2 Data Ownership Approaches Advised By Data Governance Consulting Firms

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The importance of data for evaluating the performance and finding new methods to grow the business is understood by modern enterprises. Engaging data governance consulting firms to establish a framework for management of the information being generated by an organization has become standard practice but the relationship between data and the company is not simple and possesses various layers. One of such aspects is the “ownership” of the assets with some organizations happily accepting the practice of assigning ownership roles to individuals while other entities do not believe in the theory. Experts providing data governance consulting services suggest two possible approaches and both of them will be discussed here.

1. Assigning Data Ownership Roles To Individuals/Teams

Many organizations adopt the approach of assigning the ownership of different data assets to individuals or groups and specifically define their roles and responsibilities. While the company owns all the information these “ownership” roles are created only for the convenient management of all the data assets. Appointing Data Owners or Data Stewards is helpful in meeting various objectives, like some organizations may use the appointment for efficient access management while another company would use it for enterprise compliance. The process involves the request from one entity for access to a piece of information which is approved by the data owner and granted by a technical resource. Let’s stay a staff member asks for sales figures related to an item for a particular time period which is then approved by a data owner who can be the member’s manager. The data owner will then intimate the technical resource like a database about the approval which then provides access to the staffer.

This whole process must be in complete synchronization with the data management framework implemented in the corporation. Besides, it must also include a mechanism for documentation and maintenance of all requests and permissions to fulfill all compliance requirements and achieve the business targets. It is also essential to understand the difference between a data steward and a data owner. A data steward possesses expertise in the field of data quality and is responsible for maintaining the quality of an information asset throughout its life cycle at the enterprise. A data owner, on the other hand, is usually an individual holding a senior position in the management, and the steward is dependent on him/her for making all the modifications necessary for maintaining the data quality. The enterprise must clearly define the roles and responsibilities of both the data stewards and data owners to remove any chances of ambiguity and proper running of the data governance programme.

Ownership/ stewardship accountability is generally decided according to the type of data and usually, a steward is assigned the responsibility for one or more data types. There will be different data subject areas related to a data type like clients, products, vendors etc. and relevant data elements are categorized together under a single subject area so that they can be managed efficiently. Another important aspect while defining ownership/ stewardship is data flow and it is impractical for organizations to assign accountability for only a single element or subject area because of complicated data flows. Good data governance programmes solve the problem by designating accountability for only a few sections of the data flow to individuals or teams.

2. Delegating Federated Responsibilities To Personnel

The information in an enterprise keeps flowing between various entities and becomes a part of different processes which leads to it getting stored and transformed by many information technology tools and systems. The same data element can be found in various data feeds, information products, reports etc. While it is easier to follow the journey of an information element throughout its lifecycle across various data flows in small organizations, it will not be possible to do the same in a large enterprise with complex and interconnected data flows. Data governance consulting experts do not recommend the assigning of data ownership in such cases and instead suggest federated delegation of accountabilities of data assets.

The first step of this approach involves documentation of the data lineage which is the path that a specific element takes from its creation to its arrival in a particular report or system. It is followed by the delegation of responsibilities of various segments to data stewards and data custodians. This method needs a central data governance office or team that takes the initiative of putting in place the processes important for proper data management and ensuring the sharing of data assets between the business and technical departments.

Federated responsibilities assignation in itself can be quite a hard job and resources may feel burdened with additional liabilities which underlines the importance of data governance office who has to ensure that this does not happen. Even though it has been mentioned that data lineage documentation is the first step but in case the data flow is still continuing then the first step cannot be conducted and instead accountabilities have to be assigned first. The central authority must also designate a point person, a data owner or a data steward who is familiar with the data flow so that he/she can assign responsibilities for each section of the flow. This approach is definitely more complicated than the first option but it works perfectly for large organizations and that is why it is recommended to them.

Conclusion

Data governance consulting experts are unanimous that there can be no fixed approach towards data governance and an enterprise must conduct a thorough assessment of its structure and functions in order to identify which one is best-suited for framing its strategy.

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