Master Data Management: 13 Best Practices for Effective Master Data Governance

Every company has to manage the organizational data from different departments such as operations, marketing, sales, eCommerce, account, human resources as well as individual employees and customers in more or less quantity.

• If your answer is YES, then I am sure you are not aware of the capabilities and benefits of centralized management of your organizational data. It saves a lot of time, money, and effort for your team in managing the data across multiple systems. Thus, it is highly recommended to midscale to large scale organizations to implement a Master Data Management system.

• While developing and implementing an MDM solution, don’t miss to consider advanced security and compliance standards to protect your valuable data.

• Most of the platforms available in the market come with the best security standards. But, if you want, you can add extra layers of compliance to avoid the risk of a data breach.

• Before moving towards master data governance, let’s get an overview of master data management. Udertsadingfo MDM enables you with better clarity further in this post.

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What is Master Data Management (MDM)?

Master Data Management creates a single master record of all the essential business data from external and internal data applications and sources. It involves the organization with a consistent and uniform set of extended identified and attributes that present all the core business entities.

• In MDM, companies can manage the data of their products, customers, employees, accounting, operations, partners, websites, and more.

• To get better insights about MDM, read What is Master Data Management & How Can It Benefit Your Business?

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What is Master Data Governance?

Master Data Governance is an application for data governance and compliance that helps brands improve the management of a subset of master data. Master data allows managing all types of data that every entrepreneur needs to run an organization or business.

• MDM helps companies to manage various operations too through centralized data management.

• For example; you purchase the material from the suppliers to create products that you want to sell to your customers and deliver the products to partners.

• The consistent and accurate material, product, supplier, partner, and customer data help you to boost the accuracy and efficiency of your various business processes such as record to report, procure to pay, and order to cash.

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13 Best Practices of Master Data Governance

Definitions • Master data governance presents the core set of attributes that are part of the main master data definition and these attributes are consistent across the company. • For example; you want to create a master record of customer data in MDM. For that, MDM allows you to manage all the data that are relevant to your customer base such as

1.

and

• In short, you can cover all the attributes that are essential for your business processes. • Here, the critical job is to define which attribute is important for your business. Otherwise, you will end up focusing on the least important attributes that negatively impact the success and agility of your master data management operations.

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13 Best Practices of Master Data Governance

2.

Data Quality

Management • Data quality requirements differ from company to company. Thus, organizations need to consider tools and techniques to support data monitoring and validation processes. The data quality management processes include • Enabling effective reporting and quality monitoring

Creating control for validation

Data incident tracking

Enabling recommendation and root cause analysis • Supporting the triage process for assessing the level of incident severity • The right process for data quality management enables you with trustworthy data for analysis.

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13 Best Practices of Master Data Governance

3. Data Access Management

• For data access security, two aspects are considered under master data governance.

• 1. Provision of access to available assets

• It is essential to provide data services that allow organizations to access their respective data. The companies need surety that apart from the company, no other individual or company can access their data. Most of the cloud platform providers offer varied methods for developing data services.

2. Prevention of unauthorized or improper access

• You need to develop a Master Data Management solution that allows you to define roles, groups, and identities in order to assign access rights to establish a level of managed access rights.

• Data access management is the best practice to manage the master data access services and interoperating with cloud provider’s access and identity management services by allocating and managing access keys, defining roles, and specifying access rights for ensuring that authenticated and authorized systems and individuals are able to access data assets according to determined rules.

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13 Best Practices of Master Data Governance

4. Policies

• Master Data Governance makes sure that external regulations and internal policies are taken care of as a part of master data management. These policies should be relevant to many aspects of the master data governance such as privacy and protection, risk management, data quality, and retention and deletion.

• To address the regulation and policies, it is important for you to separate the duty in terms of

• Who can create the master data for the cost center in a general ledger system

• Who is allowed to approve the creation of cost centers (it is a risk control policies in order to prevent accounting fraud)

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13 Best Practices of Master Data Governance

5. Rules

• You might be thinking, we have already discussed the policies then why we need to talk about rules. It’s indirectly a part of the policy.

• Well, it’s not so.

• Policies are supposed to define what you want to do. On the other hand, rules define how to enforce and execute policies.

• Want to understand this difference in detail? And, how policy and rules work hand in hand? Let’s look into it.

• Policy: Before you use the personal information of a customer, you must obtain approval for processing.

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13 Best Practices of Master Data Governance

6. People

• By creating the documentation of master data governance, you can provide visibility to your different teams across the organization who are continuously working towards the success of MDM activities. These people from your team could be:

7. Workflow

• Once you determine the core team who are going to utilize the master data management. You also need to define the workflow in the document that allows your teams to collaborate effectively. With the help of workflow, you can

• Define a mechanism for creating the request for master data creation requests.

• Allow multiple people of the different organizations who need to be involved with parallel approval, workflows, go-live distribution, and activation of applications.

• Determine which master data steward the request is routed to, based on domain responsibility.

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13 Best Practices of Master Data Governance

8. Catalog

• By implementing a robust Master Data Management system with the right Master Data Governance, you can get access to several cataloging capabilities.

• Assuring the quality (completeness and accuracy) of master data across every single source

• Verifying the consistency of master data definition across different sources

• Exploring and documenting which master data domains are available across different systems, applications, and other sources such as lakes, data warehouses, and more.

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13 Best Practices of Master Data Governance

9. Process Mapping

• Process mapping provides visibility on how the master data flows between different sources as a part of business activities. It is more or less similar to the catalog documents where the master data resides. Knowing how the master data flow through processes or understanding the source helps you to better visualize the varied things like

• Where rules require to be introduced into the process to enforce the policies

• Compliance risk exposure

• How the master data is being used

• In the process of mapping, you need to understand from where the master data is collected, which systems the data flows to, and what third party systems the data is shared. Thus, you can enforce policies and standards for clinical data submissions and acquisitions.

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13 Best Practices of Master Data Governance

10. Auditing

• To ensure that the systems are working as they are designed to act, companies need to access their systems. Data auditing, monitoring, and tracking (who has made what changes and when and with what information) helps your data security teams to collect data, identify risks, and act on them before any data damage or data loss occurs.

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11. Data Protection

• Most of the companies have Perimeter security that is not enough to protect your sensitive business data. There is a risk of data leak as the users with limited access to your data cannot access all of your data but some of your data can be exposed by that user anyhow.

• You need to adopt advanced data protection methodologies to make sure that exposed data cannot be read. Here you can consider various methods like

• Encryption in transit

• Permanent deletion

• Encryption at rest

• Data masking

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13 Best Practices of Master Data Governance

12. Data Literacy

• To ensure the success of data governance relies on training, education, and a true understanding of what can’t and can be done with your data.

• But the adoption of technology alone is not enough. It takes policies, people, and processes to drive the organization level change and enables users to protect and see the value of their data as a business asset.

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13. Metrics

• When it comes to managing and measuring the master data, master data governance allows businesses to define matrices. It contains varied technical metrics such as the completion and accuracy of master data, how many personal data attributes are masked or encrypted, and the number of duplicate records in an application.

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