Think big, but start small. This is particularly good advice if you plan on implementing a master data management (MDM) system any time in the near future.
MDM is an extremely powerful technology that can yield astonishing results. But like any complex, highly effective discipline it is best approached systematically and incrementally.
First, just what are we talking about? Here’s an excellent definition of MDM from Gartner’s IT Glossary: “MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.”
Gartner goes on to say that “Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts.”
The metadata residing in the system includes information on:
– The means of creation of the data
– Purpose of the data
– Technical data – data type, format, length, etc.
– Time, date and location of creation
– Creator or author of the data
That’s a lot. And it can lead to problems. For example, when moving data from one place to another, you have to know how it transforms, who owns it, where it comes from and what rules govern the data. This may mean going back into the ETL integration and trying to unscramble initial problems in data mapping and compliance. You can try tackling these problems using a spreadsheet (that way lies madness) or turn to IT for an answer that may take months in coming – not a particularly attractive solution if your business is attempting to become more agile
The fact is, that for many organizations, a full-bore MDM deployment right from the start is overkill. The massive effort required proves to be too complicated, expensive and inevitably winds up being put on hold.
To avoid this kind of quagmire, there is a better way. As I mentioned above, start small and think big. To be more specific, start with a data dictionary and ease your way into MDM over time. (A data dictionary is a centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format.)
The poster child for this approach is one of our valued customers –a large public sector organization. Here’s their story.
The organization’s core business is the assessment and collection of taxes and duties for the Republic or Ireland. With more than 65 offices countrywide, the agency has a staff of over 5700. The organization’s authorized users have access to operational business and third-party data in its data warehouse for query, reporting and analytical purposes.
The data is complex and growing rapidly. Historically the agency’s metadata has been accessed from multiple sources using spreadsheets and other business documentation, a fragmentary and ineffective solution.
Fortunately Talend’s integrations solutions are already being used by the organization as the corporate ETL tool. Because much of the technical metadata around data manipulation and transformation were already being captured by these Talend solutions, the implementation of Talend’s MDM unified platform made a lot of sense.
The implementation included the initial use of a data dictionary within the MDM platform in keeping with the “start small, think big” dictum. In addition, the organization was able to leverage the existing skills and knowledge of their business and data analyst employees who are familiar with Talend Studio.
Overall, the agency avoided additional costs for their metadata solution, reduced operational costs, and solved the business problem of knowing where to find pertinent data for reporting purposes.
Through their use of Talend MDM, we anticipate that the agency’s metadata solution will increase the understanding of data throughout the organization. This, in turn, will lead to improved decision making and improved data quality over time. Plus, the solutions’ web user interface will help cut metadata management and deployment costs. It provides the organization’s business analysts with access to one centralized location to gather metadata that had previously been scattered around the organization in various formats and residing in individual business and technical silos.
For many companies dealing with today’s influx of big data, the Revenue incremental approach is a good one. They can start by building a data dictionary for free and then upgrade to handle more users and provide additional functionality.
After all, MDM is a journey, not a destination. Companies that elect to follow this path will achieve cost effective and satisfying results by starting small and then moving ahead with all deliberate speed.