Even big data eventually gets too big and costly to maintain. Remembering the goal of minimizing costs while still maximizing value, make sure to develop a retention strategy for IoT data. Data could be simply deleted after it is retained for a certain amount of time. However, by doing this, you could miss out on building a future profitable analytics service that was not thought of before the data was thrown away.
There are other options that allow you to retain value of the data while minimizing the costs. We will discuss some of these next.
The goals of a retention strategy for IoT analytics are twofold:
- Maintain Value: Advanced modeling techniques, such as deep learning, need lots of history to maximize prediction effectiveness. It is also difficult to know ahead of time which fields will be valuable for a future unknown project. The traditional data retention strategies of storing records for a fixed period of time and then deleting the full dataset could...