Many organizations face the challenge of accurately managing their data governance initiatives due to the lack of a centralized infrastructure that enables the management of data policies and overall data management process automation.  Kalido’s release of their Kalido Data Governance Director aims to do just that.  By creating a unique tool for companies to use and to develop a structured approach to data governance through the management of data policies, they hope to provide their customers with a complete data management solution that meets their customers’ needs from master data management through data quality.

In general, because data governance is increasingly gaining importance within the marketplace, mature DG companies are looking for standardized practices to implement to make the DG process easier and automatic. Currently, organizations are left to manage their own projects independently and even though resources exist to help guide effective management of these initiatives, the software component is sorely missing.  This means that Kalido may have hit on a trend that is emerging in relation to integrating the process side into the governance and toolsets required to automate how data governance is managed within the organization.

The next phase will hopefully be moving downstream so that more organizations can take advantage of data governance software.  With a $200K entry point, organizations will have to justify an extra expenditure in addition to their current BI, MDM, and data integration costs and add DG to the mix.  Overall, it seems as if the concepts surrounding data management are slowly becoming integrated to provide companies with the opportunity to centralize their approach to BI, MDM, and broader data management through the adoption of formalized data governance processes. This means that eventually, the piecemeal approach to data management initiatives will transition towards a centralized infrastructure that includes all aspects of data management.  Kalido’s new announcement definitely provides industry insights into the increasing importance of developing an automated approach to DG that takes the guess work out of managing data policies and how they relate to overall data management initiatives.