What is Master Data Management, and Why Does Your Business Need It?

Imagine a company where every team is in charge of its own budget and finances, spending at will, using different currencies, keeping financial records in secret, and using different financial software to track their spending and income. Sounds like an absolute disaster, right?If you’re a small-business leader who is struggling to keep your company’s data organized due to a lack of resources or preparation, you could be creating a similar disaster with your data. This data disaster could cause your business to lose important client and customer data, make poor business decisions based on unreliable data, or even face crippling fines and penalties for irresponsible data handling.

A full-scale master data management (MDM) program is probably overkill for most small businesses (not to mention an excessive use of resources). But borrowing some master data management best practices—such as using data management software tools designed for smaller businesses and establishing a culture of data stewardship—can help you ensure that your data is clean, organized, and protected while also setting your business up for digital growth.

In fact, Gartner predicts that by 2025, half of all data and analytics leaders will use augmented data management practices to achieve digital acceleration goals (full report available to clients).

In this article, we’ll learn a little bit more about master data management and how you can use it to protect your business. Let’s get started.

Master data management is the centralized, coordinated oversight of an organization’s data (also known as big data). Master data management is aided by information technology infrastructure, but it is also overseen by an individual data manager or team, typically as a function of data and analytics.

Data without data quality assurance is essentially unusable data. Master data management helps ensure that the data you’re using to make business decisions is accurate and reliable. This is why master data management is so important, especially for smaller businesses that are trying to become viable. One bad decision based on inaccurate data could sink a business that doesn’t have the resources to recover from a misstep.

For example, if a small business decides to invest in growth based on bad data, but then ends up in a budget shortfall, the consequences could be dire.

However, you may be wondering if your business is even big enough to need “master” data management. While every business can and should employ good data management practices, the scale of these efforts and the formality of roles and responsibilities will depend on how much data you’re handling and how sensitive that data is.

Master data is typically:

• Uniform (for example, a list of birth dates in a specific format)

• Identifiable (for example, a list of customer ID numbers)

• Unchanging (for example, a list of customer social security numbers)

• Used by multiple teams in your organization.

Examples of potential master data include birthdates, addresses (email and physical), and customer driver's license numbers. Examples of non-master data include social media engagement statistics, anonymous reviews, and random transaction numbers.

If your business handles lots of the former, it’s a good idea to have a formal master data manager in place. If your business doesn’t handle this type of data, simply promoting and following good data compliance practices should suffice until your data pool grows to include more master data.

 Depending on the size of your business, master data management can easily be handled by one data manager using master data management software. Larger organizations can budget their master data management team with as many resources and staff as needed based on the size and quantity of their data sets.

Here are several common roles in master data management. Businesses looking to grow their master data management capabilities should start at the top of the list and work their way down as they grow.

• Data steward/data custodian: Data stewards, also referred to as data custodians, are any individuals in a business or organization who are responsible for monitoring a data source and enforcing data governance policy, either in an officially designated or implied role.

• Data manager: A data manager is responsible for maintaining and upholding an organization’s data governance policy. The data manager is also responsible for overseeing and guiding the data stewards.

• Data owner: A data owner is any individual in an organization who is directly responsible for the protection and quality of a set of data or multiple sets of data. Data owners typically work with data managers to discuss access to shared data and the state of the data governance policy.

• Data and analytics leader: The data and analytics leader is responsible for the oversight and management of all of an organization’s data and analytics teams. A data analytics leader should also have a large role in managing and connecting data silos.

• Chief data officer: In larger organizations, the chief data officer is responsible for the governance of all data across the organization’s data warehousing system. The chief data officer might manage several data and analytics leaders.

Depending on the size and resources of an organization, the responsibilities of these roles will naturally overlap and combine. For example, in a smaller business, the responsibilities of the data manager, data owner, and data and analytics leader might all be held by one individual.

Master data management software assists data managers and data owners in storing, cleaning, protecting, and verifying multiple sets of big data. Some master data management software also includes analytics features to help data and analytics leaders make connections between separate sets of data.

Example of a MDM tool dashboard (Source)

Features of a typical master data management solution include:

• Data access and permission controls to restrict and allow access to data as necessary.

• Data activity tracking to monitor who is accessing data and what they are doing with it.

• Built-in database to allow the centralized oversight and a single source of truth for all of an organization’s shared data.

• Compliance management to maintain and enforce an organization’s data compliance policies.

• Data synchronization to ensure the uniformity and accuracy of an organization’s data.

• Data visualization and mapping to help data analysts and leaders gain insight and share findings on sets of data.

• Quality control to help data managers ensure data quality and uphold good data quality policies and practices.

As we discussed in the section on master data management roles, small businesses and large enterprises will have different needs for their master data management programs. While a small business might only need one employee to oversee master data management, a large enterprise with lakes of data might have a master data management team made up of dozens of employees.

As your business grows from the former toward enterprise data management, here are some tips to scale your master data management program:

• Start with a data manager. Your first data manager should work to make data stewardship a company-wide initiative by developing and implementing a data governance policy.

• Let data management software lighten the load. It’s not humanly possible to oversee large sets of data using spreadsheets and manual monitoring (at least without quickly burning out the human attempting to perform such a task), so a good master data management tool to assist with overseeing and protecting big data is a must.

• Unite your master data management and data analytics teams as soon as possible. Data management and data analytics teams work together to protect and leverage data, so it only makes sense to join these teams as soon as you can to assist with the quality and availability of isolated sets of big data.

Check out this short video for more tips on scaling your company’s data analytics efforts:

How To Get Started With Data Analytics and BI for Your Business (Source)

As we saw in this article, borrowing master data management best practices that fit your business—even if you’re not ready to establish a master data management team—is crucial to ensuring accurate, consistent, and protected data across your business.

By starting down the path of efficient master data management, you can avoid the chaos that would come from a data disaster, including losing critical data, failing to protect customer data, and facing penalties for violating data protection laws.

Once you’ve established a master data management protocol, and you have high quality data in place and a system for continued data quality, you’re ready to plug that accurate data into a business intelligence tool to get reliable and actionable insights. Our Business Intelligence Buyers Guide has all the information you need before starting your BI software buying journey, and our Category Leaders in Business Intelligence highlights 15 top options in BI software based on verified user reviews so that you can efficiently get the data insights to guide your business in the right direction.

GetApp’s Category Leaders in Business Intelligence (Source)