When looking at data governance, many organizations do not know how to manage their data management processes using a centralized approach. Because business intelligence, master data management, and data integration infrastructures overlap, the ability to monitor the processes associated with each in a centralized manner can be challenging. In addition, managing data through technology does not help companies understand what the business value of data is and how it relates to all areas of process flow within the organization. Consequently, data governance exists to help organizations merge business processes and the data it relates to.
Although many organizations have data governance teams that address these issues, very little exists to structure and manage these processes. Kalido’s announcement of their Kalido Data Governance Director creates a unique tool for companies to use and to develop a structured approach to data governance through the management of data policies. Some of Kalido’s solution includes:
- Providing organizations clarity on how data policies are defined and implemented
- Developing and implementing business rules across the organization
- Developing processes that help those involved in data governance define, implement, and enforce data policies
- Using data governance to help manage compliance and create audit trails
- General process automation
- Addressing data management issues – for instance data quality issues that may occur over time
In general, data governance is increasingly gaining importance within the marketplace. However, organizations are left to manage their own projects independently. Although resources exist to help guide effective management of these initiatives, the software component is sorely missing. Organizations have been left to develop their own solutions to manage their data management initiatives effectively. Kalido may have hit on a trend that is emerging in relation to integrating the process side into the governance and toolset required to automate how data governance is managed within the organization.
The ability to apply a ready-made solution as a general framework within an organization may become an incentive for broader data governance adoption. Unfortunately, this still limits the types of companies able to apply data governance software depending on budget and general maturity. However, based on the business value that this software may provide, other solutions may emerge to provide data governance functionality as well. 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.
About the Author
Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is the channel expert for BI for the Mid-Market at B-eye-Network and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at firstname.lastname@example.org. And please visit Lyndsay's blog at myblog.wiseanalytics.com.
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