The Decision Maker

The Data Warehouse is not Enough

Posted by Nate Wentzlaff on Oct 27, 2015 2:05:49 PM

Relying solely on a data warehouse, without an enterprise data management strategy, is a recipe for disaster.

 

Credit unions are beginning to invest heavily in big data and analytics.  When deciding how to allocate funds in this space, leaders are awash with buzzwords and conflicting advice.  One of the most common terms used within big data and analytics is: data warehouseDeciding whether to build or buy a data warehouse is an important strategic decision for credit unions.  Unfortunately, many decision-makers get lost in discussions about storage capacity, data processing, data visualization, etc.  All of these concepts are important.  However, data warehousing is not the solution.  It is a powerful tool in an enterprise data management (EDM) strategy. 

Without master data management (MDM) to define data elements, agree on business terms, and document the logic of data integration, the data warehouse will be confusing to end users.  Because data fields are defined differently throughout a credit union’s source systems, terms are used interchangeably (without the same meanings).  This will bring more confusion.  A data warehouse, which is supposed to be the Single Version of Truth (SVOT), must have an effective EDM strategy to reach its fullest potential.

Most Valuable Asset

The internet has made data the most valuable asset in the credit union industry.  Credit unions are realizing the value of their data and are tailoring their budgets to invest accordingly.  Understanding that data is the most valuable asset of the credit union is the first step toward developing an EDM strategy.  However, a search for the word data will bring up thousands of conflicting pages instructing credit union leaders to handle their data in certain ways (while also mentioning their latest and greatest analytics applications). 

Enterprise Data Management (EDM)

While credit union leaders begin to mine their data for golden information, confusion will set in if data is not thought about in a strategic mindset from the beginning.  Raw data from a single source system has value;  however, once credit unions begin assessing all their different streams of data, they will soon realize how complicated it is to effectively integrate them into their SVOT.  Before building a data warehouse and everything else needed for effective analytics, credit unions must establish an EDM strategy.

Analytic Data Model

After developing the EDM strategy, business leaders must work to establish an analytic data model (ADM) that will be used to bring all the data together.  This is where many credit unions are making the mistake of handing over the data warehouse to the IT team.  Without intimate involvement from the business, the data warehouse will turn into another database that will become confusing to end users.  The ADM is where IT meets business.  The business must define and own all the logic that will be needed to meet their reporting needs.  IT must maintain the integrity of all data that is populating the data warehouse.

Semantic Layer 

After building the ADM, a semantic layer should be built to establish common business terminology from the data warehouse.  Building a semantic layer has three benefits:

  • Eliminates the need for users to have database language skills
  • Gives users the freedom to build ad hoc reporting
  • Establishes common business terms for all data consumed from the data warehouse

The third benefit is usually overshadowed by the first and second.  Ad hoc reporting is only as good as its underlying datasets, and how they are used for decision making.  Understanding and documenting how the semantic layer is delivering data from the data warehouse will establish an SVOT that is easy to communicate throughout the credit union. 

Master Data Management

In order to begin leveraging analytics in daily activities, credit union leaders must finally develop an MDM strategy.  Just as human languages change over time, definitions of data will change as the credit union journeys into new ventures.  This requires effective management of metadata (“data about data”).  Storing “data about data” seems redundant, but it is one of the most valuable aspects of big data and analytics.  The language of the credit union will be determined by its leaders through metadata, and as any good student of history knows, language is very powerful in changing the course of any country (or credit union).

Continuous Analytics Improvement

As credit unions advance into the future, their analytics requirements will change along with business and IT innovations.  Establishing an EDM strategy, ADM, and semantic layer will be essential for building advanced analytics.  Managing data is the responsibility of business and IT.  A data warehouse alone is not sufficient for building analytics.    Analytics will only be as powerful as the underlying data and how it is managed. As credit unions develop their EDM strategies, the data warehouse will continually improve and become a powerful tool to advance the credit union into the future.

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Topics: Analytics, Data warehouse, Semantic Layer, data management

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