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The Data Warehouse Toolkit

The Definitive Guide to Dimensional Modeling

Author: Ralph Kimball

Publisher: John Wiley & Sons


Category: Computers

Page: 600

View: 592

Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing! The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the foundation on which the data warehousing industry has been built - and now, these books are considered the most authoritative guides on dimensional modeling. This new third edition is a complete library of dimensional modeling techniques, the most comprehensive collection ever. Revised and updated, it covers design techniques that support big data analytics, adds a new chapter on ETL techniques, provides new and enhanced modeling patterns, and much more. Authored by Ralph Kimball, known worldwide as an innovator, consultant, and influential thought leader in the field of data warehousing Begins with fundamental design recommendations and progresses step by step through increasingly complex scenarios Presents unique modeling techniques for e-commerce and common business applications such as inventory management, procurement, invoicing, accounting, and more Draws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, health care, and insurance Design dimensional databases that are easy to understand and provide fast query response with The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 3rd Edition .

Query Acceleration for Business Using IBM Informix Warehouse Accelerator

Author: Whei-Jen Chen

Publisher: IBM Redbooks


Category: Computers

Page: 252

View: 809

IBM® Informix® Warehouse Accelerator is a state-of-the-art in-memory database that uses affordable innovations in memory and processor technology and trends in novel ways to boost query performance. It is a disruptive technology that changes how organizations provide analytics to its operational and historical data. Informix Warehouse Accelerator uses columnar, in-memory approach to accelerate even the most complex warehouse and operational queries without application changes or tuning. This IBM Redbooks® publication provides a comprehensive look at the technology and architecture behind the system. It contains information about the tools, data synchronization, and query processing capabilities of Informix Warehouse Accelerator, and provides steps to implement data analysis by using Informix Warehouse Accelerator within an organization. This book is intended for IBM Business Partners and clients who are looking for low-cost solutions to boost data warehouse query performance.

Agile Data Warehousing for the Enterprise

A Guide for Solution Architects and Project Leaders

Author: Ralph Hughes

Publisher: Newnes


Category: Computers

Page: 562

View: 427

Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program

Relational Database Design and Implementation

Author: Jan L. Harrington

Publisher: Morgan Kaufmann


Category: Computers

Page: 712

View: 984

Relational Database Design and Implementation: Clearly Explained, Fourth Edition, provides the conceptual and practical information necessary to develop a database design and management scheme that ensures data accuracy and user satisfaction while optimizing performance. Database systems underlie the large majority of business information systems. Most of those in use today are based on the relational data model, a way of representing data and data relationships using only two-dimensional tables. This book covers relational database theory as well as providing a solid introduction to SQL, the international standard for the relational database data manipulation language. The book begins by reviewing basic concepts of databases and database design, then turns to creating, populating, and retrieving data using SQL. Topics such as the relational data model, normalization, data entities, and Codd's Rules (and why they are important) are covered clearly and concisely. In addition, the book looks at the impact of big data on relational databases and the option of using NoSQL databases for that purpose. Features updated and expanded coverage of SQL and new material on big data, cloud computing, and object-relational databases Presents design approaches that ensure data accuracy and consistency and help boost performance Includes three case studies, each illustrating a different database design challenge Reviews the basic concepts of databases and database design, then turns to creating, populating, and retrieving data using SQL

Fact Oriented Modeling with FCO-IM

Capturing Business Semantics in Data Models with Fully Communication Oriented Information Modeling

Author: Jan Pieter Zwart

Publisher: Technics Publications


Category: Computers

Page: 306

View: 441

This book offers a complete basic course in Fully Communication Oriented Information Modeling (FCO-IM), a Fact Oriented Modeling (FOM) data modeling technique. The book is suitable for self-study by beginner FCO-IM modelers, whether or not experienced in other modeling techniques. An elaborate case study is used as illustration throughout the book. The book also illustrates how data models in other techniques can be derived from an elementary FCO-IM model. The context of fact oriented modeling is given as well, and perspectives on information modeling indicate related areas of application and further reading.

Star Schema The Complete Reference

Author: Christopher Adamson

Publisher: McGraw Hill Professional


Category: Computers

Page: 510

View: 281

The definitive guide to dimensional design for your data warehouse Learn the best practices of dimensional design. Star Schema: The Complete Reference offers in-depth coverage of design principles and their underlying rationales. Organized around design concepts and illustrated with detailed examples, this is a step-by-step guidebook for beginners and a comprehensive resource for experts. This all-inclusive volume begins with dimensional design fundamentals and shows how they fit into diverse data warehouse architectures, including those of W.H. Inmon and Ralph Kimball. The book progresses through a series of advanced techniques that help you address real-world complexity, maximize performance, and adapt to the requirements of BI and ETL software products. You are furnished with design tasks and deliverables that can be incorporated into any project, regardless of architecture or methodology. Master the fundamentals of star schema design and slow change processing Identify situations that call for multiple stars or cubes Ensure compatibility across subject areas as your data warehouse grows Accommodate repeating attributes, recursive hierarchies, and poor data quality Support conflicting requirements for historic data Handle variation within a business process and correlation of disparate activities Boost performance using derived schemas and aggregates Learn when it's appropriate to adjust designs for BI and ETL tools

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