Enterprise Data Warehouse Interview Preparation Guide
Refine your Enterprise Data Warehouse interview skills with our 13 critical questions. Our questions cover a wide range of topics in Enterprise Data Warehouse to ensure youre well-prepared. Whether youre new to the field or have years of experience, these questions are designed to help you succeed. Download the free PDF to have all 13 questions at your fingertips. This resource is designed to boost your confidence and ensure youre interview-ready.13 Enterprise Data Warehouse Questions and Answers:
1 :: Explain What is the data type of the surrogate key?
When you add a relational or a flat file source definition to a mapping, you need to connect it to a Source Qualifier transformation. The Source Qualifier represents the rows that the Informatica Server reads when it executes a session.
2 :: What a static and local variable?
Data type of the surrogate key is integer, numeric, or number.
3 :: What is data type of the surrogate key?
There is no data type for a Surrogate Key. Requirement of a surrogate Key: UNIQUE Recommended data type of a Surrogate key is NUMERIC.
4 :: Explain difference between view and materialized view?
View - store the SQL statement in the database and let you use it as a table. Every time you access the view, the SQL statement executes. Materialized view - stores the results of the SQL in table form in the database. SQL statement only executes once and after that every time you run the query, the stored result set is used. Pros include quick query results.
view : - View occupties memory to store query but not data.
Materilized view:- The view query results is stored in database knows as Materilized view.
view : - View occupties memory to store query but not data.
Materilized view:- The view query results is stored in database knows as Materilized view.
5 :: Explain the main difference between Inmon and Kimball philosophies of data warehousing?
Both differed in the concept of building the data warehouse.According to Kimball, Kimball views data warehousing as a constituency of data marts. Data marts are focused on delivering business objectives for departments in the organization. And the data warehouse is a conformed dimension of the data marts. Hence, a unified view of the enterprise can be obtained from the dimension modeling on a local departmental level.Inmon beliefs in creating a data warehouse on a subject-by-subject area basis. Hence, the development of the data warehouse can start with data from the online store. Other subject areas can be added to the data warehouse as their needs arise. Point-of-sale (POS) data can be added later if management decides it is necessary.
6 :: Why fact table is in a normal form?
The fact table consists of the Index keys of the dimension/look up tables and the measures. So whenever we have the keys in a table. That it implies that the table is in the normal form.
7 :: Explain What are Fact, Dimension, and Measure?
Fact is key performance indicator to analyze the business. Dimension is used to analyze the fact. Without dimension there is no meaning for fact.
8 :: Explain What is a cube in data warehousing concept?
Cubes are logical representation of multidimensional data. The edge of the cube contains dimension members and the body of the cube contains data values.
9 :: Explain the different types of data warehousing?
Types of data warehousing are:
1. Enterprise Data warehousing
2. ODS (Operational Data Store)
3. Data Mart
1. Enterprise Data warehousing
2. ODS (Operational Data Store)
3. Data Mart
10 :: What are the main steps to build the data warehouse?
Gathering business requirements>>Identifying Sources>>Identifying Facts>>Defining Dimensions>>Define Attributes>>Redefine Dimensions / Attributes>>Organize Attribute Hierarchy>>Define Relationship>>Assign Unique Identifiers