learn how to use the Spark shell, how to load data before finding out how to build and run your own Spark applications. Discover how to manipulate your RDD and get stuck into a range of DataFrame APIs. As if that's not enough, you'll also learn some useful Machine Learning algorithms with the help of Spark MLlib and integrating Spark with R. We'll also make sure you're confident and prepared for graph processing, as you learn more about the GraphX API. WHAT YOU WILL LEARN * Install and set up Spark in your cluster * Prototype distributed applications with Spark's interactive shell * Perform data wrangling using the new DataFrame APIs * Get to know the different ways to interact with Spark's distributed representation of data (RDDs) * Query Spark with a SQL-like query syntax * See how Spark works with big data * Implement machine learning systems with highly scalable algorithms * Use R, the popular statistical language, to work with Spark * Apply interesting graph algorithms and graph processing with GraphX ABOUT THE AUTHOR Krishna Sankar is a Senior Specialist—AI Data Scientist with Volvo Cars focusing on Autonomous Vehicles. His earlier stints include Chief Data Scientist at, Principal Architect/Data Scientist at Tata America Intl. Corp., Director of Data Science at a bioinformatics startup, and as a Distinguished Engineer at Cisco. He has been speaking at various conferences including ML tutorials at Strata SJC and London 2016, Spark Summit [], Strata-Spark Camp, OSCON, PyCon, and PyData, writes about Robots Rules of Order [], Big Data Analytics—Best of the Worst [], predicting NFL, Spark [], Data Science [], Machine Learning [], Social Media Analysis [] as well as has been a guest lecturer at the Naval Postgraduate School. His occasional blogs can be found at His other passion is flying drones (working towards Drone Pilot License (FAA UAS Pilot) and Lego Robotics—you will find him at the St.Louis FLL World Competition as Robots Design Judge. TABLE OF CONTENTS 1. Installing Spark and Setting Up Your Cluster 2. Using the Spark Shell 3. Building and Running a Spark Application 4. Creating a SparkSession Object 5. Loading and Saving Data in Spark 6. Manipulating Your RDD 7. Spark 2.0 Concepts 8. Spark SQL 9. Foundations of Datasets/DataFrames – The Proverbial Workhorse for DataScientists 10. Spark with Big Data 11. Machine Learning with Spark ML Pipelines 12. GraphX « less
Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0
About This Book Perform data analysis and build predictive models on huge datasets that leverage Apache Spark Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges Work through practical examples on real-world more » problems with sample code snippets Who This Book Is For This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you! What You Will Learn Consolidate, clean, and transform your data acquired from various data sources Perform statistical analysis of data to find hidden insights Explore graphical techniques to see what your data looks like Use machine learning techniques to build predictive models Build scalable data products and solutions Start programming using the RDD, DataFrame and Dataset APIs Become an expert by improving your data analytical skills In Detail This is the era of Big Data. The words ‘Big Data’implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. « less
A Hands-on Guide
Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big more » data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: * More than 200 examples and exercises, including code and datasets for practice. * Relevant examples for all industries. * Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before. WHAT YOU’LL LEARN * Which are the most important tools for performing analytics * How to program in SAS * How to explore, validate, and clean data * How to understand and use basic statistical methods and techniques * How to forecast future value using SAS * How to build predictive models * Fundamentals of big data WHO THIS BOOK IS FOR This book is for IT Professionals who want to become business or data analysts, predictive modelers, data scientists, social media analysts, big data analysts, or BI analysts. It's also for anyone who wants to break into data analytics or professionals who want to expand their skills. TABLE OF CONTENTS Part One: Basics of SAS Programming for Analytics Chapter 01 Introduction to Business Analytics and Data Analysis Tools Chapter 02: SAS Introduction Chapter 03: SAS Handling Using SAS Chapter 04 : Important SAS Functions and Procs Part Two: Using SAS for Business Analytics Chapter 05 Introduction to Statistical Analysis Chapter 06 Basic Descriptive Statistics Chapter 07 Data Exploration, Validation, and Data Sanitization Chapter 08 Testing of Hypothesis Chapter 09 Correlation and Linear Regression Chapter 10 Multiple Regression Analysis Chapter 11: Logistic Regression Chapter 12: Time Series Analysis and Forecasting Chapter 13: Introducing Big Data Analytics « less
Processing and Management
Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental more » challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques. « less
Bring your data to life by creating and deploying complex data visualizations with D3.js
KEY FEATURES * Learn how to create custom charts as reusable components that can be integrated with your existing projects * Design data-driven applications with several charts interacting between them * Create an analytics dashboard to display real-time data using Node.js and D3 BOOK DESCRIPTION D3.js more » is one of the most popular and powerful tools for creating data visualizations. As the pressure to produce accurate and clear insights from data increases, D3.js remains a reliable and high-quality data visualization solution. Mastering D3.js provides you with clear and detailed guidance to help you dive deeper into D3, and learn how to create data visualizations that are capable of responding to the modern challenges of data. Taking a comprehensive approach to D3.js, and tackling everything you need to take your data visualization skills to another level of sophistication, Mastering D3.js is an essential book for anyone interested in the intersection of data science and design. Use this advanced D3.js book to get to grips with cutting-edge data visualization. Learn how to create a reusable chart and a layout algorithm, before moving further into D3, as you learn how to make a color picker and develop an effective user interface. You will also find further practical information on how to create a quality user dashboard for high-quality big data analytics and tips to help you learn how to integrate mapping libraries. The book concludes with a clear demonstration of how to create a real-time data visualization application with Firebase to give you a complete picture of what D3.js makes possible in data visualization today. WHAT YOU WILL LEARN * Discover the full potential of D3.js as an awesome data visualization technology * Learn D3.js application development * Use practical tips and insight from an expert to learn how to design and make an effective interface * Learn how to create custom charts as reusable components to be integrated with existing projects * Create a powerful and high-quality analytics dashboard * Find out how to create custom maps and integrate D3 with third-party mapping libraries * Follow steps to create data-driven applications by integrating D3 with Backbone * Learn how to collaborate with Firebase for real-time data analytics ABOUT THE AUTHOR Pablo Navarro Castillo is a mathematical engineer and developer. He earned his Master's degree in Applied Mathematics from École des Mines de Saint-Etienne in France. After working for a few years in operations research and data analysis, he began to work as a data visualization consultant and developer. In 2014, he founded Masega, which is a data visualization agency based in Santiago, Chile, where he currently works. TABLE OF CONTENTS 1. Data Visualization 2. Reusable Charts 3. Creating Visualizations Without SVG 4. Creating a Color Picker with D3 5. Creating User Interface Elements 6. Interaction Between Charts 7. Creating a Charting Package 8. Data-Driven Applications 9. Creating a Dashboard 10. Creating Maps 11. Creating Advanced Maps 12. Creating a Real-time Application « less
A comprehensive guide for the setup, configuration, and customization of Salesforce CRM
Salesforce CRM is a web-based Customer Relationship Management Service designed to transform your marketing and sales. With this complete guide to implementing the service, administrators of all levels can easily acquire deep knowledge of the platform. Overview * Updated for Spring '13, this book more » covers best practice administration principles, real-world experience, and critical design considerations for setting up and customizing Salesforce CRM * Analyze data within Salesforce by using reports, dashboards, custom reports, and report builder * A step-by-step guide offering clear guidance for the customization and administration of the Salesforce CRM application * Connect users with people and share business information using Salesforce Chatter * Learn to extend the functionality of the Salesforce CRM application through the use of the platform and technologies such as Visualforce * Improve the user experience of users in Salesforce CRM by providing additional functionality using external applications from the AppExchange In Detail Salesforce CRM: The Definitive Admin Handbook is the complete guide to implementing Salesforce CRM. Whether you are looking to enhance the core features or you have already started customizing your Salesforce CRM system and are looking for guidance on advanced features. This book will show you how to get maximum benefit from this exciting product. Salesforce CRM is a market-leading customer relationship management (CRM) application that is accessed over the Internet. The CRM application provides facilities to manage sales projections and orders, marketing plans, business process automation and collaboration, service and support, and data analytics. The application greatly enhances a company’s sales performance, improves team work and collaboration, and provides a robust customer relationship management strategy for an organization. Salesforce CRM: The Definitive Admin Handbook has been updated for the Spring '13 release and gives you all the information you need to administer this powerful CRM application. The book begins with the setup of users and security settings and then progresses to configuration, data management, and data analytics. Finally, the book covers the ways in which the core platform can be further extended and enhanced. What you will learn from this book * Implement mechanisms to manage login access and determine company-specific information * Manage users within Salesforce CRM using features such as granting login access to administrators and enabling delegated user administration * Configure data structures and user interfaces in Salesforce CRM by using various mechanisms offered by Salesforce CRM * Control object and profile permissions to access data records by using permission sets, sharing rules, criteria-based sharing, and also manual sharing * Configure actions for workflow rules and approval processes to automate and streamline the key business process for your organization * Understand the functional areas within Salesforce CRM for campaigns to customers * Learn to administer and configure complex Salesforce CRM functionality with ease « less
Models and Algorithms for Intelligent Data Analysis
This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It covers data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering. It provides a sound mathematical basis, discusses advantages and drawbacks more » of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. The text is designed for undergraduate and graduate courses on data analytics for engineering, computer science, and math students. It is also suitable for practitioners working on data analytics projects. This book has been used for more than ten years in numerous courses at the Technical University of Munich, Germany, in short courses at several other universities, and in tutorials at scientific conferences. Much of the content is based on the results of industrial research and development projects at Siemens. « less