I’m often asked about the differences between software as a service (SaaS)-based master data management (MDM) and on-premises MDM. The answer is not that simple and requires a bit of explanation.

To understand this better requires an explanation of what SaaS is, as well as why companies choose it rather than an on-premises solution. Let’s start with the basic definition of MDM SaaS.

MDM SaaS (or SaaS MDM) is master data management software hosted on the cloud. SaaS is a software distribution model in which a third-party provider hosts the application and makes the application available to customers over the Internet. As SaaS is a standard model employed by many companies today, a wide variety of examples come to mind: CRM systems like Salesforce, document management services like Dropbox, and team collaboration tools like Slack, to name a few.

Another relevant term to note here is “multitenant.” Multitenancy refers to a type of software architecture in which a single instance of the software runs on a server and serves multiple tenants. A tenant is a group of users who share common access with specific privileges. It’s an architectural approach that allows for the greatest flexibility and agility, and you’ll often come across references to “multitenant MDM” as part of a SaaS MDM conversation.

Any MDM system, whether SaaS or on-premises, requires that you understand your data, build your data integrations, and configure your rules. However, there are some key differences between MDM SaaS and on-premises MDM:

• On-premises MDM offers enormous control, as you handle the configuration, upgrades, and system changes.
• While cloud-based solutions are designed to be highly flexible, organizations can get locked into many technology decisions made entirely by the vendor.
• Depending on security culture and data sensitivity, on-premises MDM may make sense if an organization has clearly defined security structures and standards for its IT applications.
• With on-premises systems, you don’t have to rely on Internet connectivity or external factors to access your software.

For companies that are already comfortable with SaaS solutions and are looking to start on their master data management journey, it’s only logical that they would want an MDM SaaS offering instead of on-premises MDM. However, there are several things to consider when evaluating MDM SaaS. I’ve highlighted five of the most important to get you started.

1. Breadth and depth of capabilities

One of the key challenges of moving to a SaaS-based model is that, while many SaaS vendors may possess fresh user interfaces and simplicity, they lack the critical capabilities required for successful master data management projects.

There are four critical aspects that should be evaluated here:

• Do they offer best-of-breed capabilities? By this, I mean things like business process management, data stewardship, matching and merging, relationship and hierarchy management, and more. The latest research clearly shows the immaturity of many cloud MDM vendors.
• Does the vendor provide an easy way to ensure the best data quality? How easy is it to integrate, cleanse, standardize, validate, and enrich data?
• Does the vendor offer the data governance and metadata catalog capabilities you need?
• Beware of rigid solutions. The solution you choose has to have the flexibility and agility to evolve and adapt to your business needs. You shouldn’t be dependent on a vendor’s engineering team to do customizations for you each time you want to expand your usage. Some MDM SaaS vendors have only basic features (if any) to address the breadth of functionality required by enterprise-wide MDM. Many offer only rudimentary capabilities in the most important areas of MDM, such as data matching—data matching has to be able to take into account errors, typos, variations in the data, and more. As you start embedding master data into your business processes, the rigidity of the solution begins to hold you back.

2. Scalability and Performance

A typical enterprise manages master data related to customers, accounts, services, employees, suppliers, distributors, products, materials, reference data, location, and more. It is also essential to manage the interconnections between these data domains to gain full value from MDM.

Can the SaaS MDM solution provide you an enterprise 360 view of all data and support the multidomain use case? Can it scale to address data volume? Does it allow for modularity and start with a domain of your choice and expand to other data types at your pace? We have been working with customers who manage over 20 domains in a single solution. Our typical customers manage 3 to 8 domains, and this is a common requirement for any organization.

Many SaaS MDM vendors frequently offer a departmental solution that does not scale to manage more than one domain. The moment you are planning to expand to address new use cases, new domains, and go beyond one department or function, you’re in for a surprise as it will require significant customization.

3. Architectural Flexibility

Most multitenant cloud MDM products were created almost 10 years ago when much of the microservices and database back-end technology were still in an infant state. Since then, we have learned a lot about how to deliver scalable, manageable, and still flexible enterprise data management software.

How a SaaS vendor architects and builds their software can profoundly impact the reliability, scalability, and flexibility of the solution. There are a few critical aspects you’ll want to evaluate here:

• Is vendor architecture based on loosely coupled, separately upgradeable, and scalable microservices? A microservices-based architecture offers more resilience and scalability than a monolithic architecture. A microservices architecture also makes it much quicker and easier for a vendor to add new features.
• Does the vendor automatically scale up or scale down resource allocations to address seasonal and other spikes?
• Has the vendor been thoughtful about the technology selection? For example, many enterprises use MDM in operational use cases where ACID (Atomicity, Consistency, Isolation, and Durability) properties are essential. Early cloud MDM services often chose NoSQL databases that cannot provide ACID data integrity. Also, some NoSQL database technologies, such as Cassandra, are much better at handling append-oriented writes than they are at handling the types of updates a typical MDM system can expect.
• Does the vendor have a well-constructed deployment pipeline for continuous integration and delivery to ensure predictable and high-quality delivery of new features and enhancements? Do they have quality assurance processes built into every step in their pipeline? Do they have secure coding and security testing built into their pipeline?

4. Security and privacy

Cloud governance is a top challenge for 84% of organizations, according to 2019 State of the Cloud Survey. Today’s enterprises have rigorous security and privacy requirements, and a multitenant cloud platform must be able to meet those requirements.

Securing each enterprise’s data must be part of the vendor’s core strategy. Data security needs to be a primary design principle in the cloud, and vendors must use industry-approved algorithms to encrypt all data. All stored and in-transit data must be encrypted.

SaaS vendors must follow a secure system development lifecycle for their software and must make sure that any third-party libraries they use are also secure and up to date. SaaS vendors must also adhere to the key standards their customer’s industries. Informatica’s Platform Trust page provides details of our approach to security and you can check the production status of our cloud products, including planned maintenance schedules, at status.informatica.com. You can find more information on Informatica’s certifications, assessments, and our compliance standards here.

5. World-class support

There is a perception that SaaS means faster implementations, and it’s certainly true that getting an environment up and ready to be configured is faster in the cloud than it is when you have to install the software yourself on-premises. But don’t forget that for any MDM system, whether in the cloud or on-premises, you still have to understand your data, build your data integrations, configure your rules and so on. If you don’t have the resources in-house to implement the system, you will want to have a wide choice of implementation partners to assist you, and you will want to be confident that your implementation partner has been well-trained and has access to the resources that they need in order to be successful for you. The world’s best systems integrators, resellers, distributors, and ISVs partner with Informatica to help you integrate, innovate, and accelerate your business.

Unlike other applications, MDM impacts every part of an organization, making a tailored customer success offering critical. You need a vendor who can provide world-class support across multi-cloud, hybrid, and on-premises environments, with dedicated operations personnel to monitor and manage the health of the system, along with technical support engineers who help you quickly resolve issues.

Unfortunately, cloud MDM vendors do not have a good reputation for providing the type of sophisticated support you need for running your enterprise workloads. Recent reports show that customer support from cloud MDM vendors have not improved over time. However, the story is not the same for Informatica. We’ve actively and consistently invested in customer success over the years.

I’ve given you a starting point for your MDM decision. But don’t forget about other proof points such as financial stability of the vendor, track record, time to value, and return on investment—you’d be wise to research them before you make a decision.

MDM is an investment for the long term, and I hope this blog provides you enough insights to make the right choice for your MDM journey. 

I would love to hear your point of view. Reach out to me on Twitter at @MDMGeek. Let’s stay in touch.