Databases Reference
In-Depth Information
In order for MDM to work with big data systems, there are several requirements:
•
MDM must also be able to store profiles for any big data source
that needs to be linked to a master record. Examples include:
account IDs to link transactional big data to customer and
account records, mobile device IDs to link mobile device data,
and real-time location data to a customer record, among others.
•
The MDM system must also be able to store preferences for each
big data source.
Does a customer want you to analyze their tweets?
Or their Facebook profile?
MDM must track the customer's
preferences and consent for certain types of communication and
interaction.
•
MDM should relate many-to-many relationships between
customers and profiles. For example, a household is related to a
single social media profile on a photo-sharing website (one social
media profile for many customers who belong to a household).
This enables MDM to effectively feed a big data application with
relevant master data and big data links.
•
MDM must also be able to store the output from big data
analytics. Intent to purchase, next best action, customer churn
alert flags, negative customer sentiment: these are all attributes
that should be stored in MDM. Insights from big data should be
available to multiple operational channels (for example, if you
detect that a customer is dissatisfied with your company, then
you want all the interaction channels to know that fact, no matter
which channel the customer interacts with).
•
The MDM system should also have the capability to proactively
detect events and send event notifications, triggering action in
business applications and enterprise processes as necessary.
MDM must be an active participant in big data analytics.
•
The big data system must be able to interact with MDM. Whether
you're working with transactional data, analyzing social media
data, or analyzing streaming call detail data off a network, the big
data system needs to understand the master view of customers
and products. There's no point in the big data system re-inventing
the wheel and trying to determine unique records and identities.
This integration or information exchange aspect is important
from a discovery/experimentation type of workload point of view
as well, which is the most-cited big data system usage so far. In
essence, big data applications need to be MDM-aware. They
should obtain master data from MDM either in batch load or in
real-time if necessary.
