A Data warehouse (DW) is a not part of DBMS, it stores large amount of data which is typically collected from multiple heterogeneous source like files, DBMS, etc. It is a vital component of business intelligence that employs analytical techniques on business data. Most organizations depend on this data for analytics or reporting purposes, the data needs to be consistently formatted and easily accessible – two qualities that define data warehousing and makes it essential to today’s businesses. Data warehouses are used for online analytical processing (OLAP), which uses complex queries to analyze rather than process transactions.
What are the Traditional Data Warehouse Concepts?
What are the stages of Data warehousing?
Can you explain Data warehouse use cases?
Can you define Business Intelligence?
Can you define Dimension Table?
Can you explain Active Data warehousing?
What is the difference between Data warehouse and OLAP?
What are the key columns in Fact and dimension tables?
What are the different types of SCD?
Can you explain Snowflake Schema?
Can you define core dimension?
Can you explain real-time data warehousing?
Can you explain Aggregate tables?
Can you define fact less fact tables?
How can we load the time dimension?
How is a data warehouse different from a regular database?
What are the Cloud Data Warehouse Concepts (Amazon red shift)?
Can you explain Non-additive facts?
Can you explain conformed fact?
What are the cons of a data warehouse?
Can you explain Cloud Data Warehouses?