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“Today’s organizations need to urgently approach the data integration and quality problems; they are seriously affecting the liability of the support solutions in decision taking” Says the IDC analyst.
BI solutions and Enterprise Planning have still not achieved to be recognized as a better mean of strategic use in organizational information. The data combination of the multitude of sources; transforming them in information that hands a liable vision of the performance of the business processes; and assures that they arrive to the right people in the organization, the right information in order to make consistent decisions.
With this in mind, and with the understanding that BI and EP should be based upon data quality, it will results promising and with a futuristic vision to approach data quality problematic as part of its implementation of BI & EP. We all aim to have the security of having the best data quality possible in which we are based when making critical business decisions.
How can technology help the data quality assessment process?
The data which is charged in the warehouse is normally infested with various types of errors. These are the most known errors:
Completeness: Is all the necessary data present?
Conformity: Which data is stored in a non-standardized format?
Consistency: Which values produce conflictive information?
Duplication: Which data entries are duplicated?
Integrity: Which important data has lost the relational link?
Opportunity: The age of the data with the requirements of the users?
The Content, Structure and Consistency errors are of basic treatment. It can happen that the data physically does not concord with its metadata: for example, when you have an alphabetic value in a defined area to support a numerical value. In other words, the data is invalid. Secondly it can happen that the data is invalid but correct. For example, the postal address can be in the correct format but it currently does not correspond to any known address.
How do we support your organization with the problematic data quality assessment?
Through what we call a quick analysis on data quality, we run the analysis and discover the principle problems, focused toward dimensional tables and the tables based on facts that are supporting the systems that provide the information for decision taking. This assessment takes between 1 and 2 weeks.
The included topics are:
- Analysis and discovery of data quality, in order to increment the knowledge on the disposition of data and quality problems
- Structural quality of the data this allows the risks to be appreciated and to stimulate the required budget for the development of the data quality project.
- Establishing a scorecard of the data quality where the quality metrics are defined in order to have a control point and advances, as well as the design with technology the strategy for the development.
- Assessment report at this point a report is handed over with metrics, a basic process and a recommended strategy for the development of the following steps.
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