Company Information
A leading telecom company offering in-flight Wi-Fi services faced a significant challenge. Their Product Managers needed quick, dynamic insights into user behavior and product performance. However, an ODBC connection imposed limitations on their Power BI setup, necessitating tedious, frequent manual data queries. The Product Managers often requested multiple reports daily, each with different date ranges and filters, creating a repetitive and time-consuming workload for data analysts. To streamline their data analysis and reporting, we developed an innovative Streamlit app, revolutionizing how Product Managers accessed and utilized critical data.
The Challenge
Data Access Limitation: With the ODBC connection in place, direct query mode in Power BI was disabled. This forced the team to manually extract and aggregate data, a process ill-suited to the fast-paced demands of the telecom industry.
Manual Reporting: The Product Managers frequently requested customized reports with various date ranges and filters, resulting in a repetitive and time-consuming task for data analysts. This delay hindered swift decision-making and strategic planning.
Dynamic Data Needs: They also required near-real-time data to effectively monitor user engagement, churn rates, and session details. The existing manual process could not keep up with these dynamic data requirements.
Example – Distinct User Count: Product Managers often require distinct counts of users within selected date ranges. However, without direct query capabilities, analysts had to aggregate the data and then import it into Power BI. While this allowed for fixed daily, weekly, and monthly counts, it did not support the dynamic date ranges the Product Managers needed. As a result, analysts had to manually query the data every time the Product Managers requested unique user counts for specific periods. This repetitive task exemplified the inefficiencies created by the ODBC limitations.
Our Approach
Analysis Requirements
Collaborated closely with Product Managers to pinpoint the key metrics and data points essential for their analyses. This included unique user counts, session durations, churn rates, and other critical KPIs.
Data Query Automation
Developed sophisticated Python scripts that take user inputs via the Streamlit app. Based on these inputs, the scripts dynamically generate and execute queries against the data source, bypassing the ODBC limitations. This ensured that all necessary data was available for immediate analysis without manual intervention.
Streamlit App Development
Created an intuitive and interactive Streamlit app, mirroring the functionality of Power BI dashboards. This app featured advanced filters, interactive charts, matrices, and robust Row-Level Security (RLS) to protect sensitive data.
Custom Visuals
Developed unique visuals using Python, CSS, and Java programming, which could not be created in Power BI. These visuals were tailored to Product Managers specific needs and made their work significantly easier.
User-Friendly Interface
Designed the app with an emphasis on usability, allowing Product Managers to easily manipulate filters and generate customized reports on demand. The interface was sleek, intuitive, and tailored to their specific needs.
Export Capabilities
Enabled exporting of all visuals into table form or PDF, providing Product Managers with versatile options for reporting and presentation.
Automation and Sharing
Streamlit app's browser-based nature made sharing incredibly simple. All that was needed was to share the link to the Streamlit app with the Product Managers, allowing them instant access to the tool and its features.
The Results
Enhanced Efficiency
The Streamlit app automated the cumbersome manual data querying process, saving countless hours for data analysts and Product Managers alike.
Dynamic, Real-Time Reporting
Product Managers can now access and analyze data in near-real-time, with the flexibility to apply various filters and date ranges. This dramatically improved their ability to respond to emerging trends and make proactive decisions.
Custom Visuals
The unique visuals developed specifically for Product Managers provided deeper insights and easier analysis, significantly improving their workflow.
High User Satisfaction
The app's user-friendly design and powerful functionality garnered enthusiastic feedback from Product Managers. They appreciated the newfound autonomy and efficiency in their data analysis capabilities.
Conclusion
Our proactive development of a custom Streamlit app demonstrated our deep understanding of the client’s needs, addressing pain points before they were fully articulated. By anticipating the demand for high interactivity and dynamic reporting, we provided a forward-thinking solution that significantly improved the telecom client’s product health reporting process. The app’s automated queries, unique visuals, and intuitive interface empowered Product Managers with real-time insights, eliminating manual inefficiencies.
This case study highlights our ability to deliver tailored solutions that tackle complex challenges with foresight and precision, advancing client goals through advanced data analytics tools while ensuring cost-effectiveness. Leveraging our expertise, clients can streamline data processes, enhance decision-making, and proactively navigate the dynamic telecom industry landscape.
