User-Facing Real-Time Analytics Using Apache Kafka and Azure Data Explorer

Companies today are generating and collecting massive amounts of data, and they use data analytics to make critical business decisions. However, the analytics should not be limited to teams within the organization. It should also be exposed to the end-users in order to democratize decision making: User-Facing analytics. An example of User-Facing analytics is LinkedIn's "Who viewed your profile". As analytics are no longer limited to users within the organization, User-Facing analytics requires a solution that will scale to millions of users to provide fast, real-time insights. This is where Apache Kafka and Azure Data Explorer comes in. Apache Kafka is the de facto standard for real-time event streaming. Azure Data Explorer is a fast, fully managed data analytics service for real-time analysis on large volumes of data. The data is streaming from applications, websites, IoT devices and more. This "demo-heavy" session shows how we stream event data from Apache Kafka (running on Confluent Cloud in Azure) into Azure Data Explorer. Some of the topics we cover: * Overview of Apache Kafka and Confluent Cloud. * Introduction to Azure Data Explorer. * Ingestion of data from Kafka into ADX. * Analyse ingested data in ADX.