Running analytics at scale with Amazon Redshift Serverless

Data warehouses play a crucial role in data management, data analysis, and data engineering. Data engineers and ML engineers spend time building data warehouses to work on projects involving batch reporting and business intelligence.

Figure 4.11 – Data warehouse

As shown in the preceding diagram, a data warehouse contains combined data from different relational data sources such as PostgreSQL and MySQL databases. It generally serves as the single source of truth when querying data for reporting and business intelligence requirements. In ML experiments, a data warehouse can serve as the source of clean data where we can extract the dataset used to build and train ML models.

Note

When generating reports, businesses and start-ups may end up performing queries directly on the production databases used by running web applications. It is important to note that these queries may cause unplanned...