Renesas Electronics
project overview
turning fragmented backend data and limited usage history into long-term reporting insights.
project type
Internship
year
summer 2026
my role
Data Analytics Intern
skills/tools
Power BI, Excel, SQL, Power Query
a technical usage tracking solution designed to help analysts understand report engagement and make better decisions about what to maintain, improve, or retire.
When I worked in the Sales Operations division of a global semiconductor company, data played a central role in nearly every business decision. My team’s job was to take large amounts of sales and operational data and translate them into dashboards, reports, and insights that helped leaders and stakeholders understand performance and make informed decisions. But there was a problem: while the organization had built a large number of Power BI dashboards and reports, it was difficult to understand which ones people were actually using. Power BI only retained detailed historical usage data for 30 days, and access to that information was limited to users with a Pro license. For analysts, this made it difficult to identify which reports were valuable, which needed to be maintained or improved, and which could potentially be retired. My job was to create a more accessible and sustainable way to track and analyze report usage over time. Although I had previous experience with data analysis and visualization, this was my first project using Power BI. I learned the platform while building the solution, using Power BI and Power Query alongside Excel, SQL, and Databricks to collect, clean, transform, and analyze usage data. I developed a reporting solution that gave analysts greater visibility into how dashboards and reports were being used beyond Power BI’s standard 30-day window. Instead of relying on a short snapshot of activity, the team could evaluate longer-term usage patterns, compare reports, and identify content with low or declining engagement. This gave analysts better information for deciding where to spend maintenance time, which reports warranted further investment, and which redundant or unused assets could be consolidated or retired. The project ultimately turned report usage itself into a measurable data point. It gave the team a clearer picture of the value of its reporting portfolio and provided stakeholders with a more data-driven way to manage and improve the analytics tools they depended on.
