IQ Research at Dublin City University - Business Informatics Research Group

--Transform Data into Business Value--



In the current economic situation information supply is more crucial than ever, but today the quality of information and data is worse than ever. In a recent survey, the data warehousing institute estimates that quality problems cost U.S. business more than $ 600 billion a year. Similar, Larry English states the business costs of non-quality data, including irrecoverable costs, rework of products and services, workarounds, and lost of missed revenue may be as high as 10 to 25 percent of revenue or total budget of an organisation. Thus, recently researchers and practitioners have realised the importance of information and data quality. But however, as the data warehousing institute’s survey and many consulting projects indicate, the problem still remains: How to ensure high-level data quality and information quality?

In order to achieve and manage high-level data and information quality in information systems, the research program within the Business Informatics Group focuses to establish a comprehensive method for proactive data and information quality management, which can be adopted in practical settings.

 MITIQ Program


--Information Quality at MIT--

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IQ (Information Quality) is a survival issue for both public and private sectors: companies & governments with the best information have a clear competitive edge. MIT is dedicated to working with government and industry to improve their ability to capture and harness the power of their information. To this end, MIT provides multiple IQ programs and initiatives, which equip organizations with knowledge and tools that improve the quality of their information. These IQ programs and initiatives are based on rigorous relevant research, analysis, and practical experience.

 TDQM Program

--MIT Total Quality Management Program--

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In recent years most corporations, large and small, have initiated Total Quality Management (TQM) programs with goals that include 100% satisfaction for customers and no product defects. Quality management programs have been a key factor in the success of companies in many industries.
Often TQM programs and other strategic corporate initiatives are not entirely successful or even fail because the data used to monitor and support organizational processes are incorrect or incomplete or otherwise faulty or inappropriate for a given application. Anecdotal evidence and a growing literature point to data being defective at levels of 10% or more in a variety of applications and industrial contexts, including sales-force automation, direct-mail programs and productivity improvement programs.

MIT's Total Data Quality Management (TDQM) research effort has been grown from industry needs for high quality data. The overall objective of this program is to establish a solid theoretical foundation in this embryonic field and, from this work, to devise practical methods for business and industry to improve data quality. We will develop tools and other capabilities necessary for data quality management in the technical, economic, and organizational phases of business operations.



 

 
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