How to create that Golden Master

The concept of a centralized view or 360 degree view of a customer is often strived for but the "name, want and get" is not always figured out. Most companies will name what they are looking for, some fall short in getting the board to want the solution and many lose it on figuring out how to get it done.

VP of Siperian describes the need for assigning reliability factors to the different sources of data as some sources may have more accurate data:

In order to deliver a “golden” or master record for each customer and its various affiliations, a system must dynamically assess reliability across all data sources – based on user-defined parameters and intrinsic data properties – and ensure that only the most reliable content survives at the cell-level of the master record. For instance, if the call center begins collecting email addresses when confirming orders, this data attribute may be more reliable than the email addresses submitted by customers at the website. The ability to rapidly adjust the system to survive the call center email address over the website email address is a critical architectural component of any CDI system. Moreover, such cell-level survivorship for data reliability must be built into the core product architecture and should not be sacrificed as the customer hub scales to millions of customers. Ultimately, how well the end-users accept a customer data hub depends on sustaining high level of data reliability, even as the hub grows in volume or as new data sources are added.

In looking into different CDI solutions, you must look into how the data hub is structured, if they have configurable rules for loading and merging and if they have a robust Data Steward. Realize that data stewardship is the way all 'exceptions' get handled. If you do not separate out the confident updates from the questionable ones, you will have a poor foundation that will eventually lead to a polluted database.

A business cannot implement an operational customer hub in the absence of data stewardship ― as soon as data begins to flow through the supported business processes, exceptions and errors begin to flow as well. Therefore, any customer hub acting as a data integration platform must offer business capabilities to monitor and handle such exceptions either by business analysts and end-users or by anyone designated as a data steward.
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Often managing such exceptions requires full user interfaces for complex data stewardship tasks such as investigating the history and lineage of certain master records in question. This may be the only way to ensure that the user acceptance and data hub reliability remains high. In other circumstances, an enterprise may choose to build a specific user interface against the programming interfaces of the master hub in order to suit its needs. In either case, an adaptive solution must deliver rules-based configurability with best-in-class data stewardship consoles as well as programming interfaces to handle all data exception and reliability needs.

I've worked on custom CDI projects before CDI was called CDI and can attest that the Data Stewardship interface will make or break your CDI project. This should not be underestimated.

The last point data export back to original sources. This is where you exchange your centralized view with the sources and provide them with your expanded view to assist them in better understanding your customers. If you have done a good job, they will love you, if you haven't you will be public enemy number one. They think their data is "better than yours", "why did you change my address", "you merged two customers into the same one!" and other rantings will be sent your way if you have not done a good job.

You should have a well thought out strategy including what data elements you will send back to sources and you should allow them to decide whether or not they want your data.

Often, certain data attributes (such as privacy preferences) need central control and exception handling whereas other attributes are best left under local management. In addition, security and access to data attributes in the hub will vary by individual roles within each organization and by organization at large. In fact, to support the broad range of business requirements across business lines, there may be multiple data governance regimes required for different data attributes, all within a single enterprise.

An adaptive approach must be based on a distributed architecture whereby multiple hubs can be deployed to integrate different data sources and support different processes, yet be able to share data across one another based on any number of hub-and-spoke or peer-to-peer governance regimes. This offers a line of business yet another dimension of flexibility to share some but not all data – each based on its own data reliability and governance policies. With full rules-based configurability and data stewardship interfaces, a broad range of data governance regimes can be supported.

In summary, data must be the central focus of any CDI project, and data reliability, stewardship and governance regime must never be an after-thought of a comprehensive CDI solution. Enterprises must closely review the details of a vendor’s offering in this area to reduce their risk of project failure and the total cost of CDI implementation.