This software will enable the user to learn about business intelligence roadmap.

"If you are looking for a complete treatment of business intelligence, then go no further than this book. Larissa T. Moss and Shaku Atre have covered all the bases in a cohesive and logical order, making it easy for the reader to follow their line of thought. From early design to ETL to physical database design, the book ties together all the components of business intelligence." --Bill Inmon, Inmon Enterprises This is the eBook version of the print title. The eBook edition contains the same content as the print edition. You will find instructions in the last few pages of your eBook that directs you to the media files. Business Intelligence Roadmap is a visual guide to developing an effective business intelligence (BI) decision-support application. This book outlines a methodology that takes into account the complexity of developing applications in an integrated BI environment. The authors walk readers through every step of the process--from strategic planning to the selection of new technologies and the evaluation of application releases. The book also serves as a single-source guide to the best practices of BI projects. Part I steers readers through the six stages of a BI project: justification, planning, business analysis, design, construction, and deployment. Each chapter describes one of sixteen development steps and the major activities, deliverables, roles, and responsibilities. All technical material is clearly expressed in tables, graphs, and diagrams. Part II provides five matrices that serve as references for the development process charted in Part I. Management tools, such as graphs illustrating the timing and coordination of activities, are included throughout the book. The authors conclude by crystallizing their many years of experience in a list of dos, don'ts, tips, and rules of thumb. Both the book and the methodology it describes are designed to adapt to the specific needs of individual stakeholders and organizations. The book directs business representatives, business sponsors, project managers, and technicians to the chapters that address their distinct responsibilities. The framework of the book allows organizations to begin at any step and enables projects to be scheduled and managed in a variety of ways. Business Intelligence Roadmap is a clear and comprehensive guide to negotiating the complexities inherent in the development of valuable business intelligence decision-support applications.

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

Too many organizations invest in performance management and business intelligence projects, without first establishing the needed conditions to ensure success. But the organizations that lay the groundwork for effective change first reap the benefits. In Profiles in Performance: Business Intelligence Journeys and the Road Map for Change, Howard Dresner (author of The Performance Management Revolution) worked with several extraordinary organizations to understand their thriving "performance-directed culture." In doing so, he developed a unique maturity model-which served as both a filter to select candidates and as a lens to examine accomplishments. Interviews with people from all sides of the organization: business users, finance, senior management and the IT department Provides a complete picture of their progress from inception to current state The models, analyses and real world accounts from these cases will be an invaluable resource to any organization hoping to improve or initiate their own performance-directed culture.

Artificial Intelligence for Business: A Roadmap for Getting Started with AI will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.

We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.