Our team pilots, develops, and implements applications in predictive analytics that our clients can use to get higher value from their existing data. We perform predictive modeling based on historical information (i.e. capacity planning) for Machine Learning. We use the ROI analysis in our meetings to support strategic decision making. Our staff collects and analyzes user requirements to create conceptual and logical data models for databases and files. We work closely with our clients’ enterprise data architects to normalize and design the data models. Our knowledge of the data enables us to help our clients’ data groups better understand the business processes that we want to depict in the model to create a solution.
Our personnel analyzes actual transaction volumes and data usage, as well as future planned business growth, to determine the impact on the application and the need for additional capacity.
We replicate data primarily for dummy/test environment activities for development and testing purposes. We manage data quality issues within the vendor data from the legacy systems, designs remediation approaches to ensure that the data imports cleanly into the DCPS2 vendor database, and implements them.