Business Link

by Brenda Scholtz

In a global and increasingly competitive market, organisations are driven by information and the search for ways to transform data into true knowledge is critical to a business’s success. However, there is also a shortage of good IT staff worldwide, and this problem is compounded in South Africa due to the brain drain phenomena. This shortage of skills within companies impacts the quality of the software development process and ultimately the quality of the final product, particularly data and information quality.

This skills shortage and the pressure which is placed on the
development team to get the product delivered quickly and in an almost impossible time limits, sometimes forces analyst tasks to be allocated to programmers who do not have the necessary skills, training or experience. This then leads to corners being cut and even though the software may have a good ‘look and feel’ and may satisfy the customer’s immediate needs, internal quality problems may exist.

The existence of poor or erroneous data in databases causes the so-called “Garbage-in, Garbage-out” problem. Poor quality data results, which leads to poor quality information that cannot be trusted. These problems may not be picked up immediately and may only surface later on, often when it is too late. Failure to follow any standards or quality guidelines in the database design process will result in low quality information which brings several negative effects to business users through the loss of customer satisfaction, high running costs, inefficient decision making processes and performance.

The introduction and adoption of standards like the Capability Maturity Model (CMM) into the software process and ISO8000 for data quality, have made great improvements in software quality for many companies. Simple frameworks are available that have been customised for smaller organisations, and can be applied to business fields to appraise their levels of data quality
management.

The bottom line is that if you compromise on data quality,
particularly in the requirements analysis process, the accuracy of your data and therefore your information cannot be trusted. It is therefore imperative that your database adheres to standards and good design principles such as normalisation and referential integrity.