Organizations are spending vast resources in harnessing their data to drive business growth. However, the swelling information volumes have left them struggling to get control over their assets. Enterprises need to take cognizance of the critical data governance elements that form the basis of information management while recalibrating their strategy. An optimized monitoring program improves operational efficiency and the quality of the decision-making. At the same time, it lowers legal risk by ensuring the alignment of the data management program with applicable regulations. Businesses need to define a clear and unambiguous data governance approach. Even those organizations that have an efficient monitoring mechanism need to change their strategy as they onboard new technological solutions. Here we are discussing the core elements which are needed while integrating new technological solutions or platforms.
1. Well-defined Policies And Procedures
The monitoring scheme is implemented to keep a close watch on the information management initiative and ensure that the business objectives are fulfilled. Every single tool, process or activity must be included in the governance plan only if it aligns with the business’ strategic goals. When you integrate a new platform or technological solution to fulfill your requirements, some new policies and procedures need to be formulated. Most organizations switch to new tools to handle their increasing data volumes. The introduction of advanced solutions empowers organizations to conduct more interactive and detailed evaluations. The scale and complexity levels of the analyses increases and some vital processes like quality assessment need to be automated to keep the entire workflow in an optimized state. Enterprises need to create new standards and policies which are in accordance with the new platform. The most important point to note here is that nothing should be considered as set in stone. All the policies and processes need to evolve with the changing requirements and framework.
2. Clearly-established Roles And Responsibilities
The introduction of new platforms will lead to a change in the associated roles and responsibilities as well. Businesses that are implementing governance for the first time do not face too many problems as they are building everything from scratch. However, things can get tricky for large enterprises that have dedicated organizations whose only objective is to support the information management program. They need to understand how their duties will be affected by the implementation of new tools. The scope of their work grows and so does the nature of processes and assets they have to monitor. All these dynamics must be understood to clearly redefine the roles and responsibilities of various users. The skills of the stewards will also need to be upgraded so that they can work with the new tools.
3. Selection Of Appropriate Technological Tools
It will be wrong to treat governance as a purely technical program. However, technological tools are one of the most important data governance elements. You cannot effectively implement the monitoring scheme without the correct solutions. Enterprises are increasingly turning to automation to handle their data processing and analysis needs. Automation is being applied to every stage- discovery, ingestion, interpretation, and enrichment of the evaluation process. Advanced analytics solutions conduct their process in real-time and generate instant reports. The governance tools need to be integrated with the analytics platform so that the stakeholders can get a consolidated view of data lineage and quality. Make sure that appropriate solutions are used and replace tools wherever necessary. All the users who will work with the tools must get proper training so that they can conduct the procedures smoothly.
4. New Approach To Data Cataloging
Data cataloging is a critical aspect of any information management program. Organizations depend on the process to get a complete view of their assets and understand their relevance. Traditional tools support a limited range of metadata assets. As elements become varied in nature, you need to recalibrate your approach and switch to new tools. In case, elements are defined through different notations, you need to adopt a semantic approach that gives more importance to business ontologies. Cognitive techniques must be introduced to capture metadata as well as to establish the relationship between different assets. Finally, get the business and IT users together to formulate your new cataloging approach so that a smooth workflow can be initiated.
5. Knowledge Of Legal Regulations
Enterprises need to be aware of their legal compliance requirements. Data security has become a prime concern for organizations as well as governments. More and more jurisdictions are looking to frame and implement data privacy laws. In order to mitigate legal risks, you need to be aware of all the applicable legal regulations. Make sure that your governance plan includes the measures necessitated by the laws. Many new tools have in-built compliance mechanisms for popular laws like GDPR. Implementing such solutions will help you in managing your risks easily.
Information management projects evolve constantly with growing information and changing business requirements. Enterprises must be aware of the core data governance strategy elements while replanning their initiative to create an optimized program.