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dimensional modeling

(Kimball) Dimensional Modeling

data_warehouse dimensional_modeling bi analytics_engineering

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2020-Q1 2026-Q1

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Mastering Data Warehouse Aggregates: Solutions for Star Schema Performance

This is the first book to provide in-depth coverage of star schema aggregates used in dimensional modeling-from selection and design, to loading and usage, to specific tasks and deliverables for implementation projects Covers the principles of aggregate schema design and the pros and cons of various types of commercial solutions for navigating and building aggregates Discusses how to include aggregates in data warehouse development projects that focus on incremental development, iterative builds, and early data loads

The Microsoft® Data Warehouse Toolkit: With SQL Server™ 2005 and the Microsoft® Business Intelligence Toolset

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.

The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data

Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality

Oracle® DBA Guide to Data Warehousing and Star Schemas

The definitive, real-world guide to Oracle data warehousing Maximizing performance, flexibility, and manageability in production environments Hardware/software architectures, star schema design, partitioning, and more Industrial strength data loading and query optimization techniques By the world-renowned architect of 7-Eleven's multi-terabyte datawarehouse Maximize Oracle data warehouse performance, flexibility, and manageability Oracle DBAs finally have a definitive guide to every aspect of designing, constructing, tuning, and maintaining star schema data warehouses with Oracle 8i and 9i. Bert Scalzo, one of the world's leading Oracle data warehousing experts, offers practical, hard-won lessons and breakthrough techniques for maximizing performance, flexibility, and manageability in any production environment. Coverage includes: Data warehousing fundamentals for DBAs--including what a data warehouse isn't Planning software architecture: business intelligence, user interfaces, Oracle versions, OS platforms, and more Planning hardware architecture: CPUs, memory, disk space, and configuration Radically different star schema design for radically improved performance Tuning ad-hoc queries for lightning speed Industrial-strength data loading techniques Aggregate tables: maximizing performance benefits, minimizing complexity tradeoffs Improving manageability: The right ways to partition Data warehouse administration: Backup/recovery, space and extent management, updates, patches, and more

SAP® BW: A Step-by-Step Guide

SAP BW has recently come to the fore as a valuable tool for developing data warehouses that accurately and effectively support critical business decision making. It facilitates easy-to-use and high-performance extraction, transfer, transformation, and loading of data from a variety of data sources, including such comprehensive business management systems as SAP R/3. This practitioner's guide uses step-by-step instructions complete with a plethora of screen captures to illustrate key SAP BW functionalities. It demonstrates how SAP BW implements the fundamental star schema and solves the major challenges inherent in the creation of data warehouses: performance, reliability, and error-handling. Using a real-world business scenario as a running example, presents a comprehensive view of the technology, from underlying concepts and basic techniques through its most sophisticated capabilities. SAP® BW Specific topics covered include: Creating an InfoCube and loading the data Checking the accuracy of data with BW Monitor and the Persistent Staging Area (PSA) Creating queries to generate reports using Business Explorer (BEx) Managing user authorization with the Profile Generator Advanced InfoCube design techniques Aggregates and multicubes Working with the Operational Data Store (ODS) Installing business content and creating an R/3 source system in BW Loading data from SAP R/3 into SAP BW Data maintenance Performance tuning, including parallel query option and data packet sizing Object transport Although the focus is on the core SAP BW technology, this book also discusses other relevant technologies, including Basis, ABAP (Advanced Business Application Programming), ALE (Application Link Enabling), and ASAP (Accelerated SAP) for BW. With the clear explanations and practical techniques presented in information systems professionals will gain both the general understanding and specific skills necessary to create high quality data warehouses that support effective decision making. SAP® BW 0201703661B07092002

The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling

Single most authoritative guide from the inventor of the technique. Presents unique modeling techniques for e-commerce, and shows strategies for optimizing performance. Companion Web site provides updates on dimensional modeling techniques, links related to sites, and source code where appropriate.

Data Warehouse Design Solutions

"Each chapter is... a practice run for the way we all ought to design our data marts and hence our data warehouses."-Ralph Kimball, from the Foreword. Let the experts show you how to customize data warehouse designs for real business needs in Data Warehouse Design Solutions. To effectively design a data warehouse, you have to understand its many business uses. This guidebook shows you how business managers in different corporate functions actually use data warehouses to make decisions. You'll get a rich set of data warehouse designs that flow from realistic business cases. Two top experts show you how to customize your data warehouse designs for real-life business needs including: Sales and marketing Production and inventory management Budgeting and financial reporting Quality control Product delivery and fulfillment Strategic business analysis such as determining market share, rates of return on investment, and other key analytic ratios. CD-ROM includes All sample data warehouse designs with accompanying preformatted reports in HTML for specific business uses such as marketing, sales, and financial analysis. This title includes additional digital media when purchased in print format. For this digital book edition, media content may not be included. Contact the publisher's customer service directly for assistance.