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Author: Michael S. Gendron
Publisher: John Wiley & Sons
ISBN: 1118478312
Category : Business & Economics
Languages : en
Pages : 175
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Book Description
Expert guidance for building an information communication and technology infrastructure that provides best in business intelligence Enterprise performance management (EPM) technology has been rapidly advancing, especially in the areas of predictive analysis and cloud-based solutions. Business intelligence caught on as a concept in the business world as the business strategy application of data warehousing in the early 2000s. With the recent surge in interest in data analytics and big data, it has seen a renewed level of interest as the ability of a business to find the valuable data in a timely—and competitive—fashion. Business Intelligence Applied reveals essential information for building an optimal and effective information and communication technology (ICT) infrastructure. Defines ICT infrastructure Examines best practices for documenting business change and for documenting technology recommendations Includes examples and cases from Europe and Asia Written for business intelligence staff, CIOs, CTOs, and technology managers With examples and cases from Europe and Asia, Business Intelligence Applied expertly covers business intelligence, a hot topic in business today as a key element to business and data analytics.
Author: Michael S. Gendron
Publisher: John Wiley & Sons
ISBN: 1118478312
Category : Business & Economics
Languages : en
Pages : 175
Get Book
Book Description
Expert guidance for building an information communication and technology infrastructure that provides best in business intelligence Enterprise performance management (EPM) technology has been rapidly advancing, especially in the areas of predictive analysis and cloud-based solutions. Business intelligence caught on as a concept in the business world as the business strategy application of data warehousing in the early 2000s. With the recent surge in interest in data analytics and big data, it has seen a renewed level of interest as the ability of a business to find the valuable data in a timely—and competitive—fashion. Business Intelligence Applied reveals essential information for building an optimal and effective information and communication technology (ICT) infrastructure. Defines ICT infrastructure Examines best practices for documenting business change and for documenting technology recommendations Includes examples and cases from Europe and Asia Written for business intelligence staff, CIOs, CTOs, and technology managers With examples and cases from Europe and Asia, Business Intelligence Applied expertly covers business intelligence, a hot topic in business today as a key element to business and data analytics.
Author: Rimvydas Skyrius
Publisher: Springer Nature
ISBN: 3030670325
Category : Computers
Languages : en
Pages : 281
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Book Description
This book examines the managerial dimensions of business intelligence (BI) systems. It develops a set of guidelines for value creation by implementing business intelligence systems and technologies. In particular the book looks at BI as a process – driven by a mix of human and technological capabilities – to serve complex information needs in building insights and providing aid in decision making. After an introduction to the key concepts of BI and neighboring areas of information processing, the book looks at the complexity and multidimensionality of BI. It tackles both data integration and information integration issues. Bodies of knowledge and other widely accepted collections of experience are presented and turned into lessons learned. Following a straightforward introduction to the processes and technologies of BI the book embarks on BI maturity and agility, the components, drivers and inhibitors of BI culture and soft BI factors like attention, sense and trust. Eventually the book attempts to provide a holistic view on business intelligence, possible structures and tradeoffs and embarks to provide an outlook on possible developments in BI and analytics.
Author: Herschel, Richard T.
Publisher: IGI Global
ISBN: 1466602805
Category : Business & Economics
Languages : en
Pages : 348
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Book Description
"This book offers a deep look into the latest research, tools, implementations, frameworks, architectures, and case studies within the field of Business Intelligence Management"--Provided by publisher.
Author: Jerzy Surma
Publisher: Business Expert Press
ISBN: 9781606491867
Category : Business & Economics
Languages : en
Pages : 150
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Book Description
This book is about using business intelligence as a management information system for supporting managerial decision making. It concentrates primarily on practical business issues and demonstrates how to apply data warehousing and data analytics to support business decision making. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. All examples are based on the most recent achievements in business intelligence. Finally this book outlines an overview of a methodology that takes into account the complexity of developing applications in an integrated business intelligence environment. This book is written for managers, business consultants, and undergraduate and postgraduates students in business administration.
Author: Nathaniel Lin
Publisher: Pearson Education
ISBN: 0133481506
Category : Business & Economics
Languages : en
Pages : 321
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Book Description
Now that you've collected the data and crunched the numbers, what do you do with all this information? How do you take the fruit of your analytics labor and apply it to business decision making? How do you actually apply the information gleaned from quants and tech teams? Applied Business Analytics will help you find optimal answers to these questions, and bridge the gap between analytics and execution in your organization. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll learn why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics; how to become one of those deciders; and how to identify, foster, support, empower, and reward others who join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at every level: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ -- and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer
Author: Wilfried Grossmann
Publisher: Springer
ISBN: 3662465310
Category : Computers
Languages : en
Pages : 348
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Book Description
This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.
Author: Larissa Terpeluk Moss
Publisher: Addison-Wesley Professional
ISBN: 9780201784206
Category : Business & Economics
Languages : en
Pages : 582
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Book Description
This software will enable the user to learn about business intelligence roadmap.
Author: Peter Rausch
Publisher: Springer Science & Business Media
ISBN: 1447148665
Category : Computers
Languages : en
Pages : 273
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Book Description
During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others. Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application.
Author: Miah, Shah J.
Publisher: IGI Global
ISBN: 1522557199
Category : Business & Economics
Languages : en
Pages : 384
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Book Description
Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Applying Business Intelligence Initiatives in Healthcare and Organizational Settings incorporates emerging concepts, methods, models, and relevant applications of business intelligence systems within problem contexts of healthcare and other organizational boundaries. Featuring coverage on a broad range of topics such as rise of embedded analytics, competitive advantage, and strategic capability, this book is ideally designed for business analysts, investors, corporate managers, and entrepreneurs seeking to advance their understanding and practice of business intelligence.
Author: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 111954985X
Category : Mathematics
Languages : en
Pages : 608
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Book Description
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
