It's actually all about you!
Just like other great start-up stories, Prodago began in its founder's garage in 2013. Mario Cantin had a vision: help organizations like yours address Data Governance differently and drive more value from it. So, he set out to solve the missing link by launching Prodago.
Be the go-to technology partner for organizations wishing to leverage data and analytics to the fullest while limiting their exposure to quality, compliance and ethics risks.
Instead of following a top-down and heavy data governance method involving committees, glossaries, stewards and the likes, Prodago developed something called Lean Data Governance, a bottom-up, context-based and pragmatic approach. By developing a SaaS solution to operationalize this framework, Prodago would connect all the dots between the data and the need for quality, compliance and ethics.
As we fast-forward to today, every organization is trying to apply Advanced Analytics and Artificial Intelligence to solve long-standing business problems. Through consulting with many organizations on lean data governance, Prodago's leadership established that data risks and regulations are not about the data itself but instead formed by their application to solving business problems, including analytics, machine learning and AI. In each case, mitigating the resulting exposure can be achieved through specific sets of operating practices.
Provide executives with the confidence that they are fully aware and in complete control of all their data risks, as they push to apply Advanced Analytics as widely as possible in their organization.
The upcoming Prodago platform version 2.0 introduces the Lean Data and Analytics Governance Operating Model. It will enable organizations to assess the state of data quality and analytics governance, identify all analytics and AI data risks, and generate a clear roadmap to bridge the gap by putting all required operating practices in place.
Enabled with the ability to monitor its implementation and, ultimately, the execution and accountability of the operating practices, each organization will be able to trust that all their data risks are covered. They will be able to confidently increase the speed and breadth of data and analytics applications while trusting that they are in complete control.