Proof of Concept Data Solutions

A Proof of Concept (POC) built on sample data does nothing for your unique set of demands and problems.

The most significant challenges organizations face when deploying business intelligence, and analytics solutions are the ongoing technical unknowns and R&D required to make the system work for their custom needs

For a POC to be successful, it is essential that the data accurately represents the data model and attribute values pertinent to your business. This ensures that the outcome addresses issues that matter to your business. Also, the POC should ideally address future requirements and not just standard reporting needs. Business requirements change all the time, and a business intelligence system should be able to adapt to these changes and continue enhancing the insights it delivers.

At Menerva we offer a range of solutions in this area.

We can help you with

Proven Technologies

Implementing a proof of concept or prototype using new or already proven technologies.

Actual Business Model

The prototype can be realized using the client’s preferred datasets (which can even be as-is or de-identified) or a dataset that is from manufactured data but fully represents the business data model and inherent relationships between data elements and their values.

Your Business Requirements

The primary goal of such a prototype is to validate if the business requirements are answered by the data solution it seeks to provide.

Implementation Tools & Technologies

  • Tools in the Hadoop ecosystem
  • Open source or commercial paid software depending on the proof of concept and technology requirements.