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Data Warehousing, Data Marts, Business Intelligence, OLAP, Data Management, Balanced Scorecard - our Knowledge Base has free publicly available hints and tips written by our consultants


We also offer a complete consultancy service that will ensure the success of your data warehouse project. If you are interested in our services please contact us

Created on 12/25/2003 01:09 PM by datamgmt
Updated on 08/03/2007 09:27 AM by datamgmt
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The Data Management & Warehousing Knowledge Base provides information and techniques about the design, build and implementation of data warehousing solutions that we as a company use and hope that you will also find useful.

The Business Case for Business Intelligence
This white paper looks at the business case that should lie behind the decision to build a data warehouse and provide a business intelligence solution.
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Detecting Changed Data
Description of a method to identify changes from one version of an extract file to the next.
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CSV File Format
We all know that we should be writing file extracts as XML but if we really need to get a CSV file then here is how to do it
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How Data Works
How business store and manage their data can have critical effect on data quality and consistency as well as performance and development times. This paper examines how data works and explores techniques exploited from understanding how data works
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Continuous Data Quality Process Wallchart
A wallchart outlining the process required to develop continuous data quality within an organisation is available for download
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Data Warehouse Documentation Roadmap
All projects need documentation and many companies provide templates as part of a methodology. This document describes the templates, tools and source documents used by Data Management & Warehousing. It serves two purposes:

* For projects using other methodologies or creating their own set of documents to use as a checklist. This allows the project to ensure that the documentation covers the essential areas for describing the data warehouse.
* To demonstrate our approach to our clients by describing the templates and deliverables that are produced.
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Data Warehouse Governance
An organisation that is embarking on a data warehousing project is undertaking a long-term development and maintenance programme of a computer system. This system will be critical to the organisation and cost a significant amount of money, therefore control of the system is vital. Governance defines the model the organisation will use to ensure optimal use and re-use of the data warehouse and enforcement of corporate policies (e.g. business design, technical design, and application security) and ultimately derive value for money.
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Category: Data Warehousing

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Taxonomies and Data Models
When dealing with unstructured data, taxonomies are used to organize and understand the textual, unstructured data.

Computed Attributes, Entity Resolution and Connectivity Hierarchies
David Loshin suggests that it is worth considering the potential of the types of computed or calculated data elements associated with data subject areas that are subjected to entity resolution. The end of the article poses an interesting question, and you’re encouraged to reply.

Norman H. Nie, Revolution Analytics
Norman Nie, CEO of Revolution Analytics, talks with Mary Jo Nott of the BeyeNETWORK about the market conditions that are causing organizations to use predictive analytics and why they are turning to Revolution and R.

Data Quality is a Business Issue: Getting Back to Basics, Part 2
This conclusion of a two-part series looks at the types of data quality issues that occur in various areas of an enterprise and describes how business leadership can play a key role in correcting and stopping the problems at their source.

Data Warehousing: Kimball vs. Inmon (By Inmon)
In this article, Bill Inmon compares and contrasts the Inmon and Kimball approaches to data warehousing, highlighting the pros and cons of each approach.

Analytic Platforms Survey
We need your input. Take Analytic Platforms Survey today.

Jake Bittner, Qlarion
Jake Bittner, President and CEO of Qlarion, talks with Ron Powell about Qlarion's spin-off from CadenceQuest; their focus on providing business intelligence, data mining and data management solutions to government agencies, government-sponsored enterprises and commercial organizations that support the public sector mission; and the unique challenges facing government agencies today.

What Can the Real-Time Web Economy Do for Your Business?
To make better business decisions, organizations are finding increased need for relevant, real-time data from public websites, such as BBC.com, or social networking sites such as Twitter, LinkedIn or Facebook, as well as from private, firewall-protected websites and Web applications.

Limiting Business Intelligence Project Failures: Some Practical Hints, Part 1
This article, Part 1 of a two-part series, offers helpful tips for developing successful business intelligence projects.

IT Jobs Are Growing: Where is Business Intelligence?
As business intelligence practitioners look to the job market as a factor in economic or social analysis, it is important to have a sense of how the IT professions themselves are performing in these times.

No Perfect Answer
Should organizations always adopt new technology when it promises to positively affect the bottom line? Or, are there times when organizations should take the safe route?

Reinventing Business: Enterprise Data Warehouse Business Opportunities for Manufacturing, Part 5
This article, Part 5 of a continuing series, covers enterprise data warehouse-enabled business improvement opportunities for the supply chain.

BPM Pulse 2010 Results and Analysis, Part 4
Craig Schiff concludes his four-part series by describing the BPM Pulse survey respondents' technology priorities and expected performance management investment.

Brett Jackson, LogiXML
Brett Jackson discusses business intelligence with Ron Powell. Brett talks about what differentiates LogiXML from other business intelligence providers.

From Business Intelligence to Enterprise IT Architecture, Part 4
This article, Part 4 of a continuing series, describes a modern approach to the business need for meaningful convergence of hard and soft information, which historically has been a challenge for data warehousing.

Category: Uncategorized

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