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Even though the competence of Data Quality has been around for over a decade now – why does it continue to stay nascent and aspirational rather than a reality with tangible value for a lot of organizations in spite of having a fair spectrum of maturity as far as being data-driven is concerned.
In my session – I want to discuss with practical examples and scenarios – the common pitfalls that prevent Data Quality reach its full potential for an organization.
- Maturity path for Data Quality
- Common pitfalls of Data Quality implementation
- Strategy and focus areas for Data Quality
- Practical examples, business scenarios
- Data Quality Competence – skill set