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Data governance and data stewardship are two crucial terms that you can’t afford to forget if you want to derive the maximum value from your company’s data. They may sound similar, but the two terms are very different.
Effectively, data stewardship is a branch of data governance. Data governance is the umbrella term that defines the collective procedures, policies, and processes required to manage and securely share data across your organization.
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Data governance is a step-by-step process that involves finding, organizing, managing, securing, and presenting data in a way that ensures it is verified, consistent, and easily accessed by authenticated users.
So, what are the key differences between data governance and data stewardship? In short, data governance refers to a company’s overall data initiative, while data stewardship is a subsection of this initiative. Data stewards are responsible for enforcing the policies that ensure data governance objectives are achieved.
Data governance is multi-layered and includes specific focus areas such as the data quality improvement lifecycle and data access management. For each focus area, data ownership and data stewardship are required.
Data stewardship is an essential part of data governance. As we covered briefly earlier on in this blog, it concerns the implementation of data governance policies by allocating specific roles and responsibilities to a data steward, or team of data stewards.
A data steward will ensure that users are held accountable for the data in their care, maintain the efficiency of data governance initiatives, define data elements in a business, establish and maintain data quality rules, make data policies and regulations easy to understand, encourage adoption, maintain definitions and terms, and more.
However, it’s not enough to just initiate data stewardship activities. They have to be done correctly. When data stewardship is carried out poorly, the results can be at best chaotic, and worst damaging to a business.
Users will continue to create and use data that, if not managed properly, will become a burden instead of a benefit. Compliance regulations may be broken leading to huge penalties. And, the likelihood of a data breach will continue to increase over time. Data stewardship is the primary step to successful data management.
Data stewards have many responsibilities, but there are some core practices and methods that every data steward should employ as a standard.
Follow well-defined roles and responsibilities: One of the core obligations of a data steward is to allocate data roles and responsibilities. The allocation of different responsibilities in an organization enables a data governance program to roll out effectively.
When users are unaware of who is responsible for which aspects of a data governance initiative, they may well avoid using data to innovate because of the difficulties in acquiring it. This is why defining and assigning roles and responsibilities is so important.
Responsibilities can include managing metadata name standards, managing data quality issues, and answering questions from business users.
Aspire to performance incentives: Data stewards should work with well-documented and widely distributed KPIs. These KPIs must be developed by a Chief Data Officer (CDO) and tie in with reward schemes and other incentives for data stewards.
Data stewardship is usually voluntary, so businesses must launch compensation schemes to incentivize participants. However, data stewards should aim to achieve the performance targets set out by management teams.
Common KPIs include the number of critical data elements (CDE), managed business glossary terms, the amount of maintained metadata, and the quality of metadata.
Integrate with the data team: Because data stewards are located in numerous departments and only partake in their stewardship activities on a part-time basis, there can be some distance between them and the data team.
Although it is the role of the CDO to integrate data stewards with the data team, data stewards themselves should make a conscious effort to do so independently. They must be fully aware of any changes that affect company data and, although primarily located elsewhere, become part of the data team.
Create a stewardship committee: Just as data stewards must integrate with data teams, so too must they integrate. The same issues with displacement affect the way that data stewards communicate with each other.
The best way to do this is to organize a data stewardship committee and meet regularly to discuss company data issues. These issues could concern data policies, standardization, business terms and definitions, adoption techniques, and other collaborative processes that encourage data governance activities in an organization.
Make data policies transparent: Transparency is key to data governance adoption, and adoption en masse will enable your organization to grow through data-driven decision-making. Every data policy developed and distributed by the data stewardship team should be done so transparently, at every stage in its life cycle.
Encourage adoption of data governance initiatives and nurture a corporate culture: Data stewards have always been responsible for enforcing data governance policies. Today, it is equally important that they show users the value of these policies.
This presentation of value doesn’t just stop with business users, it extends to management too. It is best practice for a data steward to work towards making data governance a well-accepted component in their organization's corporate culture.
Document everything well: Data stewards must document all decisions and updated policies so everyone in an organization has access to this information. This includes stakeholders, executives, and regular business users.
This documentation could be in numerous places. The most common of these places include metadata repositories and business glossaries.
Data stewards have several critical roles and responsibilities. However, four key responsibilities encapsulate the role of a data steward as a whole.
Many people may be a little confused when it comes to understanding the differences between a data owner and a data steward. Some users may be surprised to learn that any difference exists at all.
Both data owners and data stewards play an important role in the governance of a company's data, but exactly what role they play differs. A data owner is a senior stakeholder and is usually hold's a superior position in a company.
The data owner is the person who is ultimately accountable for the quality of the many data sets they oversee. On the other hand, a data steward can be from any department in a company and is not accountable for the data but responsible for enforcing governance policies.
Whether or not you need to hire both is dependent on the size of your organization and the breadth of your data governance initiatives. Data ownership is a significant commitment and the logistics required to maintain data stewardship teams incur notable expenses.
Data stewardship is essential for data governance, regardless of the size of your organization and the sector it operates in. However, it isn’t enough just to define and enforce policies. Data stewards need to work together harmoniously and encourage participation in a data governance initiative by explaining and demonstrating the ROI.
All data management processes are simplified when there is a data governance tool in place. The OvalEdge data catalog is one of the most advanced data governance tools available. Using OvalEdge, data stewards can circulate data policies, create business glossaries, and stay on top of data governance decisions.
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