Data governance is a process that ensures proper management of all data assets within an organization. It ensures that the available data can easily be trusted and that people will be responsible if any adverse event takes place because of a low quality. With a data governance system in place, there would be an entire team of individuals whose sole job would be to fix and prevent data issues, which would help the organization in becoming more efficient.
There are several methods in which data governance can be implemented. Most of the models utilized are fixed, but have already been proven to work in the past cases. Though fixed models are common even today, they are not that great an option because they do consider the capabilities of your organizations, the total available resources or the limitations of your budget. A much better approach is to implement a system that not only caters to the needs of data governance, but also suits your organizational abilities with regards to execution and sustenance.
Here are the main steps which are involved in approaching data governance in structured manner so that resulting solution is tailored to your business needs.
Build a distinct vision for your organization in terms of data governance and also define the scope. Make sure both of these are realistic and that your organization has the capabilities of fulfilling them.
Define all the data standards for your organization. Each standard should comprise of a rationale, benefits, definitions and metrics. The rationale is an explanation for the reasons of the standards existence; the benefits are the results that can be achieved if the standard is implemented; the definitions state the quality level which must be maintained for the benefits to become noticeable and the metrics are indicators that assure the required results are being achieved.
Build a team whose responsibility will be to manage the standards which were defined in the previous step. Delegate all tasks related to data governance in a proper manner and ensure there are no duplicates. Also determine the internal processes with which the activities shall be managed and specify modifications to external processes that can affect data governance.
Specify an individual or a group of people and provide them with ownership of the data standards. They will then develop the road map to data quality.
The data quality road map is a tool to which the current level is provided. The model then measures this current level with the quality level defined in the data standard. If a gap exists, suggestions are made to bridge it and techniques are also recommended which would maintain the quality level.
Specify resources which will handle those roles that are mandatory for operating the current compliance measurements. These roles also control the activities suggested by the road map.
In this section we will discuss: