The Decision Maker

7 Ways Business Intelligence Professionals Mitigate Data Warehouse Risks

Posted by Austin Wentzlaff on Aug 6, 2014 5:04:37 AM

“True intuitive expertise is learned from prolonged experience with good feedback on mistakes.” –Daniel Kahneman, Nobel Prize in Economic Sciences.

In my most recent article, 7 Challenges to Consider when Building a Data Warehouse, I wrote about a few major complexities associated with building a data warehouse that are often overlooked by the ambitious credit union do-it-yourselfer. The do-it-yourselfer has a mentality that hiring someone to do the project will increase the cost significantly. In some cases this is true, but in the case of building a data warehouse they are at a significant disadvantage to an experienced business intelligence (BI) firm. The challenges of building a data warehouse can be extremely overwhelming. Fortunately, there are professional BI firms dedicated to building data warehouses which have experience solving these complexities.

Here’s how experienced BI firms can help mitigate the seven data warehouse risks laid out in my last article:

  1. Data Quality – Using a BI firm dedicated exclusively to an industry, such as the credit union industry, ensures a data warehouse will have superior data quality. BI professionals are familiar with the data integration process and the common problems specific to the industry such as where inconsistent data will be found and how to deal with duplicates and missing data. They have various checks in place that make sure the quality of data meets expectations and the data is properly fed into the data warehouse. Their experience saves countless hours of trying to figure out how to ensure data quality.
  2. Understanding Analytics – One of the most essential parts of a data warehouse project is understanding what outcome the data will yield. Experienced BI firms have gathered information about reporting and analytics from their past clients. Many of the reporting and analytics tools were requested by other credit unions to serve one or more of their business functions. This enables credit unions new to BI to leverage the ideas of other credit unions that worked with the BI firm in the past.
  3. Quality Assurance – BI firms dedicated to credit unions know exactly what data needs to be tested, where it needs to be tested, why it needs to be tested, when it should be tested, who on their team will test it, and most importantly how to test it. Experienced BI firms have already established a successfully functioning Software Testing Lifecycle. This saves time and money that would have been dedicated to developing a testing strategy from scratch and hiring new employees needed for testing.
  4. Performance – BI firms have realistic performance goals and the experience needed to achieve those goals. They can ensure that a data warehouse will meet the level of performance desired by the credit union. This is a crucial step that saves credit unions the cost and headache associated with trying to adjust performance after completion.
  5. Designing the Data Warehouse – A professional BI firm will know the proper design requirement questions to ask to ensure the data warehouse is developed according to the credit union’s needs and specifications. Their past experiences increase the probability of the credit union will having an effective data warehouse, which provides the best end-user experience and saves time and money required for redesigning and fine-tuning any misinterpreted design requirements.
  6. User Acceptance – BI firms have past experience and success in integrating data warehouses into credit unions. They also have the ability to train and educate credit union employees to ensure they know how to use the data warehouse and its reporting capabilities. This increases the probability of users fully utilizing reports and analytics. By making the process smooth and intuitive, the BI initiative has a higher chance of success and the end users will be able to use the reports and analytics to properly drive decision making.
  7. Cost – When justifying a do-it-yourself project, people unintentionally use best-case scenarios. They ignore the complexities that inevitably end in more resources being required to finish the project. As the points above show, building a data warehouse is a classic “you get what you pay for” situation. In several cases across all sizes of credit unions, in-house efforts have led to either an inferior data warehouse or have greatly overrun initial cost and schedule estimates. For the cost of engaging an experienced credit union-focused BI firm, the organization gets not only BI-specific technical expertise but also a wealth of industry-specific knowledge that leverages past experiences.

“If you think it’s expensive to hire a professional to do the job, wait until you hire an amateur.” – Red Adair

Article written by: Austin Wentzlaff, Business Development Analyst at OnApproach

Topics: Business Intelligence, Big Data, Credit Unions, Data Integration, Analytic Data Model, Data Analytics