Rely on Automation for Scalability Build an Effective Content Recommender System with Automated Data Cleansing and Scoring Though it’s common for online businesses to give recommendations for other services or products that consumers might be interested in based on their behavior, high-quality recommendations are extremely difficult to provide in practice. They can consume extraordinary amounts of internal resources, as they require heavy data manipulation, coding, and testing of different algorithms. So when a data team is tasked with creating a recommender system based off a variety of signals, the project can get complicated quickly. data iku www.dataiku.com Case Study / MediaAbout Our Customer Our customer is a large national media organization that produces both news and

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