There are various areas where data streams are used: •
Fraud detection & scoring – raw data is used as source data for an anti-fraud algorithm (
data analysis techniques for fraud detection). For example, timestamps, cookie occurrences or analysis of data points are used within the scoring system to detect fraud or to make sure that a message receiver is not a bot (so-called Non-Human Traffic). •
Artificial intelligence – raw data is treated like a train set and a test set during AI and
machine learning algorithms building. •
Raw data is used for profiling and personalization to customize user profiles and divide them for segmentation, e.g., per gender or location (based on
data point). •
Business intelligence – raw data is a source of information for BI systems, used for enriching user profiles with detailed information about them, e.g., purchase path or geodata. This information is used for
business analysis and predictive research. •
Targeting – processed data by data scientists improve online campaigns and is used for reaching the target audience. •
CRM Enrichment – raw data is integrated with
customer-relationship management system. CRM integration allows to fill the gaps in users' profiles with demographic data, interests or buying intentions. ==Integration==