December 7, 2022

Data is an invaluable commodity in today’s world of business, no matter if it’s a big corporation or a small business that you run from your home. Data is everywhere. It should be collected, structured, managed and oversaw to maximize its efficiency. In other words, data needs governance.

Data Governance: a Definition

Before we get into the details of data governance, let’s define what ” data” actually means. It is information that is stored or processed on a digital device, such as a server, computer database, tablet, smartphone, or laptop.

Once we’ve covered the basics we can move on to discussing data governance. Data governance covers all practices, policies, procedures, roles, standards and metrics that are designed to assist an organization in achieving its goals. Data governance is responsible for ensuring that enterprise systems are available, reliable, secure, and usable.

Data governance shouldn’t be confused data management. Data management involves managing an organization’s entire lifecycle. Data governance — which includes nine additional components such as data security data cleansing, data quality, database operation, data quality and data warehousing – is a core component to data management. Data governance is the process of creating data policies and procedures. Data management is what enables the collection and use of data to make decisions.

Data Governance Goals

In today’s data-intensive world, a solid data governance plan is mandatory. It’s no exaggeration when we say that any business without a data management strategy is at great risk. Here are some goals of a good, healthy, and efficient data governance program:

  • Assure that the company is able make consistent, confident business decision based on reliable data
  • Increase data security through data ownership guidelines and other responsibilities
  • Make data a currency to increase profits
  • Compliance requirements can be met and penalties avoided by documenting the data asset lineage, data-related access controls and compliance requirements.
  • Establish consistent rules for data use
  • Reduce overhead costs
  • Data will increase in value
  • Communication between internal and extern can be improved

Data Governance: Benefits

The line between benefits/goals is often blurred, because the met goals end up being advantages. Without risking redundancy let’s discuss the benefits associated with data governance. There may be enough distinction for it to be justified.

  • The organization’s information gains in value
  • There are clearly defined and improved standards in data policies, systems, processes and procedures
  • The company achieves greater transparency when it comes to data-related activity
  • The business’s revenues rise and costs fall.
  • A company’s competitive advantage is due to the fact that valuable data drives commercial success today’s in digital world.
  • A good platform for data governance facilitates the use big analytics.
  • Data governance helps to improve cybersecurity, protecting corporate assets and assets from theft and tampering

Data Governance Challenges

Although enterprise data management seems obvious, some companies resist this concept. Here are some problems with data governance.

Budgetary Concerns

It can be hard to convince those responsible for the purse strings of an organization to spend financial resources on something they don’t have to immediately face.

Dichotomy among Flexibility & Standardization

It’s difficult to find the right balance in between adhering a set of governance guidelines and being flexible. Where do you draw a line?

Business Culture.

Data governance is dependent on an open corporate environment that embraces new ideas.

Perceived Difficulty.

Skeptics within an organisation may conclude that data governance can be difficult to implement and reject implementation.

Data Governance Framework

Data governance frameworks comprise a number of data processes, technologies, as well as organizational role delegations. They are intended to bring the company together, and ensure everyone is in the same data direction.

A data governance training plan that is well-constructed includes a clearly defined mission, goals, success definition, responsibility delegation, and accountability for each function within the program. This framework should also be documented and shared among all members of the organization.

Data Governance Principles

  • There are eight fundamental principles to data organization.
  • In order to have integrity and honesty in the way they deal with each other, everyone involved in data governance needs to be honest. This honesty can be demonstrated by being open to discussing all aspects of data-related decision making.
  • Transparency in data governance is essential, especially with regard to the timing and content of decisions and controls.
  • All data-related controls, processes, and decisions must be auditable.
  • Define who’s responsible for data-related cross-functional controls.
  • Define who will be responsible for data stewardship activities involving groups of data contributors or individuals.
  • Programs must provide checks and balances for technology and business teams as well as those who collect and create data, information users, information managers, compliance specialists, and others who establish standards and guidelines.
  • The data governance programme must facilitate enterprise data standardization.
  • The program must support proactive and reactive activities to manage change for the reference data values as well as the structure and use of metadata and master information.