Business Intelligence & Data Warehousing Simplified PDF Download

Author: Arshad Khan
Publisher: Stylus Publishing, LLC
ISBN: 1936420864
Category : Computers
Languages : en
Pages : 219

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Book Description
This book targets business and IT professionals who need an introduction to business intelligence and data warehousing through a simple question/answer format. Organized into 30 odd chapters, each on a different topic, the book contains approximately 500 questions with answers and tips. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, etc. The book can also be used as a supplemental textbook, for various data warehousing/business intelligence courses.

Author: Arshad Khan
Publisher:
ISBN: 9781936420322
Category : Computers
Languages : en
Pages : 0

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Book Description
This book targets business and IT professionals who need an introduction to business intelligence and data warehousing fundamentals through a simple question / answer format. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, trends, etc.

Author: Alan R. Simon
Publisher: Elsevier
ISBN: 0080491022
Category : Computers
Languages : en
Pages : 320

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Book Description
You go online to buy a digital camera. Soon, you realize you've bought a more expensive camera than intended, along with extra batteries, charger, and graphics software-all at the prompting of the retailer. Happy with your purchases? The retailer certainly is, and if you are too, you both can be said to be the beneficiaries of "customer intimacy" achieved through the transformation of data collected during this visit or stored from previous visits into real business intelligence that can be exercised in real time. Data Warehousing and Business Intelligence for e-Commerce is a practical exploration of the technological innovations through which traditional data warehousing is brought to bear on this and other less modest e-commerce applications, such as those at work in B2B, G2C, B2G, and B2E models. The authors examine the core technologies and commercial products in use today, providing a nuts-and-bolts understanding of how you can deploy customer and product data in ways that meet the unique requirements of the online marketplace-particularly if you are part of a brick-and-mortar company with specific online aspirations. In so doing, they build a powerful case for investment in and aggressive development of these approaches, which are likely to separate winners from losers as e-commerce grows and matures. * Includes the latest from successful data warehousing consultants whose work has encouraged the field's new focus on e-commerce. * Presents information that is written for both consultants and practitioners in companies of all sizes. * Emphasizes the special needs and opportunities of traditional brick-and-mortar businesses that are going online or participating in B2B supply chains or e-marketplaces. * Explains how long-standing assumptions about data warehousing have to be rethought in light of emerging business models that depend on customer intimacy. * Provides advice on maintaining data quality and integrity in environments marked by extensive customer self-input. * Advocates careful planning that will help both old economy and new economy companies develop long-lived and successful e-commerce strategies. * Focuses on data warehousing for emerging e-commerce areas such as e-government and B2E environments.

Author: Ken Collier
Publisher: Addison-Wesley
ISBN: 032150481X
Category : Business & Economics
Languages : en
Pages : 368

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Book Description
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.

Author: Ralph Hughes
Publisher: Newnes
ISBN: 0123965179
Category : Computers
Languages : en
Pages : 366

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Book Description
You have to make sense of enormous amounts of data, and while the notion of “agile data warehousing might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes. Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious “data mart. Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on track Includes strategies for getting accurate and actionable requirements from a team’s business partner Revolutionary estimating techniques that make forecasting labor far more understandable and accurate Demonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialties Enables you and your teams to start simple and progress steadily to world-class performance levels

Author: Rhonda Delmater
Publisher:
ISBN: 9781555582319
Category : Business
Languages : en
Pages : 0

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Book Description
This manager's guide to customer-centric business intelligence teaches data mining in an accessible way, explaining how it drives next-generation customer relationship strategies. Readers learn how to find patterns such as customer buying habits within their huge stores of data.

Author: Carlo Vercellis
Publisher: John Wiley & Sons
ISBN: 1119965470
Category : Mathematics
Languages : en
Pages : 314

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Book Description
Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

Author: Ralph Kimball
Publisher: John Wiley & Sons
ISBN: 1118082141
Category : Computers
Languages : en
Pages : 464

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Book Description
This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.

Author: Robert Stackowiak
Publisher: John Wiley & Sons
ISBN: 047012718X
Category : Computers
Languages : en
Pages : 410

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Book Description
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

Author: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 111954985X
Category : Mathematics
Languages : en
Pages : 608

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Book Description
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