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How do you set data ownership policies?

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Data ownership policies are essential for effective data governance, as they define who is responsible and accountable for the quality, security, and usage of data assets. However, setting data ownership policies can be challenging, as it involves identifying the stakeholders, roles, and rights involved in data management. In this article, we will guide you through some steps to help you set data ownership policies for your organization.

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1 Assess your data landscape

The first step is to assess your data landscape, which means understanding what data you have, where it comes from, how it is stored, and how it is used. You can use data inventory tools, data catalogs, or data lineage diagrams to help you document your data sources, flows, and dependencies. This will help you identify the data domains, data types, and data elements that need ownership policies.

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Scott Peachey

Global Data Executive | Content Creator | Leader | Strategist
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When your assessing anything related to ownership, two of the most critical pieces are more focused on the people/process part, versus using a technology. Identifying what data needs ownership sounds simple, but can get our of hand quickly. Are you only determining ownership at source? What about reports? These are important questions to consider when determining your ownership model. Once you layout the 'what' is being owned, develop robust roles and responsibilities of WHO will be doing those activities. Technology enables these things to happen, but don't solely rely on it fixing the ownership problems.

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Mark McQueen

I help data leaders navigate their data excellence journey faster, cheaper and more effectively.
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The business leader that owns their business process must own the data that is created in that process. That includes data that is created by but is not needed in that process but is a requirement from another business process that is consuming the data.

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Andre Luiz C.

Data Governance & Mgmt Expert | Data Innovation Advisor | Startup Investor
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The best way to assess your data landscape is to adopt a data catalog that can automatically perform data discovery, generating popularity and top user information for your data assets. From there, you'll clearly see each asset's potential business owners and stewards.

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Naresh Gudla, PMP?,SAFe?,CSM?,ITIL?,SRE

2x Top Community Voice on LinkedIn 2023, Release/Change Management, Operational & Delivery Management using lean & Agile, Service Delivery (ITIL, SRE), Technical Program/Project Manager,Data Governance, Data Management
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Understanding the data lifecycle is very important before setting up any data policies. This uncovers many aspects of sourcing, storage, retention, privacy, security, etc. Organizations can refer to the Data Architecture team to understand the data modeling used for building the databases or regenerating an ER diagram using any of the tools helps to understand the entities' relationships. Data Catalog, Data Dictionary, and Business glossary if available can also be a good option.

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2 Define your data ownership roles

The next step is to define your data ownership roles, which are the different functions and responsibilities that are involved in data management. There are different models and frameworks for data ownership roles, but a common one is the RACI model, which stands for Responsible, Accountable, Consulted, and Informed. For each data domain, type, or element, you need to assign one or more of these roles to the relevant stakeholders, such as business units, data stewards, data custodians, or data users. For example, a business unit might be accountable for the accuracy and completeness of a data element, while a data steward might be responsible for defining and enforcing the data quality rules and standards.

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Merrill Albert

Enterprise Data Leader, Data Governance Officer, Data Thought Leader/Evangelist, Chief Data Officer, Fractional Governance, Data Strategist, creator of #CrimesAgainstData, preventing data problems for business success
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When defining data ownership roles, it's important to understand what fits into your company culture. Some companies avoid the term "ownership", thinking it implies one person is the owner and makes all the decisions. If you implement data governance in a collaborative mode, you will get people who represent the different departments throughout the company and collectively know how the company needs to use the data. Each department will have its own perspective, but you want the company's perspective as a whole.

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3 Establish your data ownership rights

The third step is to establish your data ownership rights, which are the permissions and restrictions that apply to the access and use of data assets. You need to define the data ownership rights based on the data classification, sensitivity, and value, as well as the legal and regulatory requirements. You can use data access policies, data security policies, or data sharing agreements to specify who can view, edit, delete, or share data, and under what conditions. For example, a data access policy might grant read-only access to a data element to a certain group of data users, while a data security policy might require encryption and authentication for a sensitive data element.

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4 Communicate and enforce your data ownership policies

The final step is to communicate and enforce your data ownership policies, which means making sure that everyone is aware of and follows the data ownership policies. You can use data governance tools, data quality dashboards, or data audits to help you monitor and measure the compliance and performance of the data ownership policies. You also need to provide training, feedback, and incentives to the data owners and data users to ensure that they understand and adhere to the data ownership policies. For example, a data governance tool might alert you to any data quality issues or policy violations, while a data quality dashboard might show you the impact and value of the data ownership policies.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you set data ownership policies?

1

2

3

4

5

1 Assess your data landscape

2 Define your data ownership roles

3 Establish your data ownership rights

4 Communicate and enforce your data ownership policies

5 Here’s what else to consider

Data Governance

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How do you set data ownership policies?

1

2

3

4

5

1 Assess your data landscape

2 Define your data ownership roles

3 Establish your data ownership rights

4 Communicate and enforce your data ownership policies

5 Here’s what else to consider

Data Governance

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