Development of a Real-Time AdOps Reporting Dashboard for Programmatic Advertising

The client faces difficulties in aggregating logs from multiple data sources, processing large and varied log files in different formats, and delivering timely performance metrics to users. The existing reporting solution lacks the ability to handle real-time data processing and low latency requirements, hampering client insights and campaign management efficiency.

A mid-to-large sized digital advertising technology firm that manages and optimizes programmatic ad campaigns across multiple platforms and publishers.

• Create a central data aggregation layer that consolidates logs from disparate sources with high efficiency.
• Implement robust data processing pipelines capable of handling large, heterogeneous log files to compute accurate performance metrics.
• Design an interactive user interface to visualize real-time and historical campaign metrics with minimal delay (~10 minutes latency).
• Ensure the infrastructure is modular, easily maintainable, and capable of seamless updates, including containerized deployment options.
• Support live metric updates from external data sources to facilitate real-time decision-making.

• Data ingestion component that collects logs from various data harvesters, stored in cloud storage solutions like object storage buckets.
• Data processing engine capable of normalizing, filtering, and aggregating large volumes of log data in different formats, utilizing tools like Apache Spark.
• Data storage component for maintaining aggregated metrics, optimized for read-heavy operations, such as a relational database like PostgreSQL.
• A dynamic UI that displays key performance metrics with filtering options by demand partners, devices, time intervals, and other relevant parameters.
• Automated scheduling and streaming capabilities to enable near real-time data refresh (within approximately 10 minutes).
• An infrastructure deployment setup that supports containerization for ease of updates and scalability.

• Data harvesters or log collection systems that populate data into cloud storage (e.g., Amazon S3).
• External real-time data streams or APIs providing live performance metrics.
• Database systems for storing aggregated metrics for efficient retrieval and visualization.

• Processing large logs with varied formats within a maximum of 10 minutes latency.
• System scalability to handle increasing volume of logs and user requests without performance degradation.
• High availability and fault tolerance by leveraging cloud-native services.
• Secure data access and compliance with privacy standards relevant to ad operations.

The new reporting dashboard will empower clients with near real-time visibility into campaign performance, enabling faster decision-making and optimized ad inventory management. It aims to improve insight accuracy and timeliness, leading to increased client satisfaction and operational efficiency, similar to achieving low-latency processing within 10 minutes for large-scale data sets.