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Project Duration
Ongoing since 2023

Client Industry
Marketing and Advertising
Target Markets
United states

Group M

Task-Based Data Workflow Automation & Dashboarding Across Cloud Ecosystem

Technology Stack

No items found.

Client Overview

Challenges in Modeling Subscription and Business Metrics

GroupM is a leading global media investment company that helps brands maximize the value of their marketing through data-driven strategies, media planning, and performance optimization. As part of WPP, GroupM partners with top-tier advertisers to deliver innovative media solutions across digital, TV, and emerging platforms, empowering businesses to reach their audiences effectively and efficiently.

Solutions Delivered

Scalable, reliable, repeatable data workflows

Event-driven pipelines with Pub/Sub

KPI visualization for faster decisions

Tasks, sprints, documentation streamlined

Team Composition

Data Engineers

BI Developers

Cloud Automation Experts

Agile Project Coordinators

Engagement Type

Contractual / Ticket-Based

Task Assignment via JIRA

Key Challenges

Building Scalable and Reliable Data Infrastructure

Complex ETL Development

Built robust pipelines using BigQuery, Airflow, Dataform workflows

Automation Stability

Ensured seamless workflows via Pub/Sub, Cloud Functions

Tool Familiarity

Learned Looker, Cloud Repos setup, dashboard creation

Strategic Roadmap

The project was executed as a series of discrete JIRA tickets, with deliverables split across ETL builds, automation tasks, and BI dashboarding. BigQuery served as the warehouse foundation, while Airflow and Dataform orchestrated and managed transformations. Cloud Functions and Pub/Sub supported scalable ingestion and real-time automation. JIRA workflows structured sprint deliverables, and Confluence housed documentation for repeatability and collaboration.

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We implemented modular ETL pipelines using Airflow and Dataform to support incremental, test-covered processing.

Execution Approach

Automated, Modular ETL and Dashboarding with Scalable Cloud Tooling

We implemented modular ETL pipelines using Airflow and Dataform to support incremental, test-covered processing.
Real-time pipeline triggering and event handling were achieved using Cloud Functions and Pub/Sub, enabling seamless automation. To deliver actionable insights, we developed interactive Looker dashboards tailored by region, team, and KPI.
Project transparency and alignment improved through structured task tracking in JIRA and standardized documentation in Confluence. Together, these efforts enabled a reliable, scalable data infrastructure supporting both operational efficiency and fast decision-making across stakeholder groups

BUSINESS IMPACT

Operational Efficiency Boost
Better Decision-Making
Project Velocity & Knowledge Sharing
Improved Data Reliability

30%

reduction in manual reporting time

50%

faster reporting via streamlined pipelines

20%

savings in data operations cost