Storage and Infrastructure

Ingestion, transformation, and visualization are three separate stages in the data life cycle that move data from one place to another. In this lesson, we will look at the other two stages: storage and infrastructure. They are the key to success in the data life cycle because they run across the entire life cycle and function as a backbone to support business flows.

Storage

In many ways, how data is stored determines how it is used. For example, data in a data warehouse is typically used by batch processes and analytics, while frameworks like Apache Kafka facilitate real-time use cases. They offer not only storage capabilities but also function as an ingestion and query system. Generally speaking, there are four standard storage systems.

Data warehouse