Executive Summary
Neuralytix interviewed two different development firms to compare how they developed the same data-intensive application using different approaches. QPAIR (www.qpair.io) used various point solutions to build the platform and application, whereas Aluna Group (www.alunagroup.com) built the application using InterSystems IRIS Data Platform™, a unified data platform that provides comprehensive data management, interoperability, and analytics capabilities in a single product. The result of our investigation was that Aluna Group was able to develop the application for a lower total cost while using fewer employees and fewer total hours.
Introduction
Data is undisputedly the lifeblood of every organization. All organizations experience their own data challenges and their own data needs based on specific sets of business requirements. This has led to a diverse set of requirements for supporting data-driven applications, as well as a preponderance of data management technologies available in the marketplace to support these requirements. Many of these tools and technologies provide specialized capabilities such as relational data management, document data management, business intelligence, natural language processing, data integration, and more. Further, over the next few years, the amount of data and the number of tools are forecasted to continue to expand. This trend has given rise to the need for simplification, consolidation, and the introduction of integrated data platforms.
Currently, there are various approaches to developing data-intensive applications. One common approach is to use a variety of individual, specialized point solutions. Another approach is to use an integrated data platform such as InterSystems IRIS Data Platform. Neuralytix believes that using an integrated platform is the preferred approach in all but the most unique circumstances.
This paper compares the two approaches.
Comparison of Approaches
Neuralytix believes that, in most cases, an integrated data platform provides the customer with three main advantages:
- Lower development cost
- Faster time to deployment
- Simpler ongoing support and maintenance
To validate this belief, Neuralytix worked with two different development firms that had been tasked with developing the identical data-driven analytic application for the Office of Sustainability at a large research university.
The university wanted a data-rich application to combine and aggregate 50 separate initiatives with different data types and analytical requirements for its end users, which are organizations looking to enhance their “green” efforts. For example, organization might want to understand the benefits of installing rooftop solar panels compared with a larger-scale solar farm in terms of cost, carbon reduction, and overall environmental impact. To accomplish this, both companies were tasked with building a data-rich application that could process and aggregate data from a variety of different data sources, analyze both structured and unstructured data, perform natural language processing of the data, and provide enough flexibility so the results of the analysis could be presented to a variety of audiences. This required that the application be able to highlight specific aspects of different projects, sort projects by a variety of criteria, and evaluate the effectiveness of projects using user-defined criteria. QPAIR was tasked with developing the application using point solutions, and Aluna Group was tasked with developing the same application using the InterSystems IRIS Data Platform.