Data Governance Scan

Organizations are increasingly concerned with making business processes and outcomes measurable. This has led to data being used as input for strategic decision-making. Complete, up-to-date and high-quality data is necessary for effective governance and the achievement of strategic advantages. Just as important is reliable tooling like Microsoft Purview, to support organizations to manage and govern their data. This also helps them to make better use of data at a tactical and operational level. Operations, marketing & sales, research & development, finance & risk benefit directly from the use of data to identify and provide insight into cost reductions and efficiency opportunities.

The need for reliable and high-quality data requires integrated management with a clear goal: value creation. Data Governance is the capability of an organization to ensure high data quality and availability throughout the whole lifecycle of the data in order to support business objectives. It is about managing the responsibility, quality and security of your data in line with policies and regulations. Having the right software solutions to support your organization in achieving this goal is paramount.

Data Governance is not only about the data itself, but more about vision and strategy. It revolves around people, policies and processes that enable an organization to use data effectively. Organizations adopting Data Governance recognize the importance of data as a value-creating activity and are designing data management processes to maximize the return on investment at every layer of the organization, from the strategic to the operational level, to gain advantage. Data Governance is the framework for the integral governance of data management processes. To create value from data and to expand as an organization it is important that your organization is in control of its Data.Software can play a very important role within this ongoing process. Solutions like Microsoft Purview can create the necessary insight through its data lineage options or the needed overview of complex data-related terms through the data catalog function. .

As Cegeka we developed an assessment to measure the current Data Governance maturity level of your organization: the Data Governance Scan. For this we designed the Data Governance Maturity Model, which is based on the theory of DAMA-DMBOK: Data Management Body of Knowledge.

With help of the Cegeka Data Governance Scan the current Data Governance maturity level of your organization or a specific department of your organization will be measured. We do this by doing interviews with stakeholders and key people within your organization, analyzing the available documentation and train employees. Think of interviews with the Chief Data Officer and Data Manager, but also Data Stewards, Data Specialists, IT Specialists and more. Documentation we analyze is dependent on what is available, for example a Data Strategy document, a Business Plan, Dashboards, Data Reports et cetera.

The assessment consists of four subjects with different sub parts:

• Organization:
  • Strategy and goals
  • Organizational blueprint
  • Ownership
  • Consciousness
  • Compliance
  • Information and risk management
  • Knowledge management
• Policy, standards and processes:
  • Data policy
  • Process management
  • Standards
  • Documentation and repository
  • Communication
• Data quality management:
  • Meta data
  • Solution orientation
  • Metrics
• Technology:
  • Data security
  • Systems

The results of the assessment will lead to one overall maturity level. A score will also be given for the maturity level of each of the four parts individually. After the current level has been determined, we can support you in deciding what the desired maturity level of the organization will be. We will then help to make a plan for your organization on how to reach the wanted maturity level. This plan consists of:

• Goals;
• Scope;
• Project results;
• Acceptance criteria;
• Preconditions and assumptions;
• Relationships with other projects.

The scope is important in this process because we advise not to start implementing or expanding Data Governance for the whole organization at the same time. We think it is better to start at a specific domain or department or your organization and then proceed with the remaining parts. Low-hanging fruit, like diving into Microsoft software solutions when an Azure environment is already in place, are part of the first steps into transforming the way your employees see and handle data.