Introduction to Data Governance – Data Democratization, Governance, and Security

Introduction to Data Governance

Data governance is defined as the orchestration of people, processes, and technology to manage the company’s data assets by using roles, responsibilities, standards, policies, and procedures to ensure the data is accurate, consistent, secure, and aligned with overall company goals and objectives.

Today, effective data governance is a key challenge in the data and analytics space. Enhancing data quality, reliability, and access is a top priority. This provides data and analytics practitioners with a framework for effective data governance and quality in the era of Big Data. Effective governance provide guidance on establishing data governance’s scope and objectives, defining and implementing data stewardship programs, meeting data standardization and quality goals, and tracking ongoing improvements.

One of the core reasons for the formal introduction of data governance is to get the support of senior executives. Pressure to meet business deadlines on key IT programs can lead to more focus on immediate priorities and better handling of tactical business objectives. Many organizations have no budget for strategic data quality initiatives and ignore the risk of putting in place centralized teams for data administration.

Even though all organizations have different reasons for governance, effectiveness, efficiency, and government regulations are some of the common ones. Here are some of the challenges faced by organizations, which could be the reason to implement data governance at the enterprise level:

1. Inability to persuade business partners that data is a business concern, not an IT concern. Even though most business domainsagree on the importance of high and consistent data quality, most of them push back on having ownership of data, perceiving that managing data is an IT department responsibility alone. Continued IT ownership puts a middleman between the ultimate beneficiaries of quality data and the strategic decisions involving that data and hinders progress toward accuracy and insight of reporting and analytics.

2. Difficulty to adopt consistent data governance processes and policies. Without a formal governing body with both business andIT representation and a targeted scope, governance processes will fail to be adopted and benefit will be diluted.

3. Failure to come to consensus on common enterprise business definitions. Every business unit in an organization tends to viewtheir business definitions as unique rather than consistent with other areas of the enterprise. They are ingrained in the particular uses and nomenclatures in their silo with nominal concern for enterprise standards, leading to a continuation of sub-optimal reporting capabilities and an inability to get a holistic view of basic customer, employee, and vendor data, for example.

4. Inconsistent approach to data across projects. An inconsistent approach across the enterprise risks project solutions’ being at odds with one another and fails to achieve scalability, slowing down projects as tasks and documentation are reinvented for each project.

5. Difficult to define and sustain a path toward a target state of data competency. Achieving data quality, accuracy, andconsistency is a vast and amorphous objective. Organizations struggle to identify a realistic target state of data competency and the interim milestones to reach in the near- and mid-term. Without a maturity path that delivers tangible value along the way, data initiatives risk being deferred due to time and resource intensity coupled with distant payoff.

Despite any reason, the goal of data governance is to manage the data of an organization as an asset. This is done by providing oversight and creating policies, procedures, and processes. Other deliverables are also achieved by creating a framework or metrics. To achieve these goals, data governance should be incorporated into the organization’s culture and development methodologies. These goals and impacts should be measured and improved upon consistently and continuously.