In my last post, I described the basics for processing Adobe Analytics Click Stream Data Feeds using Hadoop. While the solutions outlined there will scale remarkably well, there is a more memory efficient way to do it. Having this flexibility is nice if you have lots of CPU cores available but not as much ram. […]
Month: June 2017
Introduction to Processing Click Stream Data Feeds with Hadoop and Map/Reduce
In an earlier post, Matt Moss showed how to process data feed data using an SQL database. This can be useful in a pinch when you have a smaller amount of data and need an answer quickly. What happens though when you now need to process the data at a large scale? For example, you […]
Marketing Mix Model for All: Using R for MMM
Understanding the ROI across all of your paid marketing channels is a top priority for senior-level executives across every industry and every geographical market. Getting a clear sense of the ROI on each channel allows companies to answer really important questions. For example: What will happen if I increase my Email spend by 20%? What […]