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Analytics in Healthcare and the Life Sciences: Strategies, Implementation Methods, and Best Practices

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.

Business Intelligence with MicroStrategy Cookbook

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

"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.

Getting Started with Greenplum for Big Data Analytics

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.

Agile Data Science

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

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.

Digital Analytics Primer

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

Healthcare Analytics for Quality and Performance Improvement

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.

Risk Scoring for a Loan Application on IBM System z: Running IBM SPSS Real-Time Analytics

When ricocheting a solution that involves analytics, the mainframe might not be the first platform that comes to mind. However, the IBM® System z® group has developed some innovative solutions that include the well-respected mainframe benefits. This book describes a workshop that demonstrates the use of real-time advanced analytics for enhancing core banking decisions using a loan origination example. The workshop is a live hands-on experience of the entire process from analytics modeling to deployment of real-time scoring services for use on IBM z/OS®. In this IBM Redbooks® publication, we include a facilitator guide chapter as well as a participant guide chapter. The facilitator guide includes information about the preparation, such as the needed material, resources, and steps to set up and run this workshop. The participant guide shows step-by-step the tasks for a successful learning experience. The goal of the first hands-on exercise is to learn how to use IBM SPSS® Modeler for Analytics modeling. This provides the basis for the next exercise "Configuring risk assessment in SPSS Decision Management". In the third exercise, the participant experiences how real-time scoring can be implemented on a System z. This publication is written for consultants, IT architects, and IT administrators who want to become familiar with SPSS and analytics solutions on the System z.

Killer Analytics: Top 20 Metrics Missing from your Balance Sheet

Learn the secrets to using analytics to grow your business Analytics continues to trend as one of the hottest topics in the business community today. With ever-growing amounts of business data and evolving performance management/business intelligence architectures, how well your business does analyzing its data will differentiate you from your competition. Killer Analytics explores how you can use the muscle of analytics to measure new business elements. Author Mark Brown introduces 20 new metrics that can drive competitive advantage for your business, including social networks, sustainability, culture, innovation, employee satisfaction, and other key business elements. Shows organizations how to use analytics to measure key elements of business performance not traditionally measured Introduces 20 new metrics that drive competitive advantage Reveals how to measure social networking, sustainability, innovation, culture, and more Aside from the science and process of analytics, businesses need to think outside the box in terms of what they are measuring and how new analytical tools can be used to measure business elements such as innovation or sustainability. Opening the doors to a powerful new way of measuring your business, Killer Analytics saves you a small fortune on consultants with dynamic, forward-thinking advice for making the most of every component of your business.

Mondrian in Action

Mondrian in Action teaches business users and developers how to use Mondrian and related tools for strategic business analysis. You'll learn how to design and populate a data warehouse and present the data via a multidimensional model. You'll follow examples showing how to create a Mondrian schema and then expand it to add basic security based on the users' roles. About the Technology Mondrian is an open source, lightning-fast data analysis engine designed to help you explore your business data and perform speed-of-thought analysis. Mondrian can be integrated into a wide variety of business analysis applications and learning it requires no specialized technical knowledge. About the Book Mondrian in Action teaches you to use Mondrian for strategic business analysis. In it, you'll learn how to organize and present data in a multidimensional manner. You'll follow apt and thoroughly explained examples showing how to create a Mondrian schema and then expand it to add basic security based on users' roles. Developers will discover how to integrate Mondrian using its olap4j Java API and web service calls via XML for Analysis. What's Inside Mondrian from the ground up -- no experience required A primer on business analytics Using Mondrian with a variety of leading applications Optimizing and restricting business data for fast, secure analysis About the Reader Written for developers building data analysis solutions. Appropriate for tech-savvy business users and DBAs needing to query and report on data. About the Authors William D. Back is an Enterprise Architect and Director of Pentaho Services. Nicholas Goodman is a Business Intelligence pro who has authored training courses on OLAP and Mondrian. Julian Hyde founded Mondrian and is the project's lead developer. Quotes A wonderful introduction to Business Intelligence and Analytics. - Lorenzo De Leon, Authentify, Inc. A great overview of the Mondrian engine that guided me through all the technical details. - Alexander Helf, veenion GmbH A significant complement to the online documentation, and an excellent introduction to how to think about designing a data warehouse. - Mark Newman, Heads Up Analytics Comprehensive ... highly recommended. - Najib Coutya, IMD Group

Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R

Today, successful firms compete and win based on analytics. Modeling Techniques in brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller’s unique balanced approach combines business context Predictive Analytics and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you’ve identified it, and then how to successfully model that data. You’ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).

Big Data Analytics

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

Adobe® Analytics Quick-Reference Guide: Market Reports and Analytics (formerly SiteCatalyst)

Companies face the challenge of measuring and analyzing the near-overwhelming quantities of data generated from their online businesses and then using that data to gain critical insights into their customersvto drive sales. Adobe Analytics (formerly SiteCatalyst) provides product and content managers, marketers, and analysts with real-time intelligence on customers’online behavior, helps businesses anticipate what their customers will want, personalizes their onlinev experience, and delivers relevant content across web and mobile channels. This quick lookup guide by Adobe Analytics expert Shane Closser uses clear, concise explanations and an easy-to-use format to jump in and start using Adobe’s powerful web analytics tool. You’ll learn the quickest way to: Create metrics Run and set options for reports Measure the effectiveness of marketing campaigns Engage and retain customers Track customers through the conversion funnel Share reports and set up dashboards

Segmentation and Lifetime Value Models Using SAS

Help your organization determine the value of its customer relationships with Segmentation and Lifetime Value Models Using SAS. This book contains a wealth of information that will help you perform analyses to identify your customers and make informed marketing investments. It answers core questions on customer relationship management (CRM), provides an overall framework for thinking about CRM, and offers real-world examples across a variety of industries.

Edward C. Malthouse introduces you to a number of useful models, ranging from simple to more complicated examples, and discusses their applications. You'll learn about segmentation models for identifying groups of customers and about lifetime value models for estimating the future value of the segments. You'll learn how to prepare data and estimate models using Base SAS, SAS/STAT, SAS/IML, and SQL.

Marketing analysts, CRM analysts, database managers, and anyone looking to address the challenges of allocating marketing resources to different customer groups will benefit from the concepts and exercises in this book. Analysts will learn how to approach unique business problems. Managers will gain a sense of what's possible and what to ask of their analytics departments.

This book is part of the SAS Press program.

Numbersense: How to Use Big Data to Your Advantage

How to make simple sense of complex statistics--from the author of Numbers Rule Your World We live in a world of Big Data--and it's getting bigger every day. Virtually every choice we make hinges on how someone generates data . . . and how someone else interprets it--whether we realize it or not. Where do you send your child for the best education? Big Data. Which airline should you choose to ensure a timely arrival? Big Data. Who will you vote for in the next election? Big Data. The problem is, the more data we have, the more difficult it is to interpret it. From world leaders to average citizens, everyone is prone to making critical decisions based on poor data interpretations. In Numbersense, expert statistician Kaiser Fung explains when you should accept the conclusions of the Big Data "experts"--and when you should say, "Wait . . . what?" He delves deeply into a wide range of topics, offering the answers to important questions, such as: How does the college ranking system really work? Can an obesity measure solve America's biggest healthcare crisis? Should you trust current unemployment data issued by the government? How do you improve your fantasy sports team? Should you worry about businesses that track your data? Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there. Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up. Praise for Numbersense " Numbersense correctly puts the emphasis not on the size of big data, but on the analysis of it. Lots of fun stories, plenty of lessons learned—in short, a great way to acquire your own sense of numbers!" Thomas H. Davenport, coauthor of Competing on Analytics and President’s Distinguished Professor of IT and Management, Babson College "Kaiser’s accessible business book will blow your mind like no other. You’ll be smarter, and you won’t even realize it. Buy. It. Now." Avinash Kaushik, Digital Marketing Evangelist, Google, and author, Web Analytics 2.0 "Each story in Numbersense goes deep into what you have to think about before you trust the numbers. Kaiser Fung ably demonstrates that it takes skill and resourcefulness to make the numbers confess their meaning." John Sall, Executive Vice President, SAS Institute "Kaiser Fung breaks the bad news—a ton more data is no panacea—but then has got your back, revealing the pitfalls of analysis with stimulating stories from the front lines of business, politics, health care, government, and education. The remedy isn’t an advanced degree, nor is it common sense. You need Numbersense." Eric Siegel, founder, Predictive Analytics World, and author, Predictive Analytics "I laughed my way through this superb-useful-fun book and learned and relearned a lot. Highly recommended!" Tom Peters, author of In Search of Excellence

Decision Trees for Analytics Using SAS Enterprise Miner

Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes.

An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice.

Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.

This book is part of the SAS Press program.

Applying Analytics

Newcomers to quantitative analysis need practical guidance on how to analyze data in the real world yet most introductory books focus on lengthy derivations and justifications instead of practical techniques. Covering the technical and professional skills needed by analysts in the academic, private, and public sectors, Applying Analytics: A Practical Introduction systematically teaches novices how to apply algorithms to real data and how to recognize potential pitfalls. It offers one of the first textbooks for the emerging first course in analytics. The text concentrates on the interpretation, strengths, and weaknesses of analytical techniques, along with challenges encountered by analysts in their daily work. The author shares various lessons learned from applying analytics in the real world. He supplements the technical material with coverage of professional skills traditionally learned through experience, such as project management, analytic communication, and using analysis to inform decisions. Example data sets used in the text are available for download online so that readers can test their own analytic routines. Suitable for beginning analysts in the sciences, business, engineering, and government, this book provides an accessible, example-driven introduction to the emerging field of analytics. It shows how to interpret data and identify trends across a range of fields.

Practical Web Analytics for User Experience

Practical Web Analytics for User Experience teaches you how to use web analytics to help answer the complicated questions facing UX professionals. Within this book, you'll find a quantitative approach for measuring a website's effectiveness and the methods for posing and answering specific questions about how users navigate a website. The book is organized according to the concerns UX practitioners face. Chapters are devoted to traffic, clickpath, and content use analysis, measuring the effectiveness of design changes, including A/B testing, building user profiles based on search habits, supporting usability test findings with reporting, and more. This is the must-have resource you need to start capitalizing on web analytics and analyze websites effectively. Discover concrete information on how web analytics data support user research and user-centered design Learn how to frame questions in a way that lets you navigate through massive amounts of data to get the answer you need Learn how to gather information for personas, verify behavior found in usability testing, support heuristic evaluation with data, analyze keyword data, and understand how to communicate these findings with business stakeholders

A Framework for Applying Analytics in Healthcare: What Can Be Learned from the Best Practices in Retail, Banking, Politics, and Sports

In A Framework for Applying Analytics in Healthcare, Dwight McNeill shows healthcare analysts and decision-makers exactly how to adapt and apply the best analytics techniques from retail, finance, politics, and sports. McNeill describes each method in depth, presenting numerous case studies that show how these approaches have been deployed and the results that have been achieved. Most important, he explains how these methods can be successfully adapted to the most critical challenges you now face in your healthcare organization. From predictive modeling to social media, this book focuses on innovative techniques with demonstrated effectiveness and direct relevance to healthcare. You’ll discover powerful new ways to manage population health; improve patient activation, support, and experience of care; focus on health outcomes; measure what matters for team performance; make information more actionable; and build more customer-centric organizations.