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Author: Prashanth Southekal
Publisher: Technics Publications
ISBN: 9781634628273
Category :
Languages : en
Pages : 208
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Book Description
Deliver enterprise data analytics success by following Prashanth's prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies. Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. 'Analytics Best Practices' is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data. Douglas B. Laney Principal, Data & Analytics Strategy, Caserta, and author of "Infonomics"
Author: Prashanth Southekal
Publisher: Technics Publications
ISBN: 9781634628273
Category :
Languages : en
Pages : 208
Get Book Here
Book Description
Deliver enterprise data analytics success by following Prashanth's prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies. Dr. Southekal proves why he is one of the leading thinkers on data and analytics today. 'Analytics Best Practices' is an indispensable guide for business leaders and those looking to get into the analytics field on the nuances, challenges, and immense opportunities with data. Douglas B. Laney Principal, Data & Analytics Strategy, Caserta, and author of "Infonomics"
Author: Evan Stubbs
Publisher: John Wiley & Sons
ISBN: 1118559444
Category : Business & Economics
Languages : en
Pages : 368
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Book Description
AVOID THE MISTAKES THAT OTHERS MAKE – LEARN WHAT LEADS TO BEST PRACTICE AND KICKSTART SUCCESS This groundbreaking resource provides comprehensive coverage across all aspects of business analytics, presenting proven management guidelines to drive sustainable differentiation. Through a rich set of case studies, author Evan Stubbs reviews solutions and examples to over twenty common problems spanning managing analytics assets and information, leveraging technology, nurturing skills, and defining processes. Delivering Business Analytics also outlines the Data Scientist’s Code, fifteen principles that when followed ensure constant movement towards effective practice. Practical advice is offered for addressing various analytics issues; the advantages and disadvantages of each issue’s solution; and how these solutions can optimally create organizational value. With an emphasis on real-world examples and pragmatic advice throughout, Delivering Business Analytics provides a reference guide on: The economic principles behind how business analytics leads to competitive differentiation The elements which define best practice The Data Scientist’s Code, fifteen management principles that when followed help teams move towards best practice Practical solutions and frequent missteps to twenty-four common problems across people and process, systems and assets, and data and decision-making Drawing on the successes and failures of countless organizations, author Evan Stubbs provides a densely packed practical reference on how to increase the odds of success in designing business analytics systems and managing teams of data scientists. Uncover what constitutes best practice in business analytics and start achieving it with Delivering Business Analytics.
Author: Thomas H. Davenport
Publisher: Pearson Education
ISBN: 0133408701
Category : Business & Economics
Languages : en
Pages : 351
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Book Description
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.
Author: Michael Watson
Publisher: Pearson Education
ISBN: 013340742X
Category : Business & Economics
Languages : en
Pages : 253
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Book Description
Analytics and Big Data Demystified, The up-to-the-minute introduction for every manager, Everything you need to know to get results!, Concepts, applications, tools, techniques, and pitfalls to avoid, How to derive more value from tools and data you already own, Want to start leveraging analytics and Big Data for profit? Managerial Analytics is your ideal first resource. Whatever your industry or management role, this up-to-date guide will help you get started fast, get started right, and quickly start driving value. Book jacket.
Author: Harvard Business Review
Publisher: Harvard Business Press
ISBN: 1633694291
Category : Business & Economics
Languages : en
Pages : 169
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Book Description
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes
Author: Eileen Mcdaniel
Publisher: Createspace Independent Pub
ISBN: 9781480112421
Category : Business & Economics
Languages : en
Pages : 300
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Book Description
The Accidental Analyst: Show Your Data Who's Boss Are you drowning in a sea of data? Would you like to take control of your data and analysis to quickly answer your business questions and make critical decisions? Do you want to confidently present results and solutions to your managers, colleagues and clients? If so, The Accidental Analyst is for you! Although you didn't plan for a career as a data analyst, you're now in a position where you have to analyze data to be successful. Whether you've been working with data for a few years or are just getting started, you can learn how to analyze your data to find answers to real-world questions. Using illustrated examples, we'll walk you through a clear, step-by-step framework that we call The Seven C's of Data Analysis. Read this book for inspiration, ideas and confidence to begin tackling the problems you face at work. Keep it by your desk as a reference on how to organize, analyze and display your data. Don't worry, you can continue to use your favorite spreadsheet or data analysis software—this information is not tied to any particular application. Throughout the book, we also include expert tips, tricks, and shortcuts that took years of analyzing data to discover and understand! Please visit us at www.AccidentalAnalyst.com for articles, our free newsletter and upcoming training events. Quotes This is a wonderful book, filled with practical advice. Business people who are struggling to make sense of their data will find it accessible and directly applicable to their work— a great resource for building analytical prowess. Stephen Few, best-selling author of "Show Me the Numbers" and "Now You See It" Finally, a book that clearly explains the fundamentals of business analytics! I wish that I had this book at the start of my career as a data analyst. Tim Latendress, Financial Analyst This book is an amazing resource for regular business people who want to make sense of their data and take charge of their business! It provides simple yet comprehensive coverage of business analytics. Diego Saenz, President, Petplace and former CIO of Pepsi Latin America Authors Eileen McDaniel, PhD, is Co-Founder and Managing Partner of Freakalytics, LLC, specializing in analytical training and short-term projects that empower people to get the most out of their data and take decisive action to solve problems in their daily work. She is co-author of Rapid Graphs with Tableau Software 7 and the Rapid Dashboards Reference Card, also available as a mobile app, and leads the development of course training materials. Working in both scientific research and business, Eileen realized that business analysts needed a formal, step-by-step method similar to the one scientists use to collect and analyze their data. This inspired her to develop the seven-step framework for data analysis found in The Accidental Analyst. Stephen McDaniel is passionate about helping people understand, present and take action with their data. He is co-author of multiple books and courses including SAS® for Dummies and Rapid Graphs with Tableau Software 7. Stephen has been on the Faculty of The American Marketing Association and The Data Warehouse Institute and is currently Director of Analytic Product Management at Tableau Software and Principal Analyst at Freakalytics, LLC.
Author: Thomas H. Davenport
Publisher: Pearson Education
ISBN: 0133039439
Category : Business & Economics
Languages : en
Pages : 287
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Book Description
"International Institute for Analytics"--Dust jacket.
Author: Randy Bartlett
Publisher: McGraw Hill Professional
ISBN: 0071807608
Category : Business & Economics
Languages : en
Pages : 289
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Book Description
Gain the competitive edge with the smart use of business analytics In today’s volatile business environment, the strategic use of business analytics is more important than ever. A Practitioners Guide to Business Analytics helps you get the organizational commitment you need to get business analytics up and running in your company. It provides solutions for meeting the strategic challenges of applying analytics, such as: Integrating analytics into decision making, corporate culture, and business strategy Leading and organizing analytics within the corporation Applying statistical qualifications, statistical diagnostics, and statistical review Providing effective building blocks to support analytics—statistical software, data collection, and data management Randy Bartlett, Ph.D., is Chief Statistical Officer of the consulting company Blue Sigma Analytics. He currently works with Infosys, where he has helped build their new Business Analytics practice.
Author: Bob Boiko
Publisher: Hartman Communicatie
ISBN: 9490164038
Category : Information resources management
Languages : en
Pages : 323
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Book Description
Author: James Warren
Publisher: Simon and Schuster
ISBN: 1638351104
Category : Computers
Languages : en
Pages : 481
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Book Description
Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth
