Our client is using the CRM for Healthcare industry has a terabytes of data and concurrent queries were hitting the system badly. The database handling through relational database like MySQL was degrading the performance of the application. We at Ira Softwares re-designed the application to run as BIG Data application. The query system was injected using the Apache Spark. Elastic Map Reduce(EMR) service of AWS was deployed and the performance of the application increased multiple folds.
The client is a specialized retailer with over 400 locations and a revenue of over a billion dollars in FY 2017. The client has a large customer base of around 5 million distinct clients. However, they were having trouble streamlining their marketing strategy. Customers were receiving more than 40 emails/coupons per week in certain circumstances, with offers that were irrelevant to their needs. As a result, customers were dissatisfied, and the return on investment (ROI) on their marketing activities was low.
The client had a specific goal in mind: to boost consumer engagement and improve the ROI of marketing initiatives (coupon redemptions and frequency of visits). IRA Softwares developed a sophisticated consumer segmentation solution based on machine learning algorithms, as well as a bespoke ROI effectiveness solution that answered the client's requirements. The client segmentation models developed by IRA Software indicated three main customer groups:
Every month, all of the linked insurance companies send the consulting company a large and rising number of medical, pharmaceutical, and enrolment claims data. Their existing data analysis pipeline couldn't keep up with the additional workload, and their data warehouse's capacity had reached its limit. The ETL data ingestion and reporting processes were also not performing well. As a result, they were limited in their capacity to bring on new clients and expand the firm.
IRA Softwares was hired to examine the firm's overall ETL difficulties, provide recommendations for removing bottlenecks, and dramatically enhance the firm's data analytics platform's performance and scalability.
The three deliverables of IRA Software's solution for the benefits and human resources consulting business were designed to set the firm's data analytics program for success.
To begin, IRA Software created a unique data-driven business rules engine (BRE) to assess income, medical, prescription, and enrolment claims. In order to detect illnesses, care gaps, and hospital admissions, the BRE was used to determine if a claim line satisfied a rule-based on diagnostic codes, procedure codes, location, gender, or a mix of multiple factors. Furthermore, IRA Software worked with internal personnel to optimize the existing load of the data warehouse in order to improve efficiency and reporting performance.
Finally, Tableau was added as a reporting and analysis tool to boost flexibility and shorten the time it takes for business users to offer new reports and analyses. Tableau offered end users with quick and simple access to all data, as well as self-service capabilities, allowing them to link historical data warehouse structures with newly built rules and disease diagnosis structures.
The combination of IRA Software's unique data-driven BRE and changes to the data input and database platform areas resulted in considerably enhanced processing performance. A typical client's monthly data processing time was reduced from hours to minutes. Segal has been able to enrol additional clients and increase its company because of this better analytics platform, which is scalable.
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