Organisations rely on information created from data, to run operations and to make decisions. If this data is incomplete, invalid or not compliant with business rules, you have a Data Quality problem. When unreliable data is then used by business applications, you then have an Information Quality problem. What is the difference between the two?
Let's start at the beginning and understand the difference between Data and Information:
Data problems, if they exist, are inherent in the facts about the thing and are often related to the accuracy and validity of the attribute. If a Date attribute contains 13 in the month field this is clearly a data quality problem.
Information problems are evident when the data is presented for use in a specific context. All Data Quality problems will result in Information Quality problems when the data is used by a business process. In addition, problems with the context or presentation of the data can result in Information Quality problems. For example a poorly formatted report can lead the user to misunderstand the data provided, even when the data itself is not incorrect, and this will result in issues with the quality of the information.
When a data item complies with all the rules associated with the attribute - we have Data Quality. When the right data is presented to the right person at the right time in a concise, useable and meaningful manner - we have Information Quality.
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