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Data Quality Channel

Channel Sponsored by
DataFlux

If there is a single pitfall that undermines any given data management initiative, it is most likely to be found in the realm of data quality, a requirement for sound decision-making. Whether in combination or by themselves, databases are almost certain to contain entry errors, multiple common entries and other redundancies that inevitably lead to incorrect or incomplete identifications of customers, products and locations. Thus, data quality is a critical prerequisite to any BI initiative that would otherwise skew or obfuscate meaning in the reporting and analytic outputs of databases, reporting tools, dashboards and scorecards.

Articles

Build a Powerful Business Case for Data Quality with Metrics

Without quantified measurements few business managers appreciate the extent to which data quality issues impact their companies

The Sad State of Data Quality

Results from the Information Difference survey document initiatives and the state of data quality today

Data Cleansing in the Cloud

This article addresses the challenges and many of the common questions that companies have regarding data cleansing in the cloud

Rely on Data Quality to Survive

How to utilize the principles of data quality to improve business intelligence and maximize sales opportunities

BI: Only as Good as its Data Quality

The assumption in business intelligence is that the data from which the information is derived is correct, but this is not always the case

Columns

What is Different about Data Integration Project Management?

Understand special challenges and dependencies on source systems for feed timing and data quality

More Data Quality for Confident Operational Business Intelligence

A continuous improvement approach to operational BI dictates that the root causes - not just the symptoms - of the problem are addressed

Data Quality for Operational BI

Operational BI can only be successful if data meets quality expectations and is understood by the business community

The Talents of a True Data Steward

Technical, interpersonal and positional skills are required to manage data as an asset

Four More Sources of Poor Data Quality

How to develop a strategy to identify and understand the issues

Books

Data Quality Assessment

By Arkady Maydanchik

Data Mining VIII: Data, Text and Web Mining and their Business Applications

By Edited by: A. Zanasi, C.A. Brebbia and N.F.F. Ebecken

Data Quality Assessment

By Arkady Maydanchik

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