Business Intelligence Reporting Systems

  business intelligence reporting systems: Business Intelligence Tools for Small Companies Albert Nogués, Juan Valladares, 2017-05-25 Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions
  business intelligence reporting systems: Business Intelligence Carlo Vercellis, 2011-08-10 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.
  business intelligence reporting systems: Handbook on Decision Support Systems 2 Frada Burstein, Clyde W. Holsapple, 2008-01-22 As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come.
  business intelligence reporting systems: Healthcare Business Intelligence Laura Madsen, 2012 This book will be constructed as a guidebook for healthcare organizations that are attempting BI/DW. It will address the primary functions of a business intelligence capability and how BI can ease the increasing regulatory reporting pressures on all healthcare organizations. Also included will be tables, checklists and a few forms. Tenative chapter contents: Chapter 1: What is Healthcare BI? Chapter 2: The Five Disciplines of Business Intelligence Chapter 3: The Importance of ETL Chapter 4: Starting with Data Governance Chapter 5: Creating a BI team Chapter 6: Data Modeling for Healthcare Chapter 7: Gaining Support for your BI program Chapter 8: Ensuring good User Adoption Chapter 9: Marketing Your BI Program Chapter 10: Maintaining Your BI Program--
  business intelligence reporting systems: Decision Support Systems for Business Intelligence Vicki L. Sauter, 2014-08-21 Praise for the First Edition This is the most usable decision support systems text. [i]t is far better than any other text in the field —Computing Reviews Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS. This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels—general theory, implications for DSS design, and code development—the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features: Expanded coverage of data mining with new examples Newly added discussion of business intelligence and transnational corporations Discussion of the increased capabilities of databases and the significant growth of user interfaces and models Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field. Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology.
  business intelligence reporting systems: Business Intelligence with SQL Server Reporting Services Adam Aspin, 2015-03-02 Business Intelligence with SQL Server Reporting Services helps you deliver business intelligence with panache. Harness the power of the Reporting Services toolkit to combine charts, gauges, sparklines, indicators, and maps into compelling dashboards and scorecards. Create compelling visualizations that seize your audience’s attention and help business users identify and react swiftly to changing business conditions. Best of all, you'll do all these things by creating new value from software that is already installed and paid for – SQL Server and the included SQL Server Reporting Services. Businesses run on numbers, and good business intelligence systems make the critical numbers immediately and conveniently accessible. Business users want access to key performance indicators in the office, at the beach, and while riding the subway home after a day's work. Business Intelligence with SQL Server Reporting Services helps you meet these need for anywhere/anytime access by including chapters specifically showing how to deliver on modern devices such as smart phones and tablets. You'll learn to deliver the same information, with similar look-and-feel, across the entire range of devices used in business today. Key performance indicators give fast notification of business unit performance Polished dashboards deliver essential metrics and strategic comparisons Visually arresting output on multiple devices focuses attention
  business intelligence reporting systems: Effective Business Intelligence Systems Robert J. Thierauf, 2001-06-30 One step above knowledge management systems are business intelligence systems. Their purpose is to give decision makers a better understanding of their organization's operations, and thus another way to outmaneuver the competition, by helping to find and extract the meaningful relationships, trends, and correlations that underlie the organization's operations and ultimately contribute to its success. Thierauf also shows that by tying critical success factors and key performance indicators into business intelligence systems, an organization's most important financial ratios can also be improved. Comprehensive and readable, Thierauf's book will advance the knowledge and skills of all information systems providers and users. It will also be useful as a text in upper-level courses covering a wide range of topics essential to an understanding of executive business systems generally, and specifically their creation and management. The theme underlying Thierauf's unique text is that a thorough understanding of a company's operations is crucial if the company is to be moved to a higher level of competitive advantage. Although data warehousing, data mining, the Internet, the World Wide Web, and other electronic aids have been in place for at least a decade, it is the remarkable and unique capability of business intelligence systems to utilize them that has in turn revolutionized the ability of decision makers to find, accumulate, organize, and access a wider range of information than was ever before possible. Effective business intelligence systems give decision makers a means to keep their fingers on the pulse of their businesses every step of the way. From this it follows that they are thus able to develop new, more workable means to cope with the competition successfully. Comprehensive and readable, Thierauf's book will advance the knowledge and skills of all information systems providers and users. It will also be useful as a text in upper-level courses covering a wide range of topics essential to an understanding of executive business systems generally, and specifically their creation and management.
  business intelligence reporting systems: Integrated Business Information Systems Klaus-Dieter Gronwald, 2017-05-30 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.
  business intelligence reporting systems: Business Intelligence and Performance Management Peter Rausch, Alaa F. Sheta, Aladdin Ayesh, 2013-02-15 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.
  business intelligence reporting systems: Data Virtualization for Business Intelligence Systems Rick van der Lans, 2012-07-25 Annotation In this book, Rick van der Lans explains how data virtualization servers work, what techniques to use to optimize access to various data sources and how these products can be applied in different projects.
  business intelligence reporting systems: Fundamentals of Business Intelligence Wilfried Grossmann, Stefanie Rinderle-Ma, 2015-06-02 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.
  business intelligence reporting systems: Business Intelligence and Analytics Ramesh Sharda, Efraim Turban, Dursun Delen, 2014-02-28 Decision Support and Business Intelligence Systems provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. The 10th edition focuses on Business Intelligence (BI) and analytics for enterprise decision support in a more streamlined book.
  business intelligence reporting systems: Oracle Business Intelligence Yuli Vailiev, 2010-10-12 A fast track guide to uncovering the analytical power of Oracle Business Intelligence: Analytic SQL, Oracle Discoverer, Oracle Reports, and Oracle Warehouse Builder with this book and eBook.
  business intelligence reporting systems: Business Analysis for Business Intelligence Bert Brijs, 2016-04-19 Aligning business intelligence (BI) infrastructure with strategy processes not only improves your organization's ability to respond to change, but also adds significant value to your BI infrastructure and development investments. Until now, there has been a need for a comprehensive book on business analysis for BI that starts with a macro view and
  business intelligence reporting systems: Microsoft Business Intelligence Tools for Excel Analysts Michael Alexander, Jared Decker, Bernard Wehbe, 2014-05-05 Bridge the big data gap with Microsoft Business Intelligence Tools for Excel Analysts The distinction between departmental reporting done by business analysts with Excel and the enterprise reporting done by IT departments with SQL Server and SharePoint tools is more blurry now than ever before. With the introduction of robust new features like PowerPivot and Power View, it is essential for business analysts to get up to speed with big data tools that in the past have been reserved for IT professionals. Written by a team of Business Intelligence experts, Microsoft Business Intelligence Tools for Excel Analysts introduces business analysts to the rich toolset and reporting capabilities that can be leveraged to more effectively source and incorporate large datasets in their analytics while saving them time and simplifying the reporting process. Walks you step-by-step through important BI tools like PowerPivot, SQL Server, and SharePoint and shows you how to move data back and forth between these tools and Excel Shows you how to leverage relational databases, slice data into various views to gain different visibility perspectives, create eye-catching visualizations and dashboards, automate SQL Server data retrieval and integration, and publish dashboards and reports to the web Details how you can use SQL Server’s built-in functions to analyze large amounts of data, Excel pivot tables to access and report OLAP data, and PowerPivot to create powerful reporting mechanisms You’ll get on top of the Microsoft BI stack and all it can do to enhance Excel data analysis with this one-of-a-kind guide written for Excel analysts just like you.
  business intelligence reporting systems: Business Intelligence Rimvydas Skyrius, 2022-03-09 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.
  business intelligence reporting systems: Business Intelligence Guidebook Rick Sherman, 2014-11-04 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.
  business intelligence reporting systems: Business Analytics for Managers Gert Laursen, Jesper Thorlund, 2010-07-13 While business analytics sounds like a complex subject, this book provides a clear and non-intimidating overview of the topic. Following its advice will ensure that your organization knows the analytics it needs to succeed, and uses them in the service of key strategies and business processes. You too can go beyond reporting!—Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College; coauthor, Analytics at Work: Smarter Decisions, Better Results Deliver the right decision support to the right people at the right time Filled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions. Take a look inside and find: Proven guidance on developing an information strategy Tips for supporting your company's ability to innovate in the future by using analytics Practical insights for planning and implementing BA How to use information as a strategic asset Why BA is the next stepping-stone for companies in the information age today Discussion on BA's ever-increasing role Improve your business's decision making. Align your business processes with your business's objectives. Drive your company into a prosperous future. Taking BA from buzzword to enormous value-maker, Business Analytics for Managers helps you do it all with workable solutions that will add tremendous value to your business.
  business intelligence reporting systems: Data Science and Its Applications Aakanksha Sharaff, G R Sinha, 2021-08-18 The term data being mostly used, experimented, analyzed, and researched, Data Science and its Applications finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.
  business intelligence reporting systems: Enterprise Resource Planning and Business Intelligence Systems for Information Quality Carlo Caserio, Sara Trucco, 2018-04-13 This book analyses the role of Enterprise Resource Planning (ERP) and Business Intelligence (BI) systems in improving information quality through an empirical analysis carried out in Italy. The study begins with a detailed examination of ERP features that highlights the advantages and disadvantages of ERP adoption. Critical success factors for ERP implementation and post-implementation are then discussed, along with the capabilities of ERP in driving the alignment between management accounting and financial accounting information.The study goes on to illustrate the features of BI systems and to summarize companies’ needs for BI. Critical success factors for BI implementation are then presented, along with the BI maturity model and lifecycle. The focus of the research entails a detailed empirical analysis in the Italian setting designed to investigate the role played by ERP and BI systems in reducing information overload/underload and improving information quality by influencing the features of information flow. The practical and theoretical implications of the study are discussed and future avenues of research are suggested. This book will be of value for all those who have an interest in the capacities of ERP and BI systems to enhance business information quality.
  business intelligence reporting systems: Decision Support Systems and Intelligent Systems Efraim Turban, Jay E. Aronson, 1998 B> This book is widely known for its comprehensive treatment of decision support theory and how it is applied. Through four editions, this book has defined the course and set the standard for up-to-date coverage of the latest decision support theories and practices by managers and organizations. This fifth edition has been streamlined and updated throughout to reflect new computing technologies. Chapter 9 has been completely rewritten to focus on the Internet and Intranet. The reader will find expanded coverage of data warehousing, data mining, on-line analytical processes, and an entirely new chapter on intelligent agents (Ch. 19). Internet related topics and links to Internet exercises and cases appear throughout the new edition.
  business intelligence reporting systems: Handbook of Research on Applied AI for International Business and Marketing Applications Christiansen, Bryan, Škrinjari?, Tihana, 2020-09-25 Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.
  business intelligence reporting systems: IBM Cognos Business Intelligence V10.1 Handbook Dean Browne, Brecht Desmeijter, Rodrigo Frealdo Dumont, Armin Kamal, John Leahy, Scott Masson, Ksenija Rusak, Shinsuke Yamamoto, Martin Keen, IBM Redbooks, 2010-10-25 IBM® Cognos® Business Intelligence (BI) helps organizations meet strategic objectives and provides real value for the business by delivering the information everyone needs while also reducing the burden on IT. This IBM Redbooks® publication addresses IBM Cognos Business Intelligence V10.1. You can use this book to: - Understand core features of IBM Cognos BI V10.1 - Realize the full potential of IBM Cognos BI - Learn by example with practical scenarios This book uses a fictional business scenario to demonstrate the power of IBM Cognos BI. The book is primarily focused on the roles of Advanced Business User, Professional Report Author, Modeler, Administrator, and IT Architect.
  business intelligence reporting systems: Business Intelligence for the Enterprise Mike Biere, 2003 This text aims to help you to maximize the potential of Business Intelligence in your organization. It includes stories of companies that implemented BI - those that have succeeded and those that have failed.
  business intelligence reporting systems: Business Intelligence in the Digital Economy Mahesh S. Raisinghani, 2004-01-01 Annotation Business Intelligence in the Digital Economy: Opportunities, Limitations and Risks describes business intelligence (BI), how it is being conducted and managed and its major opportunities, limitations, issues and risks. This book takes an in-depth look at the scope of global technological change and BI. During this transition to BI, information does not merely add efficiency to the transaction; it adds value. This book brings together high quality expository discussions from experts in this field to identify, define, and explore BI methodologies, systems, and approaches in order to understand the opportunities, limitations and risks.
  business intelligence reporting systems: Knight's Microsoft Business Intelligence 24-Hour Trainer Brian Knight, Devin Knight, Adam Jorgensen, Patrick LeBlanc, Mike Davis, 2011-11-30 A book-and-video introduction to Microsoft's Business Intelligence tools If you are just starting to get a handle on Microsoft Business Intelligence (BI) tools, this book and accompanying video provides you with the just the right amount of information to perform basic business analysis and reporting. You'll explore the components and related tools that comprise the Microsoft BI toolset as well as the new BI features of Office 2010. After a basic primer on BI and data modeling, the expert team of authors provides you with step-by-step lessons in the book and videos on the accompanying DVD on how to use SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services, Excel BI (including PowerPivot), and SharePoint. Integrates instructional videos with each of the lessons found in the book to enhance your learning experience Explores the Microsoft Business Intelligence (BI) toolset as well as the new BI features of Office 2010 Encourages you to practice what you've learned in Try It Out sections Contains video demonstrations that walk you through how to tackle each lesson featured in the book With Knight's Microsoft Business Intelligence 24-Hour Trainer, veteran authors present you with an ideal introductory book-and-video package so that you can get started working with the BI toolset immediately! Note: As part of the print version of this title, video lessons are included on DVD. For e-book versions, video lessons can be accessed at wrox.com using a link provided in the interior of the e-book.
  business intelligence reporting systems: Implementing Information Technology Governance: Models, Practices and Cases Van Grembergen, Wim, De Haes, Steven, 2007-09-30 In many organizations, information technology (IT) has become crucial in the support, sustainability, and growth of the business. This pervasive use of technology has created a critical dependency on IT that calls for a specific focus on IT governance. Implementing Information Technology Governance: Models, Practices and Cases presents insight gained through literature reviews and case studies to provide practical guidance for organizations who want to start implementing IT governance or improving existing governance models, and provides a detailed set of IT governance structures, processes, and relational mechanisms that can be leveraged to implement IT governance in practice.
  business intelligence reporting systems: The Integrated Enterprise Excellence System Forrest W. Breyfogle, Forrest W. Breyfogle, III, 2008 The Integrated Enterprise Excellence (IEE) system is a set of management techniques that innovatively builds on practices derived from the strengths of past systems--applying structured metrics and a no-nonsense roadmap to initiate process improvement and achieve predictable and sustainable bottom-line benefits.
  business intelligence reporting systems: Business Intelligence Techniques Murugan Anandarajan, Asokan Anandarajan, Cadambi A. Srinivasan, 2012-11-02 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.
  business intelligence reporting systems: Business Intelligence and Big Data Celina M. Olszak, 2020-11-17 The twenty-first century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The questions facing us today are: What does success mean? Is success a matter of chance and luck or perhaps is success a category that can be planned and properly supported? Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers, and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization. The book discusses business intelligence (BI) and Big Data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as: Analysis and interpretation of the essence of BI and BD Decision support Potential areas of BI and BD utilization in organizations Factors determining success with using BI and BD The role of BI and BD in value creation for organizations Identifying barriers and constraints related to BI and BD design and implementation The book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes and business performance, and creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success.
  business intelligence reporting systems: Business Intelligence: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2015-12-29 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. Business Intelligence: Concepts, Methodologies, Tools, and Applications presents a comprehensive examination of business data analytics along with case studies and practical applications for businesses in a variety of fields and corporate arenas. Focusing on topics and issues such as critical success factors, technology adaptation, agile development approaches, fuzzy logic tools, and best practices in business process management, this multivolume reference is of particular use to business analysts, investors, corporate managers, and entrepreneurs in a variety of prominent industries.
  business intelligence reporting systems: The Microsoft Data Warehouse Toolkit Joy Mundy, Warren Thornthwaite, 2007-03-22 This groundbreaking book is the first in the Kimball Toolkit series to be product-specific. Microsoft’s BI toolset has undergone significant changes in the SQL Server 2005 development cycle. SQL Server 2005 is the first viable, full-functioned data warehouse and business intelligence platform to be offered at a price that will make data warehousing and business intelligence available to a broad set of organizations. This book is meant to offer practical techniques to guide those organizations through the myriad of challenges to true success as measured by contribution to business value. Building a data warehousing and business intelligence system is a complex business and engineering effort. While there are significant technical challenges to overcome in successfully deploying a data warehouse, the authors find that the most common reason for data warehouse project failure is insufficient focus on the business users and business problems. In an effort to help people gain success, this book takes the proven Business Dimensional Lifecycle approach first described in best selling The Data Warehouse Lifecycle Toolkit and applies it to the Microsoft SQL Server 2005 tool set. Beginning with a thorough description of how to gather business requirements, the book then works through the details of creating the target dimensional model, setting up the data warehouse infrastructure, creating the relational atomic database, creating the analysis services databases, designing and building the standard report set, implementing security, dealing with metadata, managing ongoing maintenance and growing the DW/BI system. All of these steps tie back to the business requirements. Each chapter describes the practical steps in the context of the SQL Server 2005 platform. Intended Audience The target audience for this book is the IT department or service provider (consultant) who is: Planning a small to mid-range data warehouse project; Evaluating or planning to use Microsoft technologies as the primary or exclusive data warehouse server technology; Familiar with the general concepts of data warehousing and business intelligence. The book will be directed primarily at the project leader and the warehouse developers, although everyone involved with a data warehouse project will find the book useful. Some of the book’s content will be more technical than the typical project leader will need; other chapters and sections will focus on business issues that are interesting to a database administrator or programmer as guiding information. The book is focused on the mass market, where the volume of data in a single application or data mart is less than 500 GB of raw data. While the book does discuss issues around handling larger warehouses in the Microsoft environment, it is not exclusively, or even primarily, concerned with the unusual challenges of extremely large datasets. About the Authors JOY MUNDY has focused on data warehousing and business intelligence since the early 1990s, specializing in business requirements analysis, dimensional modeling, and business intelligence systems architecture. Joy co-founded InfoDynamics LLC, a data warehouse consulting firm, then joined Microsoft WebTV to develop closed-loop analytic applications and a packaged data warehouse. Before returning to consulting with the Kimball Group in 2004, Joy worked in Microsoft SQL Server product development, managing a team that developed the best practices for building business intelligence systems on the Microsoft platform. Joy began her career as a business analyst in banking and finance. She graduated from Tufts University with a BA in Economics, and from Stanford with an MS in Engineering Economic Systems. WARREN THORNTHWAITE has been building data warehousing and business intelligence systems since 1980. Warren worked at Metaphor for eight years, where he managed the consulting organization and implemented many major data warehouse systems. After Metaphor, Warren managed the enterprise-wide data warehouse development at Stanford University. He then co-founded InfoDynamics LLC, a data warehouse consulting firm, with his co-author, Joy Mundy. Warren joined up with WebTV to help build a world class, multi-terabyte customer focused data warehouse before returning to consulting with the Kimball Group. In addition to designing data warehouses for a range of industries, Warren speaks at major industry conferences and for leading vendors, and is a long-time instructor for Kimball University. Warren holds an MBA in Decision Sciences from the University of Pennsylvania's Wharton School, and a BA in Communications Studies from the University of Michigan. RALPH KIMBALL, PH.D., has been a leading visionary in the data warehouse industry since 1982 and is one of today's most internationally well-known authors, speakers, consultants, and teachers on data warehousing. He writes the Data Warehouse Architect column for Intelligent Enterprise (formerly DBMS) magazine.
  business intelligence reporting systems: Internet of Things in Business Transformation Parul Gandhi, Surbhi Bhatia, Abhishek Kumar, Mohammad Ali Alojail, Pramod Singh Rathore, 2021-02-03 The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named Industry 5.0 or Industrial Internet of Things. The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.
  business intelligence reporting systems: Data-Driven Business Intelligence Systems for Socio-Technical Organizations Keikhosrokiani, Pantea, 2024-04-09 The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.
  business intelligence reporting systems: Applying Business Intelligence Initiatives in Healthcare and Organizational Settings Miah, Shah J., Yeoh, William, 2018-07-13 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.
  business intelligence reporting systems: Business Intelligence For Dummies Swain Scheps, 2011-02-04 You're intelligent, right? So you've already figured out that Business Intelligence can be pretty valuable in making the right decisions about your business. But you’ve heard at least a dozen definitions of what it is, and heard of at least that many BI tools. Where do you start? Business Intelligence For Dummies makes BI understandable! It takes you step by step through the technologies and the alphabet soup, so you can choose the right technology and implement a successful BI environment. You'll see how the applications and technologies work together to access, analyze, and present data that you can use to make better decisions about your products, customers, competitors, and more. You’ll find out how to: Understand the principles and practical elements of BI Determine what your business needs Compare different approaches to BI Build a solid BI architecture and roadmap Design, develop, and deploy your BI plan Relate BI to data warehousing, ERP, CRM, and e-commerce Analyze emerging trends and developing BI tools to see what else may be useful Whether you’re the business owner or the person charged with developing and implementing a BI strategy, checking out Business Intelligence For Dummies is a good business decision.
  business intelligence reporting systems: Decision Support, Analytics, and Business Intelligence, Third Edition Daniel J. Power, Ciara Heavin, 2017-06-08 Rapid technology change is impacting organizations large and small. Mobile and Cloud computing, the Internet of Things (IoT), and “Big Data” are driving forces in organizational digital transformation. Decision support and analytics are available to many people in a business or organization. Business professionals need to learn about and understand computerized decision support for organizations to succeed. This text is targeted to busy managers and students who need to grasp the basics of computerized decision support, including: What is analytics? What is a decision support system? What is “Big Data”? What are “Big Data” business use cases? Overall, it addresses 61 fundamental questions. In a short period of time, readers can “get up to speed” on decision support, analytics, and business intelligence. The book then provides a quick reference to important recurring questions.
  business intelligence reporting systems: Business Intelligence and Human Resource Management Deepmala Singh, Anurag Singh, Amizan Omar, SB Goyal, 2022-08-31 Business Intelligence (BI) is a solution to modern business problems. This book discusses the relationship between BI and Human Resource Management (HRM). In addition, it discusses how BI can be used as a strategic decision-making tool for the sustainable growth of an organization or business. BI helps organizations generate interactive reports with clear and reliable data for making numerous business decisions. This book covers topics spanning the important areas of BI in the context of HRM. It gives an overview of the aspects, tools, and techniques of BI and how it can assist HRM in creating a successful future for organizations. Some of the tools and techniques discussed in the book are analysis, data preparation, BI-testing, implementation, and optimization on GR and management disciplines. It will include a chapter on text mining as well as a section of case studies for practical use. This book will be useful for business professionals, including but not limited to, HR professionals, and budding business students.
  business intelligence reporting systems: Analytics and Data Science Amit V. Deokar, Ashish Gupta, Lakshmi S. Iyer, Mary C. Jones, 2017-10-05 This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.
  business intelligence reporting systems: Business Intelligence for the Real-Time Enterprise Malu Castellanos, Umeshwar Dayal, Timos Sellis, 2009-08-03 In todayís competitive and highly dynamic environment, analyzing data to understand how the business is performing, to predict outcomes and trends, and to improve the effectiveness of business processes underlying business operations has become cri- cal. The traditional approach to reporting is no longer adequate, users now demand easy-to-use intelligent platforms and applications capable of analyzing real-time bu- ness data to provide insight and actionable information at the right time. The end goal is to improve the enterprise performance by better and timelier decision making, - abled by the availability of up-to-date, high-quality information. As a response, the notion of real-time enterprise has emerged and is beginning to be recognized in the industry. Gartner defines it as “using up-to-date information, getting rid of delays, and using speed for competitive advantage is what the real-time enterprise is all about. . . Indeed, the goal of the real-time enterprise is to act on events as they happen. ” Although there has been progress in this direction and many com- nies are introducing products toward making this vision a reality, there is still a long way to go. In particular, the whole lifecycle of business intelligence requires new techniques and methodologies capable of dealing with the new requirements imposed by the real-time enterprise.
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