4 Common Use Cases
In this article we explore four use cases that exemplify why real-time analytics are critical to performance and user experience, highlighting key capabilities that enable real- time analytics in each layer of your system or application:
- The Application Layer
- The Database Layer
- The Server/Hosting Layer
- Cross System, Real-time Analytics
What is Real-time Analytics?
When referring to “analytics,” people often think of manipulating an existing set of structured data to yield insights.
“Real-time analytics” takes this definition a step further by accounting for the constant appending of new data to the existing data set and continuously re-analyzing the new dataset for new insights. But, for analytics to be real-time, data needs to be ingested immediately upon creation, delivering results in a matter of seconds, enabling those interpreting the data to react right away.
Complete the form above to gain instant access to "Using Log Data Streams for Real-time Analytics: 4 Common Use Cases".