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Articles

Displaying 2040–2055 (of 2060)

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Title Popularity * Date
The Meta Data Model – Part 2 Summary
The on-going quality expectations of the meta data model are critical to the audit and control processes. This will become increasingly important as companies apply meta data in support of Sarbanes-Oxley and other regulations.

Topics: Data Integration, Best Practices, Business Intelligence, Information Management, Data Modeling and Design, Architecture, Metadata

by Jonathan Geiger | 0 comments
06-30-2004
Nanowarehousing: Nanotechnology and Data Warehousing Summary
Nanotechnology begins to defy the laws of separation. Structure and basic interaction rules are relegated to RDBMS engines, while the function of the information contained is relegated to ETL, Business Intelligence, Analytics, Data Mining, and OLTP.

Topics: Data Integration, Best Practices, Business Intelligence, Information Management, Data Modeling and Design, Architecture, Metadata

by Dan Linstedt | 0 comments
06-30-2004
The Nanotechnology Revolution Summary
The Nanotechnology Revolution has arrived! business intelligence and data warehousing need to prepare for the “atomic” age.

Topics: Data Warehousing, Best Practices, Data Mining and Statistical Analysis, Architecture, Nanowarehousing / Nanotechnology

by Dan Linstedt | 0 comments
06-30-2004
The Meta Data Model – Part 1 Summary
This model contains four critical subject areas that should to be addressed by any meta data model.

Topics: Data Integration, Best Practices, Business Intelligence, Information Management, Data Modeling and Design, Architecture, Metadata

by Jonathan Geiger | 0 comments
06-24-2004
Data Quality Summary
An enterprise runs under the assumption that the data contained inside it is accurate and valid. If the data is not valid, then there is no accountability for the decisions based upon it.

Topics: Data Integration, Best Practices, Business Intelligence, Information Management, Data Quality, Data Warehousing, Enterprise Information Integration (EII)

by Bill Inmon | 0 comments
06-24-2004
Making Sense of Analytic Applications Summary
Now that you’ve warehoused the data – Who do you want to analyze it?

Topics: Analytics, Business Intelligence, Performance Management, Data Acquisition and Delivery, OLAP, Query & Reporting

by Bill Inmon | 0 comments
06-17-2004
Who's Responsible for the Corporate Information Factory? Summary
Rather than a war between the business units and the central technology department, let’s do it together!

Topics: Data Warehousing, Best Practices, Information Management, Data Marts, Architecture, Corporate Information Factory

by Jonathan Geiger | 0 comments
06-17-2004
Iterative Development Summary
Some speakers continue to promulgate the “Big Bang” theory that a data warehouse must be built as a single project. Maybe they are simply misinformed or have their own agenda.

Topics: Data Warehousing, Best Practices, Information Management

by Bill Inmon | 0 comments
06-17-2004
The All in One Data Warehouse Summary
The push to combine real-time on-line processing and OLAP or to combine exploration and data mining with data warehousing will cause problems with transaction guarantees and integrity of data.

Topics: Data Warehousing, Best Practices, Data Mining and Statistical Analysis, OLAP, Real-Time Enterprise

by Bill Inmon | 0 comments
06-10-2004
Who is Going to Use the Data? Summary
Bigger isn't always better! The value of data warehouses is determined by real usage not volume.

Topics: Data Warehousing, Information Management, Data Mining and Statistical Analysis, Query & Reporting

by Bill Inmon | 0 comments
06-10-2004
Data Mining – Seven Years Later, Lessons Learned Summary
The 21st century approach to data mining and survival analysis

Topics: Information Management, Best Practices, CRM, Data Mining and Statistical Analysis

by Michael Berry | 0 comments
06-10-2004
Assessing BI Readiness: The Key to BI ROI Summary
BI readiness assessments are being used at the front end of business intelligence (BI) projects to determine the degree to which a given organization is prepared to make the changes that are necessary to fully capture the business value of BI.

Topics: Information Management, Best Practices, CRM, Data Mining and Statistical Analysis

by Nancy Williams, Steve Williams | 0 comments
06-01-2004
Capacity Planning for the Data Warehouse Environment Summary
Capacity planning is essential for all data warehouse environments. Data warehouses grow at high rates and must be managed to keep budgets under control.

Topics: Data Warehousing, Best Practices, Storage

by Bill Inmon | 0 comments
06-01-2004
Customer Satisfaction: The New Imperative Summary
It is no secret that, during the go-go years before the technology bubble burst, relations between enterprises and the software technology vendors that serviced them were frequently strained.

Topics: Data Warehousing, Best Practices, Storage

by Bob Butchko | 0 comments
05-27-2004
Information Agility Summary
There are many reasons that people choose a data warehouse environment. These may be the relief from the pain of legacy systems, a need for historical and integrated data among others.

Topics: Data Warehousing, Best Practices, Information Management, Data Modeling and Design

by Bill Inmon | 0 comments
05-27-2004

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