Master data management (MDM) is distinct from other data management disciplines due to its primary focus on giving the enterprise a single view of the master data that represents key business entities, such as parties, products, locations and assets. MDM achieves this by standardizing, matching and consolidating common data elements across traditional and big
Single view of customer. It's a noble goal, not unlike the search for the Holy Grail – fraught with peril as you progress down the path of your data journey. If you're a hotelier, it can improve your customer's experience by providing the information from the casinos and the spa at check-in to better meet your
Most companies are battling with master data challenges whether they realise it or not. When you're consolidating financials from multiple billing systems, you're doing MDM. When you're migrating legacy systems to a new target environment, you're doing MDM. When you're trying to perform root-cause analysis across multiple systems for a
.@philsimon on the role of MDM. TLDR: It depends.
In my last post, I discussed the issue of temporal inconsistency for master data, when the records in the master repository are inconsistent with the source systems as a result of a time-based absence of synchronization. Periodic master data updates that pull data from systems without considering alignment with in-process
The numbers are daunting. More than 40 million Americans have their identities stolen each year. Credit card companies lose more than $200 billion annually due to fraud. Cybercrime-related losses exceed $3 million per claim for large companies. If you’re like me, those stats are enough to give pause. To fuel the concern,
.@philsimon on the collision between the two.
Master data management (MDM) provides methods for unifying data about important entities (such as “customer” or “product”) that are managed within independent systems. In most cases, there is some kind of customer data integration requirement for downstream reporting, and analysis for some specific business objective – such as customer profiling for
I've spent much of my career managing the quality of data after it was moved from its sources to a central location, such as an enterprise data warehouse. Nowadays not only do we have a lot more data – but a lot of it is in motion. One of the
.@philsimon asks some fundamental questions about taking the next step with #bigdata.
