Problem Statement

Regional campaign planning relied on siloed, often inconsistent data arriving from APIs, Excel files, and SQL servers. Manual formatting and ad-hoc logic implementations slowed decision-making and introduced frequent errors. Additionally, the lack of automation made it difficult to scale operations, especially with daily update requirements from business teams.

Key Challenges

• Fragmented Data Sources

  Campaign data came in from APIs, Excel sheets, and SQL Server databases, making ingestion complex and time-consuming.

• Manual Processing Bottlenecks

  Data formatting and processing lacked automation, delaying insights and increasing dependency on engineering teams.

• Need for Daily Refreshes

  Campaign data had to be updated daily to reflect dynamic regional plans and KPIs, requiring high operational reliability.

• Inefficient Code Deployment

  Managing and deploying changes to processing logic and business rules was slow and error-prone due to limited version control.

Solution Implemented

• Built ETL Pipelines in Azure Data Factory: Created scalable pipelines to automate ingestion of campaign data from multiple structured and unstructured sources.

• Architected Centralized SQL Data Layer : Structured incoming data in SQL Server to standardize reporting and simplify access for downstream business users.

• Developed Processing Logic in Azure Databricks : Created notebooks to process and transform campaign data into actionable formats for regional business teams.

• Enabled Agile Change Management : Streamlined updates to processing logic through modular stored procedures and Databricks notebooks.

• Integrated CI/CD via Azure DevOps : Used Azure DevOps pipelines to version, test, and deploy code changes rapidly and reliably across environments.

Business Impact

• End-to-End Automation of Campaign Data Flows

  Reduced manual effort and operational risk by automating ingestion, transformation, and formatting processes.

• Faster Insight Delivery to Business Teams

  Enabled daily refreshes of campaign data, helping regional teams make timely, data-informed planning decisions.

• Improved Data Quality and Governance

  Established reliable, traceable, and governed pipelines that deliver consistent data to reporting and analytics layers.

• Greater Agility in Adapting to Business Changes

  Accelerated response time to evolving campaign needs through modular code and automated deployment.