Deeksha R

• I took up the projects in the very early days of joining and learned GCP as a new tool.
• Worked on the end-to-end data development for the channels team, which in turn is used for the Qlik dashboard analysis.
• Streamlining the CC FTE manual process to Google Cloud Platform (GCP) from Excel and automating the process, which has reduced the hours taken and the steps to execute the process.
• Played a vital role in the reinstatement of FTE logic for the year 2023, and for the ongoing months of the current year across the TOP17 markets.
• Continue to contribute support and deliver the report within TAT for the channels team.

Health Care Economics: Humana

• Automating and optimizing the reports using SAS macros in UNIX through shell scripting, and scheduled on a crontab.
• Reducing the processing time for the reports by automatically kickstarting every month, negotiating the manual intervention, and thus creating error-free reports.
• Systematizing the process of table creation in SQL Server using a Python script, scheduling it on the Task Manager, and pulling the same into the SAS environment.
• Maintaining and enhancing the existing reports, and providing periodic updates to the client and stakeholders about the discrepancies.
• Using SASPY, I am creating the dataset in SAS through a Python script and extracting the information from the website using Python web scraping.

RETAILERS: IRI

• Routine periodic updates to the client and stakeholders to initiate the upgrades in the client files and hierarchy break. Review hierarchy files on a periodic basis, and communicate any upgrades.
• Extensively worked on multi-code, multi-descriptions, and multi-maps, as well as other procedures related to quality checks in a Linux environment using SAS and Python.
• Meet ad hoc requirements within a gripping timeline.
• Creation of datasets that are used by teams across global locations. Handling huge datasets, performing analysis, and creating reports.
• Post-production: prepare standard reports based on client requirements by comparing the EAL report with the retailers' file, the placement change report, and the report extraction for perishable items, etc.

• This includes the forecasting, pricing, marketing and management of the distributions which highly depends on the historical and current data analysis, competitor analysis, KPI tracking.
• Revenue management strategy is measured using the KPIs such as occupancy rate, average daily rate, revenue per available room, total revenue and net revenue.
• Using the tool KNIGHT TEMPLER, which gives the insight of the data for setting the best price for hotel rooms, revenue based on the location of the hotel, based on the season and other factors which affect the hotel revenue.
• Comparing the previous month’s data building the dashboard to get the complete pattern graphically and conveying the revenue systems based on the daily, monthly and yearly collected revenue.