"SAP HANA Cookbook" is a hands-on guide to learning SAP HANA, a powerful in-memory database platform. Through over 50 practical recipes, you'll understand the inner workings of SAP HANA's architecture, and learn techniques to optimize operations and analytics. What this Book will help me do Understand SAP HANA's architecture and in-memory capabilities. Effectively load and integrate data from various source systems. Develop and optimize SAP HANA models such as attribute, analytical, and calculation views. Gain proficiency in using the SAP HANA SQL scripting language. Master user and role management for secure and efficient SAP HANA operation. Author(s) This book is authored by industry specialists with extensive experience in SAP HANA technology. Drawing from real-world projects, the authors provide nuanced insights and practical guidance, enabling readers to implement SAP HANA solutions effectively. Who is it for? This book is suited for solution architects, developers, and managers seeking to develop expertise in SAP HANA. Whether you are new to SAP technologies or looking to deepen your skillset, this resource provides comprehensive and actionable guidance.

Tired of boring spreadsheets and data overload from confusing graphs? Master the art of visualization with Rapid Graphs with Tableau 8! Tableau insiders Stephen and Eileen McDaniel expertly provide a hands-on case study approach and more than 225 illustrations that will teach you how to quickly explore and understand your data to make informed decisions in a wide variety of real-world situations. Rapid Graphs with Tableau 8 includes best practices of visual analytics for ideas on how to communicate your findings with audience-friendly graphs, tables and maps. "A picture is worth a thousand words" is a common saying that is more relevant today than ever as data volumes grow and the need for easy access to answers becomes more critical. This book covers the core of Tableau capabilities in easy-to-follow examples, updated and expanded for Version 8. Learn how to be successful with Tableau from the team that started the original training program as the founding Tableau Education Partner! "A must read for anyone interested in Tableau. Clear explanations, practical advice and beautiful examples!" Elissa Fink – Chief Marketing Officer, Tableau Software What you'll learn Connect to and review data visually Create insightful maps and take advantage of view shifting Understand the types of views available in Tableau Take advantage of the powerful Marks card and much more Who this book is for Rapid Graphs with Tableau 8 is a great resource for those new to Tableau, and also contains useful tips and tricks for advanced users as well.

This book explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making capabilities of an organization. Covering the key areas of business analytics, the book explores the concepts, techniques, applications, and emerging trends that professionals across a wide range of industries need to be aware of. It also examines legal and privacy issues and explores social media in analytics. With this book, readers can develop the understanding required to use Big Data and high-performance computing in complex environments to improve strategic decision making.

Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on “Big Data” have been little more than business polemics or product catalogs. is different: It’s a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist. Data Just Right Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that’s where you can derive the most value. Manoochehri shows how to address each of today’s key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You’ll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today’s leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Coverage includes Mastering the four guiding principles of Big Data success—and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically “Building for infinity” to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. COVERAGE INCLUDES • Exploring R, RStudio, and R packages • Using R for math: variable types, vectors, calling functions, and more • Exploiting data structures, including data.frames, matrices, and lists • Creating attractive, intuitive statistical graphics • Writing user-defined functions • Controlling program flow with if, ifelse, and complex checks • Improving program efficiency with group manipulations • Combining and reshaping multiple datasets • Manipulating strings using R’s facilities and regular expressions • Creating normal, binomial, and Poisson probability distributions • Programming basic statistics: mean, standard deviation, and t-tests • Building linear, generalized linear, and nonlinear models • Assessing the quality of models and variable selection • Preventing overfitting, using the Elastic Net and Bayesian methods • Analyzing univariate and multivariate time series data • Grouping data via K-means and hierarchical clustering • Preparing reports, slideshows, and web pages with knitr • Building reusable R packages with devtools and Rcpp • Getting involved with the R global community

Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits. Big Data Application Architecture Pattern Recipes answers one of the most critical questions of this time 'how do you select the best end-to-end architecture to solve your big data problem?'. The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution, trying to extract insight from huge volumes of data in real-time and across multiple relational and non-relational data types for clients from industries like retail, telecommunication, banking, and insurance. The patterns in this book provide the strong architectural foundation required to launch your next big data application. The architectures for realizing these opportunities are based on relatively less expensive and heterogeneous infrastructures compared to the traditional monolithic and hugely expensive options that exist currently. This book describes and evaluates the benefits of heterogeneity which brings with it multiple options of solving the same problem, evaluation of trade-offs and validation of 'fitness-for-purpose' of the solution. What you'll learn Major considerations in building a big data solution Big data application architectures problems for specific industries What are the components one needs to build and end-to-end big data solution? Does one really need a real-time big data solution or an off-line analytics batch solution? What are the operations and support architectures for a big data solution? What are the scalability considerations, and options for a Hadoop installation? Who this book is for CIOs, CTOs, enterprise architects, and software architects Consultants, solution architects, and information management (IM) analysts who want to architect a big data solution for their enterprise

Make healthcare analytics work: leverage its powerful opportunities for improving outcomes, cost, and efficiency.This book gives you thepractical frameworks, strategies, tactics, and case studies you need to go beyond talk to action. The contributing healthcare analytics innovators survey the field’s current state, present start-to-finish guidance for planning and implementation, and help decision-makers prepare for tomorrow’s advances. They present in-depth case studies revealing how leading organizations have organized and executed analytic strategies that work, and fully cover the primary applications of analytics in all three sectors of the healthcare ecosystem: Provider, Payer, and Life Sciences. Co-published with the International Institute for Analytics (IIA), this book features the combined expertise of IIA’s team of leading health analytics practitioners and researchers. Each chapter is written by a member of the IIA faculty, and bridges the latest research findings with proven best practices. This book will be valuable to professionals and decision-makers throughout the healthcare ecosystem, including provider organization clinicians and managers; life sciences researchers and practitioners; and informaticists, actuaries, and managers at payer organizations. It will also be valuable in diverse analytics, operations, and IT courses in business, engineering, and healthcare certificate programs.

Best practices and step-by-step instructions for using the Tableau Software toolset Although the Tableau Desktop interface is relatively intuitive, this book goes beyond the simple mechanics of the interface to show best practices for creating effective visualizations for specific business intelligence objectives. It illustrates little-known features and techniques for getting the most from the Tableau toolset, supporting the needs of the business analysts who use the product as well as the data and IT managers who support it. This comprehensive guide covers the core feature set for data analytics, illustrating best practices for creating and sharing specific types of dynamic data visualizations. Featuring a helpful full-color layout, the book covers analyzing data with Tableau Desktop, sharing information with Tableau Server, understanding Tableau functions and calculations, and Use Cases for Tableau Software. Includes little-known, as well as more advanced features and techniques, using detailed, real-world case studies that the author has developed as part of his consulting and training practice Explains why and how Tableau differs from traditional business information analysis tools Shows you how to deploy dashboards and visualizations throughout the enterprise Provides a detailed reference resource that is aimed at users of all skill levels Depicts ways to leverage Tableau across the value chain in the enterprise through case studies that target common business requirements Endorsed by Tableau Software Tableau Your Data shows you how to build dynamic, best-of-breed visualizations using the Tableau Software toolset.

Revised to cover new advances in business intelligence—big data, cloud, mobile, and more—this fully updated bestseller reveals the latest techniques to exploit BI for the highest ROI. “Cindi has created, with her typical attention to details that matter, a contemporary forward-looking guide that organizations could use to evaluate existing or create a foundation for evolving business intelligence / analytics programs. The book touches on strategy, value, people, process, and technology, all of which must be considered for program success. Among other topics, the data, data warehousing, and ROI comments were spot on. The ‘technobabble’ chapter was brilliant!” — Bill Frank, Business Intelligence and Data Warehousing Program Manager, Johnson & Johnson “If you want to be an analytical competitor, you’ve got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It’s required reading for quantitatively oriented strategists and the technologists who support them.” — Thomas H. Davenport, President’s Distinguished Professor, Babson College and co-author, Competing on Analytics “Cindi has created an exceptional, authoritative description of the end-to-end business intelligence ecosystem. This is a great read for those who are just trying to better understand the business intelligence space, as well as for the seasoned BI practitioner.” — Sully McConnell, Vice President, Business Intelligence and Information Management, Time Warner Cable “Cindi’s book succinctly yet completely lays out what it takes to deliver BI successfully. IT and business leaders will benefit from Cindi’s deep BI experience, which she shares through helpful, real-world definitions, frameworks, examples, and stories. This is a must-read for companies engaged in – or considering – BI.” — Barbara Wixom, PhD, Principal Research Scientist, MIT Sloan Center for Information Systems Research Expanded to cover the latest advances in business intelligence such as big data, cloud, mobile, visual data discovery, and in-memory computing, this fully updated bestseller by BI guru Cindi Howson provides cutting-edge techniques to exploit BI for maximum value. Successful Business Intelligence: Unlock the Value of BI & Big Data, Second Edition describes best practices for an effective BI strategy. Find out how to: Garner executive support to foster an analytic culture Align the BI strategy with business goals Develop an analytic ecosystem to exploit data warehousing, analytic appliances, and Hadoop for the right BI workload Continuously improve the quality, breadth, and timeliness of data Find the relevance of BI for everyone in the company Use agile development processes to deliver BI capabilities and improvements at the pace of business change Select the right BI tools to meet user and business needs Measure success in multiple ways Embrace innovation, promote successes and applications, and invest in training Monitor your evolution and maturity across various factors for impact Exclusive industry survey data and real-world case studies from Medtronic, Macy’s, 1-800 CONTACTS, The Dow Chemical Company, Netflix, Constant Contact, and other companies show successful BI initiatives in action. From Moneyball to Nate Silver, BI and big data have permeated our cultural, political, and economic landscape. This timely, up-to-date guide reveals how to plan and deploy an agile, state-of-the-art BI solution that links insight to action and delivers a sustained competitive advantage.

IBM® Informix® Warehouse Accelerator is a state-of-the-art in-memory database that uses affordable innovations in memory and processor technology and trends in novel ways to boost query performance. It is a disruptive technology that changes how organizations provide analytics to its operational and historical data. Informix Warehouse Accelerator uses columnar, in-memory approach to accelerate even the most complex warehouse and operational queries without application changes or tuning. This IBM Redbooks® publication provides a comprehensive look at the technology and architecture behind the system. It contains information about the tools, data synchronization, and query processing capabilities of Informix Warehouse Accelerator, and provides steps to implement data analysis by using Informix Warehouse Accelerator within an organization. This book is intended for IBM Business Partners and clients who are looking for low-cost solutions to boost data warehouse query performance.

This comprehensive guide introduces you to the functionalities of MicroStrategy for business intelligence, empowering you to build dashboards, reports, and visualizations using hands-on, practical recipes with clear examples. You'll learn how to use MicroStrategy for the entire BI lifecycle, making data actionable and insights accessible. What this Book will help me do Install and configure the MicroStrategy platform, including setting up a fully operational BI environment. Create interactive dashboards and web reports to visualize and analyze data effectively. Learn to use MicroStrategy on mobile devices, enabling access to data-driven insights anywhere. Discover advanced analytics techniques using Visual Insight and MicroStrategy Cloud Express. Master practical skills with real-life examples to implement robust BI solutions. Author(s) Davide Moraschi, an experienced professional in business intelligence and data analytics, brings his expertise to guiding readers through the MicroStrategy platform. He has years of experience implementing and developing BI solutions in diverse industries, offering practical perspectives. Davide's approachable teaching style and clear examples make technical concepts accessible and engaging. Who is it for? This book is tailored for BI developers and data analysts who want to deepen their expertise in MicroStrategy. It's also suitable for IT professionals and business users aiming to leverage MicroStrategy for data insights. Some existing knowledge of BI concepts, such as dimensional modeling, will enrich your learning experience. You need no prior experience with MicroStrategy to benefit from this book.

"IBM SPSS Modeler Cookbook" is your practical guide to mastering data mining with IBM SPSS Modeler. This comprehensive book takes you beyond the basics, offering expert insights, time-saving techniques, and powerful workflows to grow your skills and elevate your analytical abilities. You will learn to apply the CRISP-DM methodology, efficiently prepare and explore data, build advanced models, and confidently incorporate analytical results into your business decisions. What this Book will help me do Effectively apply the CRISP-DM standard process to organize your data mining projects. Leverage efficient techniques for data extraction, transformation, and preparation. Develop and evaluate predictive models for practical applications in your organization. Enhance your models by utilizing advanced features and expert tips. Automate and streamline your data mining process with scripting for ultimate control. Author(s) Keith McCormick and None Abbott are seasoned data mining professionals with deep expertise in IBM SPSS Modeler and predictive analytics. Together, they have extensive experience in consulting, training, and applying advanced analytical techniques across industries. Through their approachable and insightful writing style, they share practical knowledge and expert workflows to empower readers. Who is it for? This book is designed for individuals who have basic experience with IBM SPSS Modeler and aspire to deepen their expertise. Whether you are a data analyst looking to advance your analytical capabilities or a professional aiming to integrate data-driven solutions into your organization, this book provides the knowledge and practical guidance you need to take the next step in your data mining journey.

Continuing its commitment to developing and delivering industry-leading storage technologies, IBM is introducing the IBM Real-time Compression Appliances for NAS, an innovative new storage offering that delivers essential storage efficiency technologies, combined with exceptional ease of use and performance. In an era when the amount of information, particularly in unstructured files, is exploding, but budgets for storing that information are stagnant, IBM Real-time Compression technology offers a powerful tool for better information management, protection, and access. IBM Real-time Compression can help slow the growth of storage acquisition, reducing storage costs while simplifying both operations and management. It also enables organizations to keep more data available for use rather than storing it offsite or on harder-to-access tape, so they can support improved analytics and decision making. IBM Real-time Compression Appliances provide on-line storage optimization through real-time data compression, delivering dramatic cost reduction without performance degradation. This IBM® Redbooks® publication is an easy-to-follow guide that describes how to design solutions successfully using IBM Real-time Compression Appliances (IBM RTCAs). It provides practical installation examples, ease of use, remote management, high availability, and administration techniques. Furthermore, it explains best practices for RTCA solution design, application integration, and practical RTCA use cases.

This book serves as a thorough introduction to using the Greenplum platform for big data analytics. It explores key concepts for processing, analyzing, and deriving insights from big data using Greenplum, covering aspects from data integration to advanced analytics techniques like programming with R and MADlib. What this Book will help me do Understand the architecture and core components of the Greenplum platform. Learn how to design and execute data science projects using Greenplum. Master loading, processing, and querying big data in Greenplum efficiently. Explore programming with R and integrating it with Greenplum for analytics. Gain skills in high-availability configurations, backups, and recovery within Greenplum. Author(s) Sunila Gollapudi is a seasoned expert in the field of big data analytics and has multiple years of experience working with platforms like Greenplum. Her real-world problem-solving expertise shapes her practical and approachable writing style, making this book not only educational but enjoyable to read. Who is it for? This book is ideal for data scientists or analysts aiming to explore the capabilities of big data platforms like Greenplum. It suits readers with basic knowledge of data warehousing, programming, and analytics tools who want to deepen their expertise and effectively harness Greenplum for analytics.

Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop. Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps. Create analytics applications by using the agile big data development methodology Build value from your data in a series of agile sprints, using the data-value stack Gain insight by using several data structures to extract multiple features from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future, and translate predictions into action Get feedback from users after each sprint to keep your project on track

KNIME Essentials is a comprehensive guide to mastering KNIME, an open-source data analytics platform. Through this book, you'll discover how to process, visualize, and report on data effectively. Whether you're new to KNIME or data analytics in general, this resource is designed to equip you with the skills needed to handle data challenges confidently. What this Book will help me do Understand how to install and set up KNIME for data analysis tasks. Learn to create workflows to efficiently process data. Explore methods for importing and pre-processing data from various sources. Master techniques for visualizing and analyzing processed data. Generate professional-grade reports based on your data visualizations. Author(s) Gábor Bakos, the author of KNIME Essentials, leverages his expertise in data analytics and software tools to provide readers with a practical guide to mastering KNIME. With years of experience in working with analytics platforms, he crafts content that is accessible and focused on delivering real-world results. His user-focused approach helps readers quickly grasp complex concepts. Who is it for? This book is ideal for data analysts and professionals seeking to enhance their data processing skills with KNIME. No prior knowledge of KNIME is expected, but a foundational understanding of data analytics concepts would be beneficial. If you're looking to produce insightful analytics and reports efficiently, this guide is tailored for you.

Learn the concepts and methods for creating economic and business value with digital analytics, mobile analytics, web analytics, and market research and social media data. In , pioneering expert Judah Phillips introduces the concepts, terms, and methods that comprise the science and art of digital analysis for web, site, social, video, and other types of quantitative and qualitative data. Business readers—from new practitioners to experienced executives—who want to understand how digital analytics can be used to reduce costs and increase profitable revenue throughout the business should read this book. Phillips delivers a comprehensive review of the core concepts, vocabulary, and frameworks, including analytical methods and tools that can help you successfully integrate analytical processes, technology, and people into all aspects of business operations. This unbiased and product-independent primer draws from the author's extensive experience doing and managing analytics in this field. Digital Analytics Primer

UPGRADE TO THE NEW GENERATION OF DATABASE SOFTWARE FOR THE ERA OF BIG DATA! If big data is an untapped natural resource, how do you find the gold hidden within? Leaders realize that big data means all data, and are moving quickly to extract more value from both structured and unstructured application data. However, analyzing this data can prove costly and complex, especially while protecting the availability, performance and reliability of essential business applications. In the new era of big data, businesses require data systems that can blend always-available transactions with speed-of-thought analytics. DB2 10.5 with BLU Acceleration provides this speed, simplicity, and affordability while making it easier to build next-generation applications with NoSQL features, such as a mongo-styled JSON document store, a graph store, and more. Dynamic in-memory columnar processing and other innovations deliver faster insights from more data, and enhanced pureScale clustering technology delivers high-availability transactions with application-transparent scalability for business continuity. With this book, you'll learn about the power and flexibility of multiworkload, multi-platform database software. Use the comprehensive knowledge from a team of DB2 developers and experts to get started with the latest DB2 trial version you can download at ibm.com/developerworks/downloads/im/db2/. Stay up to date on DB2 by visiting ibm.com/db2/.

Improve patient outcomes, lower costs, reduce fraud—all with healthcare analytics Healthcare Analytics for Quality and Performance Improvement walks your healthcare organization from relying on generic reports and dashboards to developing powerful analytic applications that drive effective decision-making throughout your organization. Renowned healthcare analytics leader Trevor Strome reveals in this groundbreaking volume the true potential of analytics to harness the vast amounts of data being generated in order to improve the decision-making ability of healthcare managers and improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: to leverage advances in both clinical and information technology to improve quality and performance while containing costs Explores the tools and techniques to analyze and extract value from healthcare data Demonstrates how the clinical, business, and technology components of healthcare organizations (HCOs) must work together to leverage analytics Other industries are already taking advantage of big data. Healthcare Analytics for Quality and Performance Improvement helps the healthcare industry make the most of the precious data already at its fingertips for long-overdue quality and performance improvement.

Transform Big Data into Insight "In this book, some of Oracle's best engineers and architects explain how you can make use of big data. They'll tell you how you can integrate your existing Oracle solutions with big data systems, using each where appropriate and moving data between them as needed." -- Doug Cutting, co-creator of Apache Hadoop Cowritten by members of Oracle's big data team, Oracle Big Data Handbook provides complete coverage of Oracle's comprehensive, integrated set of products for acquiring, organizing, analyzing, and leveraging unstructured data. The book discusses the strategies and technologies essential for a successful big data implementation, including Apache Hadoop, Oracle Big Data Appliance, Oracle Big Data Connectors, Oracle NoSQL Database, Oracle Endeca, Oracle Advanced Analytics, and Oracle's open source R offerings. Best practices for migrating from legacy systems and integrating existing data warehousing and analytics solutions into an enterprise big data infrastructure are also included in this Oracle Press guide. Understand the value of a comprehensive big data strategy Maximize the distributed processing power of the Apache Hadoop platform Discover the advantages of using Oracle Big Data Appliance as an engineered system for Hadoop and Oracle NoSQL Database Configure, deploy, and monitor Hadoop and Oracle NoSQL Database using Oracle Big Data Appliance Integrate your existing data warehousing and analytics infrastructure into a big data architecture Share data among Hadoop and relational databases using Oracle Big Data Connectors Understand how Oracle NoSQL Database integrates into the Oracle Big Data architecture Deliver faster time to value using in-database analytics Analyze data with Oracle Advanced Analytics (Oracle R Enterprise and Oracle Data Mining), Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop Analyze disparate data with Oracle Endeca Information Discovery Plan and implement a big data governance strategy and develop an architecture and roadmap