Data is a valued organization asset. Data is continually flowing and changing and growing. Your organization needs to properly manage data all the time. If you have not already done so, you need to make data governance a part of the organization’s culture (not a one-time project or initiative). This blog post will discuss what data governance / data intelligence is and the importance of making it part of the culture for the organization. We will also cover the data governance continuous activities (processes, content knowledgebase, people, and monitoring).
But what is data governance?
- Is data governance a project?
- Is data governance an initiative?
- Is data governance a shared service?
- Is data governance a program?
- Is data governance a framework?
- Is data governance a process?
- Is data governance part of an organization’s culture?
Well, it is probably a bit of all of these but definitely it should be part of the organization's culture. It is a project that has no end but does involve managment like a project. It is an initiative as it needs to be a priority of the organization. It is a shared service as data governance is about helping the people of the organization much like the departments of Human Resources or Information Technology. It is a program as it often entails a team with a common objective. It is a framework as it consists of established processes and policies. And data governance involves processes to make the data in the organization’s data more accessible, accurate and understandable. It is our thought that data governance needs to be part of the organization’s culture. Check out our “Fit Data Intelligence into Your Organization's Culture” blog post.
Data intelligence consists of a data governance framework along with a data catalog and data intelligence content. The framework consists of a unified data knowledgebase that is open to data consumers and creators, data stewardship/data governance oversight, and data governance processes which includes points of engagement (for searching, discovery, referencing and requesting) as well as content creation workflows. We believe that data governance should have a customer service/ help desk approach and a just-in-time philosophy. Data governance content includes the following: business glossary, data system catalog, report catalog, data flow catalog/lineage, data requests, reference data, data quality, and data policies. The goal of data governance is to improve the value of data and to help people. Data governance is continuous with consistent improvements.
A few points:
- If possible, tie data governance to a technology project (new ERP, new data warehouse, new CRM, new reporting solution) as this will save time and resources. By doing this, individuals can immediately see the importance of data governance. See our blog post on linking data governance with technology projects.
- Like a project plan, you need a data governance plan (a roadmap) and before you can create a plan you need an assessment. Data governance must be carefully planned, so that everyone involved knows what needs to be done, when it should be done, and by who. See roadmap and assessment resources blog post for additional information.
- Do not create a data governance binder on a shelf or a digital folder that is never looked at. Check out our “Data Governance is No Binder on a Shelf” blog post.
- Set the right expectations regarding data governance. Let staff know that it is not a project, there is no end date and that data governance is evergoing. Let staff know that there will be continuous improvement to the data governance processes and content. Also that there will be training regarding data governance. Sometime, people believe that data quality would improve overnight with the implementation of a data governance project / initiative. It is unrealistic to expect data governance to be completed in one step.
- Do not expect data governance success if the discussions are hypothetical. Get down to work, look for quick wins, look for champions in certain departments, leverage on what you have already done, and look for other likeminded individuals in the organization. Getting things done about data should be part of the organization's culture.
- Data governance is often mistaken as a one-time project with a beginning, middle, and definite endpoint. Data governance has no endpoint. Project-based data governance is not comprehensive and has no continuity. It can solve temporary data issues, but it is challenging to obtain sustained data value. Projects end while processes evolve.
- Data governance involves creating content/processes, establishing data quality standards, implementing data cleansing procedures, and regularly auditing data assets for compliance. Data governance is an ongoing process that requires continuous monitoring, assessment, and improvement. Data governance provides a forum for making decisions, and makes experts available to assist with decision-making.
- Processes are part of the operational fabric of any organization. A data governance process is the documented way that your organization gathers and manages data daily. Data governance processes (such as data quality resolution) are not a single, one-time activity. Processes have no end until a new process replaces it.
- You need to have ongoing data governance process support. In the beginning, you will probably have a team focused on implementing data governance. But you need to make sure that you have a team (data stewards) in place for ongoing data governance support.
Ask yourself these questions:
- Does your organization consider data governance an IT project or an initiative by the Institutional Research department or enterprise-wide?
- Is data governance being communicated as part of the organization’s culture?
- Is data governance part of the new employee onboarding training?
- Do you have a long-term vision, supported by short-term goals for supporting data governance?
- Is data governance front-of-mind, and being used daily?
- Who is responsible for making sure data governance is a living process and continuous activity?
- What are the expectations for data governance in the organization?
- How are data governance activities supported once the data governance implementation team is gone?
Data governance is ongoing that requires continuous monitoring, assessment, and improvement. It involves the consistent update and improvement of data governance knowledgebase content as well as linking appropriate content to make it more powerful and useful. Data governance must evolve with changing business needs, technological advancements, and regulatory requirements. By treating data governance as a continuous effort, organizations can ensure the integrity, accuracy, and reliability of their data assets over time. Most organizations that successfully introduce data governance implement it incrementally.
Continuous activities include:
- Continuous Process Improvements - There are many processes in data governance such as new data requests and data quality issue requests. These processes need to be reviewed on a regular basis and improved so that they remain relevant and effective. Maybe a new request template needs to be added to make it easier for submissions. Check out our "Evaluate Your Data Governance Processes" blog post.
- Continuous Knowledgebase Improvement - As new reports and integrations occur, they need to be documented. Take a just-in-time philosophy, and only update data governance knowledgebase content when it is requested.
- Continuous People Activities such as Training and Communication - A data culture requires a commitment to continuous learning and improvement. This includes ongoing training and education for employees on the latest data tools, processes, and best practices of data governance. There is employee turnover and new situations that arise in the industry and organization (such as new compliance requirements) which need to be addressed by the organization and the data governance in the organization. New employees and new data users in the organization need to have data governance as part of their onboarding training materials so that they can be more data literate. Check out our blog post on data governance onboarding. Additional resources on data governance training and communication can be found in this blog post.
- Continuous Measuring and Monitoring - Like measuring a project or a department you want to continuously capture and measure the effectiveness and value generated from data governance and data stewardship efforts. You need to monitor compliance and exceptions to defined policies and rules. You want to enable transparency and auditability of your data governance efforts.
We hope you found this blog post useful. Data governance has no end. Start small and make consistent changes to the knowledgebase and processes. Get more people involved (data consumers and data stewards). If data governance is done right, you have set up a sustainable practice that will carry on into the future and be part of the organization’s culture. Provide employees with the training, communication, and tools, like the Data Cookbook, to do their job better.
Additional resources (videos, blog posts, recorded webinars) on data governance and data intelligence can be found at www.datacookbook.com/dg.
IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance, data intelligence, data stewardship and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.
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