ABOUT CLIENT
The client, a prominent international e-commerce giant, navigates a complex data landscape, managing vast data critical to its operations and decision-making processes. The data, stored in Google Sheets and BigQuery, required intricate transformations to reach its final destinations, introducing time-consuming processes and a substantial risk of errors in the data flow.
ZELAR ROLE IN PROJECT
Zelar engineered a react-based application with AI/ML functionality. It allows parents to record and upload videos of their child’s activities, and the Al analyzes the footage, condensing it into concise summaries. The technology enables doctors to track progress, correlate behaviors with medication, and identify potential regressions in autism and neurological disorder cases.
THE CHALLENGE
- Complex Data Journey: Managing data across Google Sheets and BigQuery, involving numerous transformations.
- Time Consumption: The complexity of data handling resulted in prolonged processes.
- Error Risk: The intricate data handling process introduced a significant risk of errors.
THE SOLUTION
- A Python-powered ETL (Extract, Transform, Load) solution was developed to streamline the data pipelines, ensuring seamless data integration from various sources, skillful data manipulation, and efficient data loading to designated destinations, which were BigQuery and Google Sheets.
KEY RESULTS
- Optimized Data Access: Streamlined BigQuery flow for enhanced accessibility and efficient retrieval.
- Effortless Report Generation: Simplified client reporting, aiding sales tracking, trend monitoring, and customer insights.
- Timely Communication: Integrated Google Sheets for user-friendly data extraction and automated updates, ensuring prompt daily reports.
- 33% Pipeline Processing Time Reduction: Achieved efficiency gains in data processing.”