Spend Analytics helps find the top supplier, item, cost center from the spend data.
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1. Which dataset did you use? Public Medicaid enrollment data from Kaiser Family Foundation (KFF), Centers for Medicare & Medicaid Services (CMS), and MACPAC. Covers all 50 states + DC, 69 months of national enrollment trends, and 18 months of renewal outcomes during the Medicaid unwinding (2023-2024). 2. How did you…
1. What dataset did you use? I used a "Mental Health Crisis" dataset covering 50 countries from 2000 to 2024. The dataset included the following key attributes: Depression prevalence Anxiety prevalence Suicide rate per 100,000 DALY burden measures Treatment access and treatment gap Social media usage Academic pressure…
OTT Platform Analytics This dashboard provides an integrated analytical view of OTT content performance by combining content attributes like genre, language, ratings, and viewership into a single decision-support framework. It connects audience engagement metrics with content characteristics to identify trends,…
Which dataset did you use? I used a service management dataset with around 10,000 records covering the last 3 years. It includes ticket details like issue type, priority, status, SLA, resolution time, location, category, and satisfaction. How did you analyze or prepare the data? I cleaned the data by removing duplicates…
1. Which dataset did you use? The dataset which is synthetic and represents the simulation of real-world service operations of a Car Service network running across 7 service centers in Chennai. It captures 23 months of day-to-day service activity, from the first customer walk-in to the final invoice — tracking every repair…
1. Which dataset did you use? Bangalore Traffic Dataset from Kaggle 2. How did you analyze or prepare the data? I used Auto-Insights and the AI-Assistant to gain few insights and build dashboard based on the inputs. 3. Who is the intended audience for your visualization? Ideal for general public, urban planners and smart…
This Treemap visualization provides a comprehensive breakdown of the 'Daily Rate' across Human Resources, R&D, and Sales, segmented by Gender. By leveraging Oracle's advanced Trellis layout, I have identified key distribution patterns to help leadership ensure equitable resource allocation.
I used the Auto Insurance dataset provided by Oracle. I created an aggregate visual of insurance claim amounts by state and subseqiuently did a drill down to look at the most common accident types by weekday for each given state. My intended audience is state agencies that would use the analysis to provide a Public Service…