Business Analytics with Management Science Models and Methods PDF Download

Author: Arben Asllani
Publisher: Pearson Education
ISBN: 0133760359
Category : Business & Economics
Languages : en
Pages : 401

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Book Description
This book is about prescriptive analytics. It provides business practitioners and students with a selected set of management science and optimization techniques and discusses the fundamental concepts, methods, and models needed to understand and implement these techniques in the era of Big Data. A large number of management science models exist in the body of literature today. These models include optimization techniques or heuristics, static or dynamic programming, and deterministic or stochastic modeling. The topics selected in this book, mathematical programming and simulation modeling, are believed to be among the most popular management science tools, as they can be used to solve a majority of business optimization problems. Over the years, these techniques have become the weapon of choice for decision makers and practitioners when dealing with complex business systems.

Author: Iiba
Publisher:
ISBN: 9781927584200
Category : Computers
Languages : en
Pages : 172

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Book Description
The Guide to Business Data Analytics provides a foundational understanding of business data analytics concepts and includes how to develop a framework; key techniques and application; how to identify, communicate and integrate results; and more. This guide acts as a reference for the practice of business data analytics and is a companion resource for the Certification in Business Data Analytics (IIBA(R)- CBDA). Explore more information about the Certification in Business Data Analytics at IIBA.org/CBDA. About International Institute of Business Analysis International Institute of Business Analysis(TM) (IIBA(R)) is a professional association dedicated to supporting business analysis professionals deliver better business outcomes. IIBA connects almost 30,000 Members, over 100 Chapters, and more than 500 training, academic, and corporate partners around the world. As the global voice of the business analysis community, IIBA supports recognition of the profession, networking and community engagement, standards and resource development, and comprehensive certification programs. IIBA Publications IIBA publications offer a wide variety of knowledge and insights into the profession and practice of business analysis for the entire business community. Standards such as A Guide to the Business Analysis Body of Knowledge(R) (BABOK(R) Guide), the Agile Extension to the BABOK(R) Guide, and the Global Business Analysis Core Standard represent the most commonly accepted practices of business analysis around the globe. IIBA's reports, research, whitepapers, and studies provide guidance and best practices information to address the practice of business analysis beyond the global standards and explore new and evolving areas of practice to deliver better business outcomes. Learn more at iiba.org.

Author: Rajan? Gupta
Publisher:
ISBN: 9781099250507
Category :
Languages : en
Pages : 237

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Book Description
The purpose of this book is to provide information related to the "Certified Analytics Professional (CAP)" and "Associate Certified Analytics Professional (aCAP)" exam conducted by INFORMS, USA. The information has been compiled from various sources available on the INFORMS website and other allied web sources. This book on CAP and aCAP exam preparation cover three major aspects related to the certification. Firstly, the information and history related to the CAP exam are given in the book. Secondly, the exam pattern, topic coverage, study time and various resources have been given with respect to the preparation of the CAP exam. Thirdly, 250 practice questions have been given in this book with solutions. These questions have been mapped with the CAP exam pattern under various domains.The objective of this book is to make aspirants aware of the pattern of the CAP exam; To give the aspirants an idea about topic coverage in the CAP exam; To give the aspirants an idea about pattern of question & options in CAP exam; Not to share the exact questions that appear in CAP exam; Not to claim that performing well in the practice questions will guarantee passing of the CAP exam.The solutions given in this book are correct as per the experts. Reader's opinion may vary with those of experts. The material in this book is only an indication towards actual CAP test preparation and may not be related to actual questions or their solutions. Since the aspirant has to opt for the MOST appropriate choice of answer, so a lot of subjectivity is there. A question may have all the correct options, but aspirant will have to choose the BEST from the given options.This book covers up 250 questions with answers (and explanation) on the format of CAP exam as per the CAP handbook guidelines. It gives a detailed analysis of the responses along with the detailed list of topics to be studied for CAP exam preparation. A week-wise study plan for 16-20 weeks has been given to help the aspirants prepare for the exam. Moreover, a list of online and offline resources has been given in the book to prepare for the CAP exam, along with the topic list and glossary of important topics.

Author: Gary Cokins
Publisher: John Wiley & Sons
ISBN: 0470471190
Category : Business & Economics
Languages : en
Pages : 336

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Book Description
Praise for Praise for Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics "A highly accessible collection of essays on contemporary thinking in performance management. Readers will get excellent overviews on the Balanced Scorecard, strategy maps, incentives, management accounting, activity-based costing, customer lifetime value, and sustainable shareholder value creation." —Robert S. Kaplan, Harvard Business School; coauthor of The Balanced Scorecard: Translating Strategy into Action, The Execution Premium, and many other books "Gary Cokins demonstrates in this book that performance management is not a mysterious black art, but a structured, process-oriented discipline. If you want your performance management system to be a smoothly running analytical machine, read and apply the ideas in this book—it's all you need." —Thomas H. Davenport, President's Distinguished Professor of Information Technology and Management, Babson College; coauthor of Competing on Analytics: The New Science of Winning "Drawing on a deep reservoir of knowledge and experience gained from hundreds of customer engagements around the world, Gary Cokins offers an authoritative examination of the major dimensions of performance management. Cokins not only paints a rich and textured view of the major principles and concepts driving performance management implementations, he offers a nuanced look at the important subtleties that can spell the difference between success and failure. This is an informative and enjoyable text to read!" —Wayne Eckerson, Director of Research, The Data Warehouse Institute (TDWI); author of Performance Dashboards: Measuring, Monitoring, and Managing Your Business "[In this] very insightful book, the view of an integrated performance management framework with a goal to link various operational activities with business strategy is an excellent approach to manage and improve business. Gary's explanation of risk-based performance management, for providing the capability to achieve long-term objectives with reliably calculated risks, is definitely thought provoking." —Srini Pallia, Global Head and Vice President of Business Technology Services, Wipro Technologies, Bangalore, India "Gary Cokins is clearly one of the world's thought leaders in the area of performance management, and the need for integrated performance management, improvement and execution is clearly at a premium in these challenging economic times. This book is a must read for CEOs, CFOs, and management accountants around the globe seeking higher levels of sustainable business performance for their stakeholders." —Jeffrey C. Thomson, President and CEO, Institute of Management Accountants

Author: Bhimasankaram Pochiraju
Publisher: Springer
ISBN: 3319688375
Category : Business & Economics
Languages : en
Pages : 971

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Book Description
This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters. The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text. Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter.

Author: Harjit Singh
Publisher: FT Press
ISBN: 0134190491
Category : Business & Economics
Languages : en
Pages : 412

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Book Description
To manage projects, you must not only control schedules and costs: you must also manage growing operational uncertainty. Today’s powerful analytics tools and methods can help you do all of this far more successfully. In Project Management Analytics, Harjit Singh shows how to bring greater evidence-based clarity and rationality to all your key decisions throughout the full project lifecycle. Singh identifies the components and characteristics of a good project decision and shows how to improve decisions by using predictive, prescriptive, statistical, and other methods. You’ll learn how to mitigate risks by identifying meaningful historical patterns and trends; optimize allocation and use of scarce resources within project constraints; automate data-driven decision-making processes based on huge data sets; and effectively handle multiple interrelated decision criteria. Singh also helps you integrate analytics into the project management methods you already use, combining today’s best analytical techniques with proven approaches such as PMI PMBOK® and Lean Six Sigma. Project managers can no longer rely on vague impressions or seat-of-the-pants intuition. Fortunately, you don’t have to. With Project Management Analytics, you can use facts, evidence, and knowledge—and get far better results. Achieve efficient, reliable, consistent, and fact-based project decision-making Systematically bring data and objective analysis to key project decisions Avoid “garbage in, garbage out” Properly collect, store, analyze, and interpret your project-related data Optimize multi-criteria decisions in large group environments Use the Analytic Hierarchy Process (AHP) to improve complex real-world decisions Streamline projects the way you streamline other business processes Leverage data-driven Lean Six Sigma to manage projects more effectively

Author: Kristin Briney
Publisher: Pelagic Publishing Ltd
ISBN: 178427013X
Category : Computers
Languages : en
Pages : 312

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Book Description
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin

Author: Gaurav Aroraa
Publisher: BPB Publications
ISBN: 9388511956
Category : Antiques & Collectibles
Languages : en
Pages : 481

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Book Description
A Complete Data Analytics Guide for Learners and Professionals. KEY FEATURES ● Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database. ● Dive into Machine Learning, its tools, and applications. ● Coverage of applications of Big Data, Data Analysis, and Business Intelligence. DESCRIPTION These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science. WHAT YOU WILL LEARN ● Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. ● Learn to manage data warehousing with real time transaction processing. ● Explore various machine learning techniques that apply to data analytics. ● Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry. ● Acquaint yourself with Big Data tools and statistical techniques for machine learning. WHO THIS BOOK IS FOR IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book. TABLE OF CONTENTS 1. Database Management System 2. Online Transaction Processing and Data Warehouse 3. Business Intelligence and its deeper dynamics 4. Introduction to Data Visualization 5. Advanced Data Visualization 6. Introduction to Big Data and Hadoop 7. Application of Big Data Real Use Cases 8. Application of Big Data 9. Introduction to Machine Learning 10. Advanced Concepts to Machine Learning 11. Application of Machine Learning

Author: Steven Bennett
Publisher: McGraw Hill Professional
ISBN: 1260463931
Category : Computers
Languages : en
Pages : 401

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Book Description
100% coverage of every objective for the EC-Council’s Certified Chief Information Security Officer exam Take the challenging CCISO exam with confidence using the comprehensive information contained in this effective study guide. CCISO Certified Chief Information Security Officer All-in-One Exam Guide provides 100% coverage of all five CCISO domains. Each domain is presented with information mapped to the 2019 CCISO Blueprint containing the exam objectives as defined by the CCISO governing body, the EC-Council. For each domain, the information presented includes: background information; technical information explaining the core concepts; peripheral information intended to support a broader understating of the domain; stories, discussions, anecdotes, and examples providing real-world context to the information. • Online content includes 300 practice questions in the customizable Total Tester exam engine • Covers all exam objectives in the 2019 EC-Council CCISO Blueprint • Written by information security experts and experienced CISOs

Author: Christopher Greco
Publisher: Mercury Learning and Information
ISBN: 1683926463
Category : Computers
Languages : en
Pages : 220

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Book Description
Data analytics is creeping into the lexicon of our daily language. This book gives the reader a perspective as to the overall data analytics skill set, starting with a primer on statistics, and works toward the application of those methods. There are a variety of formulas and algorithms used in the data analytics process. These formulas can be plugged into whatever software application the reader uses to obtain the answer they need. There are several demonstrations of this process to provide straightforward instruction as to how to bring data analytics skills to your critical thinking. This book presents a variety of methods and techniques, as well as case studies, to enrich the knowledge of data analytics for project managers, systems engineers, and cybersecurity professionals. It separates the case studies so that each profession can practice some straightforward data analytics specific to their fields. The main purpose of this text is to refresh the statistical knowledge necessary to build models for data analytics. Along with that, this book encompasses the analytics thinking that is essential to all three professions. FEATURES: Provides straightforward instruction on data analytics methods Includes methods, techniques, and case studies for project managers, systems engineers, and cybersecurity professionals Refreshes the statistical knowledge needed to bring data analytics into your skillset and decision-making Focuses on getting readers up to speed quickly and efficiently to be able to see the impact of data analytics and analytical thinking