Data quality techniques and best practices
- May 29, 2020
Talend users from Covanta and AutoZone provide insight into data management challenges amid growing data complexity at the Talend Connect virtual conference.
- January 23, 2020
With the acquisition of Waterline Data, Hitachi Vantara is bringing new data catalog capabilities that will expand the Lumada Data Services and DataOps portfolio.
- March 21, 2019
Machine learning will bring change to analytics and data management, said data luminary Michael Stonebraker. Others agree managing such change will take special effort.
- March 15, 2019
Many data professionals have yet to solidify traditional data management practices, but they have a new set of challenges to overcome to ensure data privacy and avoid misuse.
- October 05, 2017
At the Strata conference in New York, IT managers detailed steps they're taking to improve data quality in their big data environments in order to help ensure analytics accuracy.
- September 06, 2017
Breitburn Energy Partners employed data quality tools to address the business pain of bad data, using the software to give end users the means to fix data quality issues themselves.
- February 03, 2017
The head of Kaiser Permanente's data governance program says data stewards hold the key to the initiative's success, and he offers advice on managing data stewardship processes.
- July 15, 2016
Forces at work in data management have led to the advent of the chief data officer. The role of the CDO and more is discussed in a Q&A with consultant Joe Caserta.
- January 29, 2016
Data governance managers who spoke during an online conference said that tracking business-oriented metrics on data quality improvement is a key to success in governance efforts.
- February 28, 2014
In an interview, author and data quality architect Laura Sebastian-Coleman discusses steps organizations should take to improve data quality levels.
- July 28, 2012
Ensuring that business users follow corporate standards when entering and updating data is vital to the success of data quality improvement efforts.
- June 12, 2012
Data accuracy is critical in technology-driven business processes, making it a must to involve business users in data quality efforts, analysts say.
- March 28, 2012
IBM customers Nationwide Insurance and Cardinal Health reveal five rules of thumb they learned while implementing highly ambitious data governance programs.
- March 08, 2012
IT professionals from Sallie Mae and Fannie Mae offered insight on data governance challenges and tips on how to overcome them in separate sessions at two recent conferences.
- July 29, 2011
In an interview, Michele Koch discusses the data governance program she leads at Sallie Mae and provides insight on key governance best practices.
- June 24, 2011
Building effective processes for managing data throughout its lifecycle can help maximize the value of information. But that’s easier said than done.
- June 22, 2011
Enterprise information management aims to optimize the use of data as a corporate asset. But setting up an EIM program presents a variety of challenges and potential missteps to watch out for.
- June 14, 2011
Consultants and IT pros offer tips on creating highly proactive data quality management strategies – and on overcoming the challenges that presents.
- December 14, 2010
All the reporting tools in the world mean nothing if you’re using dirty data. Learn how to select the right data quality tools and management software for your organization.
- November 01, 2010
Get expert advice on data governance best practices, including tips on how to structure a data governance program to best fit your organization’s governance policies and needs.
- October 28, 2010
Learn about the issues that a data governance framework is designed to address, and get a list of questions to consider when designing the framework for a data governance program.
- August 30, 2010
Get expert tips on calculating data quality metrics to document the financial impact of poor data quality and help build a business case for a data quality improvement program.
- August 27, 2010
Data governance programs are often overlooked, pushed aside and just plain ignored through a lack of executive interest and funding. But some technology professionals are making the most of the situation.
- November 12, 2009
The open source data quality market is still in its infancy, but a handful of vendors offer adequate data profiling software, according to Gartner.
- March 04, 2009
Master data tables seem to be particularly sensitive to the limits of normalization, and Malcolm Chisholm believes that a reflexive attachment to normalization can be counterproductive.
- February 25, 2009
Jeff Pettit explains how to reap the benefits of highly productive data for years to come.
- February 17, 2009
The hard reality is that always problematic and often costly data anomalies do exist. Will Dwinnell explains why it is helpful to have a tool to automatically ferret out a substantial fraction of those anomalies.
- November 05, 2008
Listen to IBM's Steve Mills discuss Big Blue's Information On Demand initiative and why he thinks it's in a better position to help customers than rival Oracle.
- July 21, 2008
Learn how data stewardship fits into data governance and data quality management programs, from Jill Dyché.
- June 05, 2008
An effective master data management project starts with managing people and processes, including data governance. The technology is secondary.
- May 27, 2008
Data quality problems can't be fixed until they are identified. Learn how a data quality assessment can help pinpoint data quality problems.
- September 20, 2007
Carried to an extreme, quality can be a real enemy to progress.
- June 21, 2007
This article considers two challenging aspects of enterprise information management: key data entity ownership and data quality management.
- January 24, 2007
Data quality tools and processes have changed dramatically, so keep up with the latest data quality trends. Renowned expert Larry English provides timely advice for your data quality strategy.
- December 18, 2006
Manually verifying data accuracy is bound to introduce errors. Therefore, sampling can be used to derive some conclusions about a large body of information by selecting a smaller number of instances for the purposes of inferencing.
- September 21, 2006
Data confidence, a critical management success factor, is not automatic. How do you attain it?
- March 22, 2005
With a Data Governance Entity in place and quality raised as a top-tier issue, the question now becomes how to fix data quality problems.