Analyzing usage
Due to the nature of a data platform, it is not practical to build it once and leave it as it is without any updates. This is because data volume, velocity, and variety increase day by day. Also, how the data is consumed and utilized can often vary. It is practical to build a platform based on the minimum requirement, start using it, measure end user activities, and continuously improve it based on end user feedback.
After you release the data platform to end users, you might see issues such as the following:
- Less usage than expected
- Less adoption in specific teams
- Too many escalations from end users
To make the data platform useful for your end users, you need to maintain and keep improving the platform by tracking and analyzing end user activities.
Let’s look at how user activity can be measured for each type of activity. For example, if it is a simple data reference, it can be recorded and measured in the Amazon S3 server access...