Introduction to Data Warehousing is the first topic of the
second module of the course. It includes the following subtopics:
- What
is Data Warehousing: This section defines what a data warehouse is and its
role in the larger field of data engineering. It explains that a data
warehouse is a centralized, integrated, and consolidated repository of
data that is designed to support decision-making and reporting.
- Data
Warehousing vs. Databases and Data Lakes: This section explains the
differences between a data warehouse and other data storage systems such
as databases and data lakes. It explains that a data warehouse is
optimized for reporting and analytics, while a database is optimized for
transactional processing and a data lake is optimized for storing raw data
in its native format.
- Use
cases for Data Warehousing: This section covers the different use cases
for data warehousing such as business intelligence, data mining, and
reporting. It explains that a data warehouse is used to support
decision-making and reporting by providing a single source of truth for an
organization's data.
- Importance
of Data Warehousing: This section covers the importance of data warehousing
in today's data-driven world. It explains that data warehousing allows
organizations to collect, store, and analyze large amounts of data, which
is essential for making data-driven decisions and remaining competitive.
- Summary:
This section provides a summary of the key concepts covered in the topic
and what students should have learned.
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