Case Study Data Warehousing for a Health Benefits Company A health benefits company operating in the United States serves more than $11\mathrm{.}9$ million customers. Its product portfolio includes a diversified mix of managed care products, including Preferred Provider Organizations $($PPOs$),$ Health Maintenance Organizations $($HMOs$),$ and Point$-$Of$-$Service $($POS$)$ plans. The company also offers several specialty products, including group life and disability insurance benefits, pharmacy benefit management, and dental, vision, and behavioral health benefits services. Business Need The company had a significantly large database, which was consolidated from various systems using an ETL $($Extract$,$ Transform, and Load$)$ tool. This tool would mine data from a database and then transform and store the mined data in a data warehouse. The company wanted to outsource the reengineering of the data warehouse and partnered with Infosys to build a modular, scalable architecture so that the processing batch time could be reduced considerably. After the success of this engagement, Infosys handled the maintenance of the data warehouse, thus freeing the client's internal resources to tackle other pressing tasks and lending flexibility in operations. Challenges and Requirements The task of taking a huge database and reshaping it to improve efficiency is a difficult undertaking. Infosys found that: $$ The existing ETL mappings were inefficient and this reduced performance while the transformation operation was being performed. Infosys had to re$-$engineer the whole process to derive significantly better performance $$ The existing code was not of the highest standards and Infosys was faced with poor code manageability. This meant that Infosys' engineers had to carry out tasks to make the programs easier to maintain $$ The application took too long to run and this was proving difficult for the client because of the huge amounts of data involved. The client wanted Infosys to ensure that the speed of the operations was boosted by a remarkable factor. Companies' Role Since time was as critical as cost savings, Infosys used its Global Delivery Model and its team of nine personnel completed the project in $16$ months. The initial task concerned a detailed study of the existing ETL model to identify the bottlenecks. Once this was completed, the Infosys team determined areas of improvement. These changes were implemented in a short duration, resulting in an ETL that processed information at a faster pace. Once the speed factor had been satisfactorily handled, Infosys had to ensure the future maintainability of the ETL. This was done by making the ETL concurrent and scalable so that the client could confidently ramp up the storage and processing capabilities of the data warehouse at a later date if required. The final task before Infosys was maintaining the data warehouse so that the client's key personnel could handle other tasks. This is an ongoing task and is being achieved to the satisfaction of the client. Benefits The new ETL delivered many benefits to the client including: $$ The new batch processes ran significantly faster than before, thanks to the tightly integrated code. The immense speed ensured a $70\%$ time reduction in batch processes and enhanced the efficiency of the client's processing capabilities $$ Flexibility was also improved and the client could easily add newer data from sources that were not initially supported. This improved the capabilities of the data warehousing solution $$ As part of the improvement process, the client's data warehouse solution started generating more useful output and this helped the company to take key business decisions with high$-$quality data $$ The continuous enhancements that are being carried out to the production environment by automating the load processes, adding reconciliation and automated balancing processes, are helping the client to improve the satisfaction of its customers To Discus In class: Individual $/$ Group $1)$ Reflect on recent data discovery strategies to recommend an appropriate method for incorporating business intelligence in industrial information resources. $2)$ Define and data cubes and multi$-$dimensionality in business information repository and apply the models to develop a quality data warehouse. $3)$ Analyze the industrial data resource architecture, management process for information resource integration, and the process of establishing data relationships to build a data warehouse that assists management in the decision$-$making process. $4)$ Explain business intelligence technologies to develop intelligent information resources that enable users to view data patterns by deploying various tools.