ADI and MDM: When, Where and Why

The exponential growth of data underscores its significance as a fundamental asset in today's world. Professionals working with data have access to a vast array of tools. When users confront the common issue of managing overlapping, fragmented records and addressing various data quality issues, they often opt for Master Data Management (MDM). However, it's crucial to recognize that MDM isn't the exclusive solution available and that it's often not the best suited solution available.

What is MDM

MDM as a concept focuses on the creation and ongoing management of “golden records” in a centralized system. This all-encompassing approach often comes with a high cost - in time, money, and people, but can yield clean data assets to operate on. While MDM seems like the “perfect” solution, we routinely see and hear the pain from MDM practitioners and top executives across many industries on the limitations of their MDM platform or of MDM in general.  

Overall, MDM is not the answer for everything. Here is a quick list of well established pro’s and con’s of typical MDM solutions:

• Pro: Single Solution. Often a fully integrated platform with tools for quality, resolution, and governance.
• Pro: Creation of Golden Records. Results in data that is often “single source of truth”
• Pro: Pre Existing Integrations. Many platforms have existing integrations (for reading and writing) with major CRM, ERP, and other core business applications.
• Con: Poor time to value.  Implementations are typically multi-year, multi-million dollar ordeals.
• Con: Narrow scope.  MDM programs typically focus on only the most critical entities / data.
• Con: Expensive. Deployment and operation of the MDM program/platform requires significant monetary, time, and resource investment.
• Con: Limiting Technology. Restricted to only using the functions/features available by the platform.

What is ADI

ADI is a no-code, AI-driven entity resolution platform that data citizens, not just domain experts, can leverage to combine data quickly to make it actionable. While there are many challenges to using messy data, we created ADI to solve the first and most significant challenge faced by consumers of data - simply and reliably linking records to one another; otherwise known as entity resolution.

• Intelligent Matching. Our semantic and AI powered matching process makes joining A to B as simple as selecting your data and pressing “go”.
• Extensible. Add new functionality or semantics to easily customize the platform for your unique data and needs without limitation.
• Scalable. Each component can independently scale up to handle faster or larger throughput.
• Transparent. No black box processes, track how your matches were made and overrides selected.

Ok, so which one should I use?

Great question - based upon our discussions with top data executives, experience as practitioners, and research in the field, we’ve put together the following matrix to help understand when you might want each solution - or both!