Invalid Ad Traffic Prediction


Year2015 – 2018

RoleMachine Learning, Predictive Analytics

TechnologyApache Spark, Scala, HDFS, Apache Zeppelin

Building a better anti-fraud mousetrap.
Driving ROI for advertisers and publishers.

An AdTech player specializing in Programmatic Advertising Platform wanted to pull up it’s ranking in invalid traffic detection during industry surveys. Their requirement was to detect and block sophisticated invalid traffic arriving at the ad-exchange.


The chain is only as strong as its weakest link.
Advanced analytics help you spot anomalies.


We started off by building a data scraper that collates data from various sources for analysis. We also created a Machine Learning algorithm that predicts invalid ad requests. Moreover, storage optimization techniques on raw HDFS were kicked in to optimize filtered aggregation Spark SQL execution time to <10 seconds for over 9 million records.


Be on top of your game in weeding out IVT.
Protecting your advertisers from frauds.

The client was able to improve their Pixalate rank and optimize bid decisions on ad-exchange. The optimized data ingestion pipeline could crunch a TB of data under 50 minutes.

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