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| database and business intelligence: Oracle Data Warehousing and Business Intelligence Solutions Robert Stackowiak, Joseph Rayman, Rick Greenwald, 2007-01-06 Up-to-date, comprehensive coverage of the Oracle database and business intelligence tools Written by a team of Oracle insiders, this authoritative book provides you with the most current coverage of the Oracle data warehousing platform as well as the full suite of business intelligence tools. You'll learn how to leverage Oracle features and how those features can be used to provide solutions to a variety of needs and demands. Plus, you'll get valuable tips and insight based on the authors' real-world experiences and their own implementations. Avoid many common pitfalls while learning best practices for: Leveraging Oracle technologies to design, build, and manage data warehouses Integrating specific database and business intelligence solutions from other vendors Using the new suite of Oracle business intelligence tools to analyze data for marketing, sales, and more Handling typical data warehouse performance challenges Uncovering initiatives by your business community, security business sponsorship, project staffing, and managing risk |
| database and business intelligence: 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 |
| database and business intelligence: 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. |
| database and business intelligence: Business Intelligence David Loshin, 2012-11-27 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 |
| database and business intelligence: 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. |
| database and business intelligence: Business Database Systems Thomas Connolly, Carolyn E. Begg, Richard Holowczak, 2008 Business Database Systems arms you with the knowledge to analyse, design and implement effective, robust and successful databases. This book is ideal for students of Business/Management Information Systems, or Computer Science, who will be expected to take a course in database systems for their degree programme. It is also excellently suited to any practitioner who needs to learn, or refresh their knowledge of, the essentials of database management systems. |
| database and business intelligence: Internet-enabled Business Intelligence William A. Giovinazzo, 2003 William Giovinazzo gives experienced database professionals practical guidance for every aspect of planning and deploying Web-based data warehouses -- and leveraging them for competitive advantage. Unlike previous books, The Web-Enabled Data Warehouse covers all the enabling technologies and analysis approaches you need to know about -- from XML to CRM, Java to customer profiling. Giovinazzo begins by introducing the compelling advantages of integrating business intelligence and data warehouses with Web technology. He reviews the business and technical contexts in which the Web-enabled data warehouse will operate; shows how to build and optimize data warehouse infrastructure, and presents in-depth coverage of key enabling technologies -- including Java, XML and XSL, LDAP directories, and WAP wireless development environments. In the book's final section, Giovinazzo introduces and explains powerful new analysis techniques that can dramatically improve your understanding of customers -- and shows how to integrate data warehouses with CRM and other enterprise systems so you can act on your knowledge far more quickly and efficiently. For every experienced database professional seeking to understand or deploy Web-based data warehouses. |
| database and business intelligence: Open Source Data Warehousing and Business Intelligence Lakshman Bulusu, 2012-08-06 Open Source Data Warehousing and Business Intelligence is an all-in-one reference for developing open source based data warehousing (DW) and business intelligence (BI) solutions that are business-centric, cross-customer viable, cross-functional, cross-technology based, and enterprise-wide. Considering the entire lifecycle of an open source DW & BI implementation, its comprehensive coverage spans from basic concepts all the way through to customization. Highlighting the key differences between open source and vendor DW and BI technologies, the book identifies end-to-end solutions that are scalable, high performance, and stable. It illustrates the practical aspects of implementing and using open source DW and BI technologies to supply you with valuable on-the-project experience that can help you improve implementation and productivity. Emphasizing analysis, design, and programming, the text explains best-fit solutions as well as how to maximize ROI. Coverage includes data warehouse design, real-time processing, data integration, presentation services, and real-time reporting. With a focus on real-world applications, the author devotes an entire section to powerful implementation best practices that can help you build customer confidence while saving valuable time, effort, and resources. |
| database and business intelligence: Developing Business Intelligence Apps for SharePoint David Feldman, Jason Himmelstein, 2013-07-02 Create dynamic business intelligence (BI) solutions for SharePoint faster and with more capabilities than previously possible. With this book, you’ll learn the entire process—from high-level concepts to development and deployment—for building data-rich BI applications with Visual Studio LightSwitch, SQL Server 2012, and a host of related Microsoft technologies. You’ll learn practical techniques and patterns necessary to use all of these technologies together as you build an example application through the course of the book, step by step. Discover how to solve real problems, using BI solutions that will evolve to meet future needs. Learn the fundamentals of SharePoint, LightSwitch, and SQL Server 2012 Get a solid grounding in BI application basics and database design principles Use LightSwitch to build a help desk app, including data model design and SharePoint data integration Build a tabular cube with Microsoft’s Business Intelligence Semantic Model (BISM) Dive into the data visualization stack, including Excel and SQL Server Reporting Services Create reports with Excel Services, Report Builder, and PowerView Use tips and tricks for setting up your BI application development environment |
| database and business intelligence: 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. |
| database and business intelligence: 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. |
| database and business intelligence: Introduction to R for Business Intelligence Jay Gendron, 2016-08-26 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. |
| database and business intelligence: Practical Business Intelligence with SQL Server 2005 John C. Hancock, Roger Toren, 2006-08-28 Design, Build, and Manage High-Value BI Solutions with SQL Server 2005 In this book, two of Microsoft’s leading consultants illustrate how to use SQL Server 2005 Business Intelligence (BI) technologies to solve real-world problems in markets ranging from retail and finance to healthcare. Drawing on extensive personal experience with Microsoft’s strategic customers, John C. Hancock and Roger Toren offer unprecedented insight into BI systems design and step-by-step best practices for implementation, deployment, and management. Hancock and Toren introduce practical BI concepts and terminology and provide a concise primer on the Microsoft BI platform. Next, they turn to the heart of the book–constructing solutions. Each chapter-length case study begins with the customer’s business goals, and then guides you through detailed data modeling. The case studies show how to avoid the pitfalls that derail many BI projects. You’ll translate each model into a working system and learn how to deploy it into production, maintenance, and efficient operation. Whether you’re a decision-maker, architect, developer, or DBA, this book brings together all the knowledge you’ll need to derive maximum business value from any BI project. • Leverage SQL Server 2005 databases, Integration Services, Analysis Services, and Reporting Services • Build data warehouses and extend them to support very large databases • Design effective Analysis Services databases • Ensure the superior data quality your BI system needs • Construct advanced enterprise scorecard applications • Use data mining to segment customers, cross-sell, and increase the value of each transaction • Design real-time BI applications • Get hands-on practice with SQL Server 2005’s BI toolset |
| database and business intelligence: Tapping into Unstructured Data William H. Inmon, Anthony Nesavich, 2007-12-11 The Definitive Guide to Unstructured Data Management and Analysis--From the World’s Leading Information Management Expert A wealth of invaluable information exists in unstructured textual form, but organizations have found it difficult or impossible to access and utilize it. This is changing rapidly: new approaches finally make it possible to glean useful knowledge from virtually any collection of unstructured data. William H. Inmon--the father of data warehousing--and Anthony Nesavich introduce the next data revolution: unstructured data management. Inmon and Nesavich cover all you need to know to make unstructured data work for your organization. You’ll learn how to bring it into your existing structured data environment, leverage existing analytical infrastructure, and implement textual analytic processing technologies to solve new problems and uncover new opportunities. Inmon and Nesavich introduce breakthrough techniques covered in no other book--including the powerful role of textual integration, new ways to integrate textual data into data warehouses, and new SQL techniques for reading and analyzing text. They also present five chapter-length, real-world case studies--demonstrating unstructured data at work in medical research, insurance, chemical manufacturing, contracting, and beyond. This book will be indispensable to every business and technical professional trying to make sense of a large body of unstructured text: managers, database designers, data modelers, DBAs, researchers, and end users alike. Coverage includes What unstructured data is, and how it differs from structured data First generation technology for handling unstructured data, from search engines to ECM--and its limitations Integrating text so it can be analyzed with a common, colloquial vocabulary: integration engines, ontologies, glossaries, and taxonomies Processing semistructured data: uncovering patterns, words, identifiers, and conflicts Novel processing opportunities that arise when text is freed from context Architecture and unstructured data: Data Warehousing 2.0 Building unstructured relational databases and linking them to structured data Visualizations and Self-Organizing Maps (SOMs), including Compudigm and Raptor solutions Capturing knowledge from spreadsheet data and email Implementing and managing metadata: data models, data quality, and more |
| database and business intelligence: Business Intelligence Roadmap Larissa Terpeluk Moss, S. Atre, 2003 This software will enable the user to learn about business intelligence roadmap. |
| database and business intelligence: Perspectives on Business Intelligence Raymond T. Ng, Patricia C. Arocena, Denilson Barbosa, Giuseppe Carenini, 2022-05-31 In the 1980s, traditional Business Intelligence (BI) systems focused on the delivery of reports that describe the state of business activities in the past, such as for questions like How did our sales perform during the last quarter? A decade later, there was a shift to more interactive content that presented how the business was performing at the present time, answering questions like How are we doing right now? Today the focus of BI users are looking into the future. Given what I did before and how I am currently doing this quarter, how will I do next quarter? Furthermore, fuelled by the demands of Big Data, BI systems are going through a time of incredible change. Predictive analytics, high volume data, unstructured data, social data, mobile, consumable analytics, and data visualization are all examples of demands and capabilities that have become critical within just the past few years, and are growing at an unprecedented pace. This book introduces research problems and solutions on various aspects central to next-generation BI systems. It begins with a chapter on an industry perspective on how BI has evolved, and discusses how game-changing trends have drastically reshaped the landscape of BI. One of the game changers is the shift toward the consumerization of BI tools. As a result, for BI tools to be successfully used by business users (rather than IT departments), the tools need a business model, rather than a data model. One chapter of the book surveys four different types of business modeling. However, even with the existence of a business model for users to express queries, the data that can meet the needs are still captured within a data model. The next chapter on vivification addresses the problem of closing the gap, which is often significant, between the business and the data models. Moreover, Big Data forces BI systems to integrate and consolidate multiple, and often wildly different, data sources. One chapter gives an overview of several integration architectures for dealing with the challenges that need to be overcome. While the book so far focuses on the usual structured relational data, the remaining chapters turn to unstructured data, an ever-increasing and important component of Big Data. One chapter on information extraction describes methods for dealing with the extraction of relations from free text and the web. Finally, BI users need tools to visualize and interpret new and complex types of information in a way that is compelling, intuitive, but accurate. The last chapter gives an overview of information visualization for decision support and text. |
| database and business intelligence: Delivering Business Intelligence with Microsoft SQL Server 2012 3/E Brian Larson, 2012-03-16 Implement a Robust BI Solution with Microsoft SQL Server 2012 Equip your organization for informed, timely decision making using the expert tips and best practices in this practical guide. Delivering Business Intelligence with Microsoft SQL Server 2012, Third Edition explains how to effectively develop, customize, and distribute meaningful information to users enterprise-wide. Learn how to build data marts and create BI Semantic Models, work with the MDX and DAX languages, and share insights using Microsoft client tools. Data mining and forecasting are also covered in this comprehensive resource. Understand the goals and components of successful BI Design, deploy, and manage data marts and OLAP cubes Load and cleanse data with SQL Server Integration Services Manipulate and analyze data using MDX and DAX scripts and queries Work with SQL Server Analysis Services and the BI Semantic Model Author interactive reports using SQL Server Data Tools Create KPIs and digital dashboards Use data mining to identify patterns, correlations, and clusters Implement time-based analytics Embed BI reports in custom applications using ADOMD.NET |
| database and business intelligence: Perspectives on Business Intelligence Raymond T. Ng, Patricia C. Arocena, Denilson Barbosa, Giuseppe Carenini, 2013-04-01 business intelligence, big data, business modeling, vivification, data integration, information extraction, information visualization |
| database and business intelligence: 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. |
| database and business intelligence: 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. |
| database and business intelligence: Customer and Business Analytics Daniel S. Putler, Robert E. Krider, 2012-05-07 Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the tex |
| database and business intelligence: Delivering Business Intelligence with Microsoft SQL Server 2005 Brian Larson, 2006-02-14 Transform disparate enterprise data into actionable business intelligence Put timely, mission-critical information in the hands of employees across your organization using Microsoft SQL Server 2005 and the comprehensive information in this unique resource. Delivering Business Intelligence with Microsoft SQL Server 2005 shows you, step-by-step, how to author, customize, and distribute information that will give your company the competitive edge. It's all right here--from data mining, warehousing, and scripting techniques to MDX queries, KPI analysis, and the all-new Unified Dimensional Model. Real-world examples, start-to-finish exercises, and downloadable code throughout illustrate all of the integration, analysis, and reporting capabilities of SQL Server 2005. |
| database and business intelligence: Delivering Business Intelligence With Microsoft Sql Server" 2008 Brian Larson, 2009 With help from this fully updated bestselling book, database professionals will be able to transform disparate enterprise data into actionable Business Intelligence. Covering all the new and improved BI features available in SQL Server 2008, the book shows you how to put timely, mission-critical information in the hands of employees across the organization.Delivering Business Intelligence with Microsoft SQL Server 2008 begins with a discussion of BI, defining what it is and why it is important in today's business environment. After laying this foundation, the book works through the entire BI lifecycle: defining the analysis database; analyzing the data; mining the data; and delivering BI. Several analysis databases will be built and used for examples throughout the book. |
| database and business intelligence: Principles of Database Management Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens, 2018-07-12 Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science. |
| database and business intelligence: 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. |
| database and business intelligence: Agile Analytics Ken Collier, 2012 Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve back-end data management, front-end business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way. |
| database and business intelligence: Business Intelligence, Reprint Edition Stacia Misner, Michael Luckevich, Elizabeth Vitt, 2008-12-10 “This readable, practical book helps business people quickly understand what business intelligence is, how it works, where it's used, and why and when to use it—all illustrated by real case studies, not just theory.” Nigel Pendse Author of The OLAP Report www.olapreport.com So much information, so little time. All too often, business data is hard to get at and use—thus slowing decision-making to a crawl. This insightful book illustrates how organizations can make better, faster decisions about their customers, partners, and operations by turning mountains of data into valuable business information that’s always at the fingertips of decision makers. You’ll learn what’s involved in using business intelligence to bring together information, people, and technology to create successful business strategies—and how to execute those strategies with confidence. Topics covered include: THE BUSINESS INTELLIGENCE MINDSET: Discover the basics behind business intelligence, such as how it’s defined, why and how to use it in your organization, and what characteristics, components, and general architecture most business intelligence solutions share. THE CASE FOR BUSINESS INTELLIGENCE: Read how world leaders in finance, manufacturing, and retail have successfully implemented business intelligence solutions and see what benefits they have reaped. THE PRACTICE OF BUSINESS INTELLIGENCE: Find out what’s involved in implementing a business intelligence solution in your organization, including how to identify your business intelligence opportunities, what decisions you must make to get a business intelligence project going, and what to do to sustain the momentum so that you can continue to make sense of all the data you gather. |
| database and business intelligence: Information Systems for Business and Beyond David T. Bourgeois, 2014 Information Systems for Business and Beyond introduces the concept of information systems, their use in business, and the larger impact they are having on our world.--BC Campus website. |
| database and business intelligence: The Microsoft Data Warehouse Toolkit Joy Mundy, Warren Thornthwaite, 2011-03-08 Best practices and invaluable advice from world-renowned data warehouse experts In this book, leading data warehouse experts from the Kimball Group share best practices for using the upcoming “Business Intelligence release” of SQL Server, referred to as SQL Server 2008 R2. In this new edition, the authors explain how SQL Server 2008 R2 provides a collection of powerful new tools that extend the power of its BI toolset to Excel and SharePoint users and they show how to use SQL Server to build a successful data warehouse that supports the business intelligence requirements that are common to most organizations. Covering the complete suite of data warehousing and BI tools that are part of SQL Server 2008 R2, as well as Microsoft Office, the authors walk you through a full project lifecycle, including design, development, deployment and maintenance. Features more than 50 percent new and revised material that covers the rich new feature set of the SQL Server 2008 R2 release, as well as the Office 2010 release Includes brand new content that focuses on PowerPivot for Excel and SharePoint, Master Data Services, and discusses updated capabilities of SQL Server Analysis, Integration, and Reporting Services Shares detailed case examples that clearly illustrate how to best apply the techniques described in the book The accompanying Web site contains all code samples as well as the sample database used throughout the case studies The Microsoft Data Warehouse Toolkit, Second Edition provides you with the knowledge of how and when to use BI tools such as Analysis Services and Integration Services to accomplish your most essential data warehousing tasks. |
| database and business intelligence: 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 |
| database and business intelligence: Data Mining for Business Analytics Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel, 2019-10-14 Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R |
| database and business intelligence: 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. |
| database and business intelligence: 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. |
| database and business intelligence: Microsoft Data Mining Barry de Ville, 2001-05-17 Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best practices for using all of them. The book bridges the previously specialized field of data mining with the new technologies and methods that are quickly making it an important mainstream tool for companies of all sizes.Data mining refers to a set of technologies and techniques by which IT professionals search large databases of information (such as those contained by SQL Server) for patterns and trends. Traditionally important in finance, telecommunication, and other information-intensive fields, data mining increasingly helps companies better understand and serve their customers by revealing buying patterns and related interests. It is becoming a foundation for e-commerce and knowledge management. - Unique book on a hot data management topic - Part of Digital Press's SQL Server and data mining clusters - Author is an expert on both traditional and Microsoft data mining technologies |
| database and business intelligence: E-Business Intelligence Bernard Liautaud, 2001 Publisher Fact Sheet How to leverage corporate information for reduced costs & increased profits. |
| database and business intelligence: Delivering Business Intelligence with Microsoft SQL Server 2016, Fourth Edition Brian Larson, 2016-11-04 Distribute Actionable, Timely BI with Microsoft® SQL Server® 2016 and Power BI Drive better, faster, more informed decision making across your organization using the expert tips and best practices featured in this hands-on guide. Delivering Business Intelligence with Microsoft SQL Server 2016, Fourth Edition, shows, step-by-step, how to distribute high-performance, custom analytics to users enterprise-wide. Discover how to build BI Semantic Models, create data marts and OLAP cubes, write MDX and DAX scripts, and share insights using Microsoft client tools. The book includes coverage of self-service business intelligence with Power BI. • Understand the goals and components of successful BI • Build data marts, OLAP cubes, and Tabular models • Load and cleanse data with SQL Server Integration Services • Manipulate and analyze data using MDX and DAX scripts and queries • Work with SQL Server Analysis Services and the BI Semantic Model • Author interactive reports using SQL Server Data Tools • Create KPIs and digital dashboards • Implement time-based analytics • Embed data model content in custom applications using ADOMD.NET • Use Power BI to gather, model, and visualize data in a self-service environment |
| database and business intelligence: Computational Intelligence Applications in Business Intelligence and Big Data Analytics Vijayan Sugumaran, Arun Kumar Sangaiah, Arunkumar Thangavelu, 2017-06-26 There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book. |
| database and business intelligence: 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. |
| database and business intelligence: Successful Business Intelligence: Secrets to Making BI a Killer App Cindi Howson, 2007-12-17 Praise for Successful Business Intelligence If you want to be an analytical competitor, you've got to go well beyond business intelligence technology. Cindi Howson has wrapped up the needed advice on technology, organization, strategy, and even culture in a neat package. It's required reading for quantitatively oriented strategists and the technologists who support them. --Thomas H. Davenport, President's Distinguished Professor, Babson College and co-author, Competing on Analytics When used strategically, business intelligence can help companies transform their organization to be more agile, more competitive, and more profitable. Successful Business Intelligence offers valuable guidance for companies looking to embark upon their first BI project as well as those hoping to maximize their current deployments. --John Schwarz, CEO, Business Objects A thoughtful, clearly written, and carefully researched examination of all facets of business intelligence that your organization needs to know to run its business more intelligently and exploit information to its fullest extent. --Wayne Eckerson, Director, TDWI Research Using real-world examples, Cindi Howson shows you how to use business intelligence to improve the performance, and the quality, of your company. --Bill Baker, Distinguished Engineer & GM, Business Intelligence Applications, Microsoft Corporation This book outlines the key steps to make BI an integral part of your company's culture and demonstrates how your company can use BI as a competitive differentiator. --Robert VanHees, CFO, Corporate Express Given the trend to expand the business analytics user base, organizations are faced with a number of challenges that affect the success rate of these projects. This insightful book provides practical advice on improving that success rate. --Dan Vesset, Vice President, Business Analytics Solution Research, IDC |
| database and business intelligence: Big Data and Business Analytics Jay Liebowitz, 2016-04-19 The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions todo this, avoid that.'-From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee CompanyWith the growing barrage of big data, it becomes vitally important for organizations to mak |
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