Skip to content

Case Study

Data Engineering

Film Advertising Analytics & Performance Tracking Platform

Overview

JashDS developed a comprehensive data warehouse and analytics platform for a film advertising company, integrating PostgreSQL databases and Google Analytics through automated ETL pipelines built with Apache Airflow on Google Cloud Platform. The solution delivered real-time campaign performance dashboards that enabled film distributors to optimize marketing strategies and track social media traffic attribution, significantly improving their ability to analyze film campaign effectiveness and make data-driven marketing decisions.

About the Client

The Challenge

Key Results

Our Solution

Technologies Used

Google BigQueryApache Airflow (Google Cloud Composer)Google Cloud Platform (GCP)PostgreSQLPythonGoogle AnalyticsETL/ELT PipelinesData Warehousing

Related Case Studies

← Back to All Case Studies

Data Engineering

An EV cab booking company required a fully automated backend integrated with WhatsApp Business API to streamline booking workflows and enable real-time trip management. Our team built a scalable Python and PostgreSQL-based solution with FastAPI that increased booking efficiency by 80% and ensured seamless trip updates and notifications through automated message parsing and asynchronous processing.

Read More

Data Engineering

JashDS developed a scalable serverless AWS architecture for a dash cam technology company, replacing their legacy FTP system with a comprehensive solution featuring ESE Fargate, Lambda functions, S3 storage, SQS and Kinesis queuing to handle video footage and telemetry data processing. The implementation supported a projected tenfold increase in data volume while providing automated scaling, reduced latency, and improved reliability for their new dash cam product line through modern cloud-native data processing pipelines utilizing Aurora RDS, ECS Fargate, and site-to-site VPN connectivity.

Read More

Data Engineering

A cybersecurity and compliance platform successfully migrated from legacy infrastructure to a modern cloud-native architecture, overcoming complex multi-tenant database challenges and fragmented data storage that threatened scalability and competitive positioning. The solution achieved improvement in data processing efficiency through implementing real-time Change Data Capture pipelines, streaming data processing with AWS Kinesis and Databricks, and centralized analytics infrastructure using Amazon QuickSight.

Read More

Have a similar challenge?

Connect with us