The answer to that question is a little less than straightforward. From a physical
standpoint, there are indeed two data warehouses—a standard data warehouse and a bulk
data warehouse. But from a logical standpoint, there is only one data warehouse. The
physical possibilities for a data warehouse are the following:

A standard data warehouse

A bulk data warehouse

A standard data warehouse and a bulk data warehouse

The confusion arises when a data warehouse is built inside a data lake, as is certainly a
possibility. The data lake resides on physically different technology (i.e., big data) than
the standard data warehouse (which typically resides on relational technology).

However, even though there are physically two different data warehouses, there should
never be any overlap of data from the standard data warehouse to the bulk data
warehouse. Therefore, there is logically one data warehouse that is physically
implemented over two environments.

There are several advantages to this “duplexed” approach. One advantage is that the data
warehouse can grow to any size. Another advantage is that the data warehouse
infrastructure cost is minimized. Both of these advantages are quite attractive to most
organizations.

Where Different Types of Questions Are Answered

Across the End State Architecture

Yet, another way to understand the end-state architecture is to look at the different types
of questions that are answered in different places in the end-state architecture.

Fig. 2.1.5 shows the possibilities.

Chapter 2.1: The End-State Architecture—The “World Map”