In Ad Tech (as it is happening in other industries), we are dealing with three major technical challenges:
1) How to deal with huge amounts of data.
2) How to deal with different sources, and multiple data models, in real-time.
3) How to normalize, aggregate, analyze and make predictions out of the data.
It is not an implementation problem: there are plenty of technologies to choose from (Elastisearch for storing/analyzing data, AWS Kinesis to process data in real-time, Python scikit-learn to run machine learning models.)
It is a design problem: how to architect all the available tools in a way that makes sense for your platform; how to come up with predictions that are worth predicting.
We have the libraries, services, and capacity to analyze huge amounts of data, in real-time, from multiple sources, and make predictions out of it.
Now we need to find talented architects and product managers to orchestrate those technologies in a way that produces business results.
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