The document discusses two projects using InfluxDB: 1) Transforming email reports by consuming messages from Kafka, aggregating and storing in InfluxDB, and generating dashboards. They solved a high volume mismatch issue by adding unique tags and building a point cache. 2) Anomaly detection by collecting data from various sources, storing counts in InfluxDB, and finding anomalies like sudden drops, volume decay, and deadman events. Anomalies and alerts are stored in InfluxDB and handled via Slack, email, and SMS. Visualizations are created in Grafana by obtaining data from InfluxDB.