Category: Kinesis Data Analytics

Financial trading houses and stock exchanges generate enormous volumes of data in near real-time, making it difficult to perform bi-temporal calculations that yield accurate results. Achieving this requires a processing architecture that can handle large volumes of data during peak bursts, meet strict latency requirements, and scale according to incoming volumes. In this post, we’ll […]

As businesses race to digitally transform, the challenge is to cope with the amount of data, and the value of that data diminishes over time. The challenge is to analyze, learn, and infer from real-time data to predict future states, as well as to detect anomalies and get accurate results. In this blog post, we’ll […]