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Articles from this Site
The Song Remains the Same - Data Shadows Systems Continue to be Pervasive for Reporting and Analytics: BI and DW Trends, 8 for '08
Data Warehousing Meets Data Archiving in Information Lifecycle Management
Eight Best Practices in Dashboard Design
The Role of Packaged BI Applications in Delivering Enterprise-Wide BI and DW
Dazed and Confused - Product Roadmaps, Upgrades and Migrations: BI and DW Trends, 8 for '08
White Papers
Spend Data Warehouse on Steroids
An Architected Approach to Integrated Information
KALIDO Business Modeling
Data Warehouse Lifecycle Management
Data Warehousing Ensuring Data Integrity
Books
The Enterprise Data Warehouse: Planning, Building, and Implementation
Enterprise One to One: Tools for Competing in the Interactive Age
Data Warehousing Advice for Managers
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing, and Deploying Data Warehouses
90 Days to the Data Mart
DW Basics Channel
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Data warehouses are often at the heart of the strategic reporting systems used to help manage and control the business. The function of the data warehouse is to consolidate and reconcile information from across disparate business units and IT systems and provide a context for reporting on and analyzing:
- Corporate performance management
- Profitability
- Consolidated financials
- Compliance
As strategic as they are, enterprise data warehousing projects are highly complex and can be risky. Projects fail almost as much as they succeed, often because of long development cycles, poor information quality and an inability to adapt quickly to changing business conditions or requirements.
The purpose of this portal is to help data warehousing professionals keep the probability of success in their favor by staying abreast with the latest technology and best-practices topics, including:
- Data integration and reconciliation
- Data quality and master data management (MDM)
- Iterative delivery
- "Packaged" data warehousing applications
- Data warehouse performance
- Deployment and change management
This Data Warehousing Basics channel is brought to you by DM Review and Kalido - the leading provider of adaptive enterprise data warehousing and master data management software. It will be updated on a continual basis.
Articles
Using Data Virtualization to Maximize Return on Data Warehousing Investments
Todays enterprises rely on the information in their data warehouses more than ever.
Essential Steps for the Integrated Enterprise Data Warehouse, Part 2
This article describes what the dimension manager and fact provider do, and how to configure business intelligence tools to use the integrated EDW.
Essential Steps for the Integrated Enterprise Data Warehouse, Part 1
This article provides guidance to what an integrated EDW is and what design elements are needed to achieve integration.
Data Warehousing and Business Intelligence is a Service-Oriented Architecture
This paper examines how data warehousing and business intelligence fit into a service-oriented architecture.
Time and Time Again: Managing Time in Relational Databases Part 16 - Physical Implementation of Version Pattern 1
This installment in our series begins to describe the physical implementation of versioning patterns.
Columns
Analytical Database Options
Relational databases are ill-suited for analytical processing. Until recently, database developers were able to overcome the problem.
Building a Leadership Foundation
Ill suggest areas where information management leaders can look to build a leadership foundation.
Drill Down to Ask Why, Part 1
Boiled down to its essence, the real purpose of a data warehouse is to be the perfect platform for decision-making.
Technologies to Take Your Enterprise-Wide BI and DW Program to the Next Level
This column addresses the role of technologies that can take enterprise BI/DW architecture to the next level.
The Song Remains the Same - Data Shadows Systems Continue to be Pervasive for Reporting and Analytics: BI and DW Trends, 8 for 08
BI may not be pervasive, but spreadsheets are.
Ask the Experts
Can anyone share some experience as to how to test a data warehouse?
When is it better to have normalized data to create data marts and when is it better to have dimensional data?
How do I convince my reluctant boss to begin work on a data warehouse?
Where is the best place for a BI application to reside?
How can I enhance the productivity of my fact table load?
White Papers
Spend Data Warehouse on Steroids
By Zycus
An Architected Approach to Integrated Information
By David Waddington
KALIDO Business Modeling
By Bruce Ottmann
Data Warehouse Lifecycle Management
By Cliff Longman
Data Warehousing Ensuring Data Integrity
By Cindy Maurer
Books
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The Enterprise Data Warehouse: Planning, Building, and ImplementationBy Eric Sperley |
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Enterprise One to One: Tools for Competing in the Interactive AgeBy Don Peppers, Martha Rogers |
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Data Warehousing Advice for ManagersBy Patricia L. Ferdinandi |






