Business Intelligence An Overview
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| Author | : Vinaitheerthan Renganathan |
| Publisher | : Vinaitheerthan Renganathan |
| Total Pages | : 105 |
| Release | : 2021-03-18 |
| Genre | : Business & Economics |
| ISBN | : |
Business organizations develop strategies and set targets which focus on maximizing profit, reduce cost, improving customer satisfaction & retention and operational performance. In order to achieve the set targets, organizations need to continuously monitor status of organizational performance. Organizations need to collect, store, organize, transform the data to know the current status of set targets. Business Intelligence tools help the organizations to draw meaningful and actionable insights from the raw data in achieving the set targets. Business Intelligence tools help the organizations to answer questions such as where the organization stands in terms of profitability, growth status, brand & market position and market segment. Business intelligence tools focuses mainly on the past or current data and try to explore the hidden insight from the data. Business intelligence tools include querying, reporting, online analytics and data visualization tools which help the business decision makers to arrive at informed decision about the impact and status of their strategies. This book starts with the introduction of business intelligence concepts, components of business intelligence system, business intelligence tools used for querying, reporting and visualization of data. It provides an overview of the data visualization and data mining methods like classification, clustering and regression methods using R open source software. Book also covers some of the basic descriptive and inferential statistical tools. It focuses on both managerial side and technological side of BI. Vinaitheerthan Renganathan www.vinatheerthan.com/book.php
| Author | : David Loshin |
| Publisher | : Newnes |
| Total Pages | : 401 |
| Release | : 2012-11-27 |
| Genre | : Computers |
| ISBN | : 0123858909 |
Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. - Guides managers through developing, administering, or simply understanding business intelligence technology - Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization's data into actionable knowledge - Contains a handy, quick-reference to technologies and terminology
| Author | : Marie-Aude Aufaure |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 215 |
| Release | : 2012-01-16 |
| Genre | : Business & Economics |
| ISBN | : 3642273572 |
Business Intelligence (BI) promises an organization the capability of collecting and analyzing internal and external data to generate knowledge and value, providing decision support at the strategic, tactical, and operational levels. Business Intelligence is now impacted by the Big Data phenomena and the evolution of society and users, and needs to take into account high-level semantics, reasoning about unstructured and structured data, and to provide a simplified access and better understanding of diverse BI tools accessible trough mobile devices. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. The lectures held at the First European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI technologies like data warehouses, OLAP query processing, or performance issues, but extend into new aspects that are important in this new environment and for novel applications, e.g., semantic technologies, social network analysis and graphs, services, large-scale management, or collaborative decision making. Combining papers by leading researchers in the field, this volume will equip the reader with the state-of-the-art background necessary for inventing the future of BI. It will also provide the reader with an excellent basis and many pointers for further research in this growing field.
| Author | : Jerzy Surma |
| Publisher | : Business Expert Press |
| Total Pages | : 161 |
| Release | : 2011-03-06 |
| Genre | : Business & Economics |
| ISBN | : 1606491865 |
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 | : Steve Williams |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 241 |
| Release | : 2016-04-08 |
| Genre | : Computers |
| ISBN | : 0128094893 |
Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like "big data and "big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans
| Author | : Klaus-Dieter Gronwald |
| Publisher | : Springer |
| Total Pages | : 206 |
| Release | : 2017-05-30 |
| Genre | : Computers |
| ISBN | : 3662532913 |
Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM), Business Intelligence (BI) and Big Data Analytics (BDA) are business related tasks and processes, which are supported by standardized software solutions. The book explains that this requires business oriented thinking and acting from IT specialists and data scientists. It is a good idea to let students experience this directly from the business perspective, for example as executives of a virtual company. The course simulates the stepwise integration of the linked business process chain ERP-SCM-CRM-BI-Big Data of four competing groups of companies. The course participants become board members with full P&L responsibility for business units of one of four beer brewery groups managing supply chains from production to retailer.
| Author | : Carlo Vercellis |
| Publisher | : John Wiley & Sons |
| Total Pages | : 314 |
| Release | : 2011-08-10 |
| Genre | : Mathematics |
| ISBN | : 1119965470 |
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.
| Author | : Rick Sherman |
| Publisher | : Newnes |
| Total Pages | : 551 |
| Release | : 2014-11-04 |
| Genre | : Computers |
| ISBN | : 0124115284 |
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. - Provides practical guidelines for building successful BI, DW and data integration solutions. - Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. - Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses - Describes best practices and pragmatic approaches so readers can put them into action. - Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.
| Author | : Jay Gendron |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 223 |
| Release | : 2016-08-26 |
| Genre | : Computers |
| ISBN | : 178528651X |
Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions—and all of this with the help of real-life examples.
| Author | : Murugan Anandarajan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 271 |
| Release | : 2012-11-02 |
| Genre | : Business & Economics |
| ISBN | : 3540247009 |
Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.
