Case Study

Case Study — Assessing the Ability to Handle Real Time Big Data in the Financial Sector

Assessing the Ability to Handle Real Time Big Data in the Financial Sector

Client: A major financial sector organization
Industry: Finance
Company Size: NA

NOTE: Several of our clients have strict corporate policies against associating their names with testimonials and case studies for any product or service. As a result, this case study describes a situation for which the related client has requested anonymity.


An extremely large and influential financial organization processes billions of transactions as they flow through the financial system. These transactions come in a variety of forms including check, electronic, and nontraditional formats. Transaction handling generates close to 100 terabytes of data annually. This organization started asking tough questions, such as: what could we accomplish if we tied together all of these transactions and allowed our staff, and our customers, to analyze them in real time? Could we find ways to speed our transaction handling and, thereby, save potentially millions of dollars in interest? Could we find ways to interrupt fraud as its occurring?

These questions and hundreds more led the organization to investigate whether a data warehouse could be built to bring together huge streams of data, and ultimately support the envisioned business processes. The decision was made to ask a data warehousing specialist organization to perform an analysis and deliver an opinion on the feasibility of a successful outcome.


Significant challenges faced in performing this analysis included:

  • Dealing with multiple, geographically separate, information technology groups, each protective of its data and having its own conception of data warehousing.
  • Designing a solution that could handle huge volumes of data in real time while supporting thousands of simultaneous users.
  • Ensuring that the selected solution was stable and would provide adequate backup and failover protection.
  • Delivering a design that accomplished all of these goals at a viable cost point.


This organization considered a number of vendors for this project. Dataspace proposed a solution that capitalized on its data warehouse assessment methodology and a project team consisting of consultants with significant experience in banking, data warehousing, and the intersection of the two fields.


After considering a number of vendors, this client chose to work with Dataspace.


After a two month project, Dataspace presented viable options to management. This presentation was accompanied by a 100 page analysis that reviewed the situation and provided details on the selected approach. The project team found that the vision was, indeed, attainable. Of particular interest was the recommendation that the client consider using the Amazon Redshift database solution to house the data warehouse. This approach offered a combination of security, performance, and cost effectiveness.




Headquartered in Ann Arbor, Michigan, Dataspace is a consulting firm with a national client base. Since its founding in 1994, the firm has focused solely and passionately on providing unparalleled expertise in data management, business intelligence, and data warehousing strategy and implementation.

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