Understanding the Key Benefits and Differentiators
As I lean into more and more Salesforce Data Cloud conversations with customers, I’ve noticed some overlap and conflation in how Data Cloud is being perceived in relation to Master Data Management (MDM). What’s the difference between the two? Do I need one if I have the other? If MDM is already in place, does that replace the need for Data Cloud?
At a high level, the two ideas are entirely different concepts. MDM is a practice, whereas Data Cloud is a product. MDM may consist of multiple products and processes established by an organization to ensure data is accurate and governed across enterprise applications. It’s basically a discipline made up of certain technologies and processes that seeks to standardize a company’s data and dispense it across a variety of business teams and functions. Data Cloud, on the other hand, is a single platform that can store, harmonize, unify, segment, and act on that data. So, what does that mean exactly?
Salesforce Data Cloud
Salesforce Data Cloud provides the advantages of a standard Customer Data Platform (CDP) in that it ingests, stores, and models data as well as providing profile unification, contact data enrichment, audience segmentation, actions, and insights. But Data Cloud provides this beyond standard marketing needs and provides for use cases across departments such as Sales, Customer Service, Commerce, Loyalty, etc. Some of the distinguishing characteristics of Data Cloud include:
- Data Integrity: Unlike MDM, Salesforce Data Cloud maintains mutable data, ensuring data integrity while providing the flexibility to erase and merge records as needed. It acts as a centralized repository and enhances data quality, segmentation, and activation to other systems without overwriting data in those systems.
- Data Lineage and Identity Resolution: Salesforce Data Cloud not only enriches data but also maintains source lineage in its identity resolution. This helps businesses trace the origin of data and maintain data credibility, so data is never lost or destroyed. Profile unification is designed to be a malleable process in Data Cloud, where the consolidation rate of profile data from multiple sources can be increased or decreased based on new data, new source systems, or business rules as they may develop over time.
- Flexibility and Accessibility: One of the greatest challenges that Data Cloud meets is being flexible in its ability to ingest data and make that data readable and accessible to users. I always say that data communicates value throughout marketing efforts, but you shouldn’t need your IT department to translate that value for you. Data Cloud unlocks this with an easy UX capable of advanced segmentation, unlocking the power of your data in a useable format, and activating it to marketing, sales, or other users.
Master Data Management (MDM)
MDM, on the other hand, is typically a practice or concept rather than a single product. It focuses on creating a unified, consistent view of data across an organization by standardizing and integrating data from a variety sources. MDM places its focus on:
- Immutable Data: MDM establishes immutable data and processes by generating a unique identifier, also known as a “golden record,” for each entity. It ensures data accuracy and consistency across multiple systems.
- Data Governance: MDM incorporates data governance practices such as data standardization, data classification, and access controls to maintain data quality and compliance.
- Standardized Application: MDM can be applied to enterprise, product and customer data management throughout an organization to maintain accurate customer records, manage product information, and ensure regulatory compliance. For these reasons, MDM is and should be a rigid process; updating it at any point has a ripple effect throughout an entire universe of data, models, and systems. That is why updates or edits to an MDM strategy are typically slow, critically planned, and can be painful to implement. New data types, sources, and technologies are not always directly integrated into the overarching MDM strategy because it can be viewed as such a large scale undertaking.
The Power of Salesforce Data Cloud + MDM
While both Salesforce Data Cloud and MDM aim to improve data quality, integration, governance, and security, they differ in their approaches and functionalities. Salesforce Data Cloud offers advanced data enrichment and integration capabilities with a focus on maintaining data integrity and flexibility. On the other hand, MDM focuses on standardizing and integrating data through a centralized “golden record” approach. Additionally, MDM requires more IT resources to implement and maintain, whereas Data Cloud provides capability for marketers and other users to access and leverage data without burdening IT, Data Science, and other teams. MDM can be useful in maintaining accurate data across systems, but that doesn’t always mean the end users readily have access to the data in a readable and usable format.
The strengths of Salesforce Data Cloud and MDM can be combined to provide a more comprehensive data management solution. By utilizing Salesforce Data Cloud with MDM, organizations can avail themselves of various benefits such as:
- Advanced Data Enrichment and Integration: Salesforce Data Cloud enhances the quality and completeness of data, while MDM ensures standardization and integration across the organization. Starting off with clean data ensured by MDM solves many issues; applying Data Cloud to that strategy enriches that data.
- Comprehensive Data Governance and Security: By leveraging the data governance and security features of both solutions, businesses can establish robust data management practices, react in near real time to consent changes, and stay in compliance with regulatory requirements.
- Extending the Customer Graph: Salesforce Data Cloud works alongside MDM to extend the customer graph beyond the boundaries of MDM. It can serve as a system of reference for analytics platforms, Loyalty products, CRM tools, and other systems. That graph is malleable and can be updated without losing or altering data.
- Fluid Data Model: Salesforce Data Cloud’s fluid and nondestructive data model allows companies to adapt their identity graph as needed without incurring significant changes to existing systems, requiring largescale efforts to update a multitude of systems and processes, and can easily experiment with the impacts of such changes before applying them permanently.
Understanding the differences between Salesforce Data Cloud and MDM is essential for businesses looking to enhance their data management practices. Data Cloud provides advanced data enrichment, integration, and flexibility to offer users a holistic view of their customers. While MDM focuses on standardization and maintaining a consistent view of data.
The two ideas provide one another with mutual benefit. An effective MDM strategy provides a head start for Data Cloud to begin offering value and doesn’t require arduous or complex updates to the MDM strategy. Meanwhile, MDM benefits from the use of Data Cloud by enriching customer data and making it more easily accessible to teams to leverage it for segmentation, activation, and data actions across channels.