How does one focus on data quality when limited budgets encourage the management to cut corners with IT? How does one talk of data quality when the hype around the Cloud and its cost effectiveness adds fuel to the fire of their belief and they are convinced that just transmitting data to the Cloud will ensure quality?
The truth is that there can be no compromise with data quality whatever the circumstances. Good quality data enables optimization of business applications and decision making efforts. It is a business imperative. The data quality program will have to be thought through more rigorously and implemented meticulously so that the recession does not erode competitiveness and reduce revenues. You will have to learn to do more with less.
Data quality is a necessity, rather than a luxury, in the following areas:
- Transactional customer facing systems
- Business intelligence systems
- Enterprise performance management systems
- Financial reporting and compliance
- Data migration, support and application reconciliation
- Supplier management system
Poor quality data can create far-reaching negative effects on the business! Data quality ought to be a given.
Cloud service providers realize that data quality is not an exciting area in management. It does not capture and hold the attention of IT professionals and business leaders in the way that Cloud computing or virtualization commands attention. But, without data quality all other programs, including data transmission to Cloud repositories can become meaningless. The devil is in the details; and data is detail for businesses around the world.
Cloud services recognize that data quality management is a good practice and it should be enforced automatically enterprise wide. Organizations should have a hard look at their data for accuracy for the devil is in the details and the business can fail if the quality of data is poor. Data cleansing routines should kick start at every stage to ensure that only quality data is delivered to the end user. Data consolidation should be given and scattered information should be brought together for optimization of services and their delivery.
However, it should be remembered that data quality is not a technological implementation. Quality is about managing the asset properly and wisely. It is about integrating the knowledge of IT with the demands of the business and coming up with a solution that suits them both. Cloud implementations do not make exceptions to this rule.