DQ Framework

Applying Data Quality measure is not a new practice, and many organization have implemented some sort of quality procedures in place which in most cases born ad-hoc within the projects, which ultimately end-up with multiple data measure systems running across the organization. Another scenario is that there is no data quality measures in place, which creates an unreliable data ecosystem, from the source to its downstream databases.

Why DQ framework?
There is an urge for creating a generic framework which would be available across organization for projects, facilitating an efficient and effective data validation procedure and creating a trustworthy Data Quality reference among the stakeholders and team members. It would help establish a standard to implement quality checks across projects, there-by creating an effortless but yet an effective DQ Framework strengthening the Data Quality process of an organization.

**** Our motto is that every organization reports on trusted data. ****