Smart Mastering | MarkLogic NoSQL Database Feature

When integrating data, you want to harmonize data from different sources — your support, sales, loyalty card systems, etc. — to create a unified 360 view of your customer, partner, or patient. That 360 view is your holy grail. It enables your APIs to access the right data to deliver value, whether it’s to improve customer loyalty, deliver better ads, or comply with GDPR related data requests. That 360 view is where the magic happens.

Unfortunately, achieving that 360 view is quite difficult. The traditional approach of buying a dedicated tool for Master Data Management (MDM) is slow and inaccurate. Not to mention the fact that, according to one report, 76% of MDM projects fail.

MarkLogic’s Smart Mastering is different. It provides the ability to master data quickly and automatically. You don’t have to buy an ineffective, siloed MDM system. It leverages the flexibility of our data modeling approach to quickly build your 360 view in the context of everything it knows. It looks at the multi-layered relationships across all of the data and uses fuzzy logic and AI (relevance scoring, database intelligence, and probabilistic algorithms to be specific) to match related records and provide confidence scores. Based on those scores, related records are merged automatically.

Even more cool, MarkLogic’s Smart Mastering also makes it possible to unmerge records if necessary. Because it all happens in the context of an Operational Data Hub, you can still easily access both the raw data and the harmonized, mastered versions. And it keeps the lineage and provenance so you can look back at all of your changes. No other MDM solution does that. Cool. Very cool.

Making Sense of Person Entities

MDM exists because of common data inconsistencies. It gets especially tricky when dealing with data about human identity, or “Person” entities in the parlance of MDM.

The data for one customer entity, for example, may appear differently across systems because of misspellings, nicknames, or the existence of multiple accounts. A customer appearing as Pat Richards in one system, may be Patricia Richards or Pat Ricardo in another. Or, what appears to be one entity is actually multiple entities — maybe Pat Richards actually has a son or daughter at the same address who, surprisingly enough, is also named Pat Richards.

These challenges with human identity are constantly occurring in business, and traditional Master Data Management (MDM) technology is simply terrible at fixing them. To make sense of it all, you need to re-think your approach to these challenges because without a 360 view, you won’t be able to serve your customers and achieve the business results you want.

Besides being too simplistic in how they match and merge data, traditional MDM tools run into a whole host of other problems.

Slow to implement — Complex data modeling and ETL must all be done up front
Too simplistic — Non-AI driven models are riddled with inaccuracies, sometimes as high as 80%
No unmerge — Survivorship rules determine which record to keep, and the loser dies forever
Weak governance — Provenance timestamps on every table are difficult to model and slow to query
More silos — Requires re-engineering to include an MDM tool, operational access, and data warehouse
Not trusted — Each additional silo adds another endpoint which adds security risk

Your data is safe in MarkLogic, the most secure NoSQL database. And it’s well governed because Smart Mastering is designed to maintain the full provenance and lineage of data — as it is mastered. It is essential to your business when dealing with regulations like GDPR, but it’s also helpful in providing great customer service.

Data integration projects go 5x faster with MarkLogic. You can expect the same agility with Smart Mastering. And, you don’t have to buy some old legacy MDM product that’s prone to failure. Smart Mastering provides out-of-the box rule configurations, a set of APIs, and a visual interface to get you started quickly.

MarkLogic’s Smart Mastering takes the full context of your data in mind as it matches and merges -automatically. It uses a trust based approach to address duplicate, incomplete, and partial entities. It also allows un-merging when mistakes are made (and they always are with MDM).

Making Sense of Person Entities

Why Does Traditional MDM Fail?

The Smarter Approach? Smart Mastering in a Data Hub

Mastering Process in the MarkLogic Data Hub

Want to See How Smart Mastering Works

Get Started with Smart Mastering

Github

Data Hub Framework Repo

Github

Smart Mastering Repo

github

Smart Mastering Demo

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