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Data Quality Portal

This portal sponsored by

Companies often cannot rely on the information that serves as the very foundation of their primary business applications. Inaccurate or inconsistent data can hinder your company's ability to understand its current – and future – business problems. This leads to poor decisions that can cause a host of negative results, including lost profits, operational delays, customer dissatisfaction and much more.

An effective data quality strategy can help you better understand your business environment, allowing you to maximize profitability and reduce costly operational inefficiencies.

The goal of data management is to provide the infrastructure to transform raw data into consistent, accurate and reliable corporate information. Its foundation consists of the five building blocks of data management technology:

  • Data Profiling – Inspect data for errors, inconsistencies, redundancies and incomplete information
  • Data Quality – Correct, standardize and verify data
  • Data Integration – Match, merge or link data from a variety of disparate sources
  • Data Augmentation – Enhance data using information from internal and external data sources
  • Data Monitoring – Check and control data integrity over time

Begin with discovery; end with enlightenment. This resource portal, proudly brought to you by DataFlux and DM Review, will help you reach the goal of a unified, complete data repository (database or data warehouse) of corporate data. As leaders in the industry, DataFlux (www.dataflux.com) and DM Review support this Web site with continually updated, accurate and targeted information, so bookmark this site and visit often!

RELATED ARTICLESDATA QUALITY RELATED CONTENT

Deming, Data Quality and ETL, Part 2 :
Point 5 - Constant Improvement
By Fon Silvers
This approach requires a great deal of effort; however, the benefit of including a data quality process in the creation of an ETL application is a data warehouse that can be trusted.

Intelligent Solutions
By Lisa Loftis
Don't Blink - You Might Lose Your Vendor, Part 1

Intelligent Solutions
By Lisa Loftis
Action-Oriented Stewardship

257 more related content available. Click Here!


WHITE PAPERSDATA QUALITY WHITE PAPERS

Addressing Data Quality at the Enterprise Level
Available for download in: PDF format

Data Profiling: Minimizing Risk in Data Management Projects
Available for download in: PDF format

Data Quality - A Problem and An Approach
Available for download in: PDF format

The Essential Ingredient: How Business Intelligence Depends on Data Quality
Available for download in: PDF format

34 more whitepaper(s) available on this topic. Click Here!

Looking for other white papers? Visit the complete White Paper Library.


BOOKSDATA QUALITY BOOKS


Business Intelligence: The Savvy Manager's Guide
By David Loshin

Business Intelligence describes the basic architectural components of a business intelligence environment, ranging from traditional topics such as business process modeling, data modeling, and more modern topics such as business rule systems, data profiling, information compliance and data quality, data warehousing, and data mining. This book progresses through a logical sequence, starting with data model infrastructure, then data preparation, followed by data analysis, integration, knowledge discovery, and finally the actual use of discovered knowledge. The book contains a quick reference guide for business intelligence terminology. Business Intelligence is part of Morgan Kaufmann's Savvy Manager's Guide series.

14 more book(s) available on this topic. Click Here!


MORE RESOURCESMORE DATA QUALITY RESOURCES

View Data Quality industry events in our Industry Events Calendar.
Read product reviews on Data Quality products.
Check out Data Quality software demos.
Read Data Quality questions and answers in Ask the Experts.

Interested in receiving an update of DMReview.com editorial on Data Quality? Subscribe to our Content Alert e-mail. You'll receive a topic-specific e-mail focused on industry topics. Subscribe Here!



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