Business Intelligence For The Enterprise

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.

Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the "Big Data Era"...and most see a critical need to revitalize their current capabilities. Whether they find the frustrating and business-impeding continuation of a long-standing "silos of data" problem, or an over-reliance on static production reports at the expense of predictive analytics and other true business intelligence capabilities, or a lack of progress in achieving the long-sought-after enterprise-wide "single version of the truth" – or all of the above – IT Directors, strategists, and architects find that they need to go back to the drawing board and produce a brand new BI/data warehousing roadmap to help move their enterprises from their current state to one where the promises of emerging technologies and a generation’s worth of best practices can finally deliver high-impact, architecturally evolvable enterprise-scale business intelligence and data warehousing. Author Alan Simon, whose BI and data warehousing experience dates back to the late 1970s and who has personally delivered or led more than thirty enterprise-wide BI/data warehousing roadmap engagements since the mid-1990s, details a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale. Simon addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic. Takes a fresh look at true enterprise-scale BI/DW in the "Dawn of the Big Data Era" Details a checklist-based approach to surveying one’s current state and identifying which components are enterprise-ready and which ones are impeding the key objectives of enterprise-scale BI/DW Provides an approach for how to analyze and test-bed emerging technologies and architectures and then figure out how to include the relevant ones in the roadmaps that will be developed Presents a tried-and-true methodology for building a phased, incremental, and iterative enterprise BI/DW roadmap that is closely aligned with an organization’s business imperatives, organizational culture, and other considerations

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.

A Complete Blueprint for Maximizing the Value of Business Intelligence in the Enterprise The typical enterprise recognizes the immense potential of business intelligence (BI) and its impact upon many facets within the organization—but it’s not easy to transform BI’s potential into real business value. In The New Era of Enterprise Business Intelligence, top BI expert Mike Biere presents a complete blueprint for creating winning BI strategies and infrastructure, and systematically maximizing the value of information throughout the enterprise. This product-independent guide brings together start-to-finish guidance and practical checklists for every senior IT executive, planner, strategist, implementer, and the actual business users themselves. Drawing on thousands of hours working with enterprise customers, Biere helps decision-makers choose from today’s unprecedented spectrum of options, including the latest BI platform suites and appliances. He offers practical, “in-the-trenches” insights on a wide spectrum of planning and implementation issues, from segmenting and supporting users to working with unstructured data. Coverage includes Understanding the scope of today’s BI solutions and how they fit into existing infrastructure Assessing new options such as SaaS and cloud-based technologies Avoiding technology biases and other “project killers” Developing effective RFIs/RFPs and proofs of concept Setting up competency centers and planning for skills development Crafting a better experience for all your business users Supporting the requirements of senior executives, including performance management Cost-justifying BI solutions and measuring success Working with enterprise content management, text analytics, and search Planning and constructing portals, mashups, and other user interfaces Previewing the future of BI

Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.

Business intelligence (BI) has evolved over several years as organizations have extended their online transaction processing (OLTP) capabilities and applications to support their routine operations. With online analytical processing (OLAP), organizations have also established the capability to extract internal and external data from a variety of sources to specifically obtain intelligence about non-routine and often less-structured arrangements. BI therefore refers to applications and technologies that are used to gather, provide access to, and analyze data and information about the operations of an organization. It has the capability of providing comprehensive insight into the more volatile factors affecting the business and its operations, thereby facilitating enhanced decision-making quality and contributing to the creation of business value. Larger and more sophisticated organizations have long been exploiting these capabilities. Business Intelligence for Small and Medium-Sized Enterprises (SMEs) guides SMEs in replicating this experience to provide an agile roadmap toward business sustainability. The book points out that successful BI implementations have generated significant increases in revenue and cost savings, however, the failure rates are also very high. More importantly, it emphasizes that a full range of BI capabilities is not the exclusive purview of large organizations. It shows how SMEs make extensive use of BI techniques to develop the kind of agility endowing them with the organizational capability to sense and respond to opportunities and threats in an increasingly dynamic business environment. It points to the way to a market environment in which smaller organizations could have a larger role. In particular, the book explains that by establishing the agility to leverage internal and external data and information assets, SMEs can enhance their competitiveness by having a comprehensive understanding of the key to an agile roadmap for business sustainability.

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

A Complete Blueprint for Maximizing the Value of Business Intelligence in the Enterprise The typical enterprise recognizes the immense potential of business intelligence (BI) and its impact upon many facets within the organization-but it's not easy to transform BI's potential into real business value. In The New Era of Enterprise Business Intelligence, top BI expert Mike Biere presents a complete blueprint for creating winning BI strategies and infrastructure, and systematically maximizing the value of information throughout the enterprise. This product-independent guide brings togethe.