Can Master Data Management be successful without encompassing SaaS?

Adoption of cloud and SaaS specifically, the idea that an organization’s most important data resides in databases needs a rethink. A large majority of records are now unstructured and sitting in file storage systems such as Google Drive/One Drive while company IP resides in codebases or ticketing systems while chat systems are the knowledge highways for employees. MDM programs need to be reimagined to get a handle on access and usage of? PII, NPI, financial and other sensitive data stored and transacted over 3rd Party SaaS apps.

Achieving high fidelity in System of Records & Reference

A typical MDM program will target a state to establish a System of Record and System of Reference.

System of Reference:

A System of Reference refers to a set of authoritative sources or frameworks that provide guidance, standards, or benchmarks for a particular field or subject. It serves as a point of reference or a reliable source of information that individuals or organizations can consult for accurate and consistent data. A System of Reference helps ensure that information is based on established principles, accepted methodologies, or recognized best practices. It provides a reliable foundation for decision-making, analysis, and communication within a specific domain.

System of Records:

On the other hand, a System of Records refers to the structured collection, storage, and management of information or data by an organization. It encompasses the databases, files, documents, and other repositories where an organization stores its records, including personally identifiable information (PII), customer data, financial records, employee files, and other sensitive information. The System of Records typically involves policies, procedures, and technologies to ensure the accuracy, availability, integrity, and security of the records throughout their lifecycle.

What it takes to build an MDM program

A typical MDM program will generally target the following framework in getting established:

Historically MDM programs have only focused on structured data sets as sources of System of Records and System of Reference. Only recently, the ability to catalog semi-structured and unstructured datasets has allowed organizations to employ technologies to understand data outside of traditional row/column structures.

Why SaaS is important?

Understanding and governing data in SaaS platforms is an area that is still overlooked in traditional business settings. This is a massive blind spot in data governance. With more knowledge sharing sitting in 3rd Party SaaS applications, there are either duplicates or generally raw information that is sitting ticketing, file storage, chat and other such systems on the cloud. Including these systems in an organization’s System of Records is a must-have. In certain cases, System of Reference is also mirrored in Jira tickets, Confluence or Notion documentation. Though the complexity in mapping unstructured data to a data warehouse table structure can make this impractical in many cases.?

Achieve successful MDM via SaaS DLP

In the context of modern data management, leveraging tools like SaaS Data Loss Prevention (DLP) can provide valuable assistance. These tools play a crucial role in classifying data within SaaS platforms and go beyond that by establishing clarity on data ownership, usage guidelines, and real-time monitoring capabilities.?

In a shameless plug, for instance, let's consider implementing Polymer DLP, a powerful SaaS DLP solution. This tool enables the organization to automatically classify and tag sensitive data stored in file storage systems, codebases, ticketing systems, and chat platforms, ensuring that data is properly identified and protected.?

Additionally, Polymer DLP allows for defining data access controls, setting usage policies, and monitoring data activities in real-time. By integrating such tools into their MDM program, organizations can enhance data governance practices, mitigate risks, and ensure effective management of data assets throughout the SaaS landscape.

In conclusion, as organizations embrace cloud and SaaS platforms, it is essential to reconsider Master Data Management (MDM) programs to encompass the diverse sources of data. Relying solely on structured databases is no longer adequate. MDM programs must expand to include file storage systems, codebases, ticketing systems, and chat platforms within their System of Records. Neglecting data governance in these areas presents a significant gap in our understanding. By incorporating these systems into the MDM framework, organizations can ensure comprehensive data governance, protection, and accessibility, thereby maximizing the value of their data assets in the SaaS era.