DMI evaluates technology trends to modernize solutions and transform the user experience to obtain faster and more granular insights from data, thereby delivering meaningful results.
By obtaining faster and granular insights from data, we deliver meaningful results. DMI analytics experts have decades of experience in gaining insights out of data and tying it to successful program outcomes. We evaluate and analyze existing legacy applications and databases, identifying the best solution to transform legacy applications into data-driven systems to obtain accurate and actionable insights. DMI follows an iterative methodology for data analysis, starting with the “Requirement Gathering” phase, which is crucial in ensuring that each requirement has been understood correctly. This phase is followed by the “Data Construct” phase, which is further divided into “Data Ingestion” and “Data Analysis.” Initially, in the “Data Ingestion” layer, structured, relevant sources will be identified and integrated.
Then other data types such as semi-structured and unstructured data from these sources will go through the processes of Extract, Transformation, and Load (ETL); standardization; and validation. The next phase is comprised of curating and enhancing tasks such as data aggregation, reporting, dashboards, scorecards, and related activities using algorithms based on the request. Predictive models created using machine learning algorithms and BI reports, and dashboards are then deployed. In the “Maintenance” phase, Preventive, Perfective, Corrective, and Adaptive maintenance is applied to legacy BI systems on a scheduled basis. We have successfully employed this approach to transform several of our past clients from data aggregators into data science organizations.