Data Warehousing Interview Questions

Introduction to Data Warehousing Interview Questions and Answers

Data-warehouse is a central repository that stores heterogeneous data from various sources. The data in a warehouse can be used for analytical reporting, structured or ad hoc queries and used in decision making. The process of collecting data from multiple sources and storing it in the central repository is called Data Warehousing.

The data may be of several types like structured, semi-structured or unstructured data. The data from various sources is processed, transformed and ingested to one single database that is called a data warehouse. Users can access this processed data in the data warehouse through various tools like Business Intelligence tools, SQL clients, spreadsheets and many other tools. This data helps to perform data mining operations that help to find some pattern in the data.

Now, if you are looking for a job that is related to Data Warehousing then you need to prepare for the 2021 Data Warehousing Interview Questions. It is true that every interview is different as per the different job profiles. Here, we have prepared the important Data Warehousing Interview Questions and Answers which will help you get success in your interview.

Now Let us understand some of the important 2021 Datawarehousing Interview Questions that can be asked in an interview. But this doesn’t mean that these are the only questions that will be asked in an interview, you need to be prepared thoroughly regarding each topic that we are discussing here. These questions are divided into two parts are as follows:

Part 1 – Data Warehousing interview Questions (Basic)

This first part covers basic Data Warehousing Interview Questions and Answers

Q1. What is Data Warehousing?

Answer:
Data Warehousing is a process of collecting data from various sources processing it and storing it a huge database, thus the processed data could be used for various purposes like analytical reporting, business intelligence or data mining etc. The basic idea behind the data warehouse is nothing but storing huge amount of data.

Q2. Difference between Database and Data Warehouse?

Answer:
Please find below the different tables that are supported by Data Warehousing are:

Q3. What are the stages of Data Warehousing?

Answer:
General stages of the data warehouse are:

• Offline Operational Database: Data is copied from the operating system to another server to perform various operations.
• Offline Data Warehouse: Data in the Data Warehouse is regularly updated from the operational database.
• Real Time Data Warehouse: Data Warehouse is updated when any transaction takes place in the operational system.
• Integrated Data Warehouse: Data Warehouse is updated continuously when any transaction is performed on the operational system.

Q4. What is Business Intelligence (BI)?

Answer:
This is the basic Data Warehousing Interview Questions asked in an interview. BI is a technology-driven process for analyzing data and presenting meaningful insights to the end users that helps in better decision making. BI encompasses various tools which help in understanding the data trends and patterns hidden in the data. Some of the tools that are widely being used are SAP Business Intelligence, MicroStrategy, Science, Tableau, and many more.

Q5. What are the components of Data Warehouse?

Answer:
Four components of the Data Warehouse are:

• Load Manager: It performs all the operations associated with the extraction and load of data into the warehouse.
• Warehouse Manager: It performs operations associated with the data in the warehouse. It performs operations like analysis of data to ensure consistency, the creation of indexes and views and many other operations.
• Query Manager: It performs all the operations related to user queries. The operations of this component are direct queries to the appropriate tables.
• End-user access tool: Tools used by end users to access the data. It is categorized into different groups like

1. Data Reporting tools
2. Query tools
3. Application Development tools
4. EIS tools
5. OLAP and Data mining tools

Part 2 – Data Warehousing interview Questions (Advanced)

Let us now have a look at the advanced Data Warehousing Interview Questions.

Q6. What is the Dimension table?

Answer:
Dimension table in a data warehouse is a table in a star schema. Dimension tables are used to store dimension or attributes that describe the data in the Fact table. For example, Product dimension might contain the name, description, unit price, weight, color, and many other attributes. The system generated the key is used uniquely identify the row in the dimension table. This key acts a primary key in the dimension table and used as foreign key in fact table which helps join between the two tables.

Q7. What is Fact table?

Answer:
A fact table is the center table of the star schema, surrounded by a dimension table of a data warehouse. Fact table consists of the quantitative metrics or facts of the business process. Fact table works with a dimension table and it stores the data that is to be analyzed. The fact table contains a foreign key column which acts as a primary key in the dimension table this key allows join between these two tables.

Let us move to the next Data Warehousing Interview Questions

Q8. What is Data Mart?

Answer:
Data Mart is a subset of the data warehouse that usually contains a specific set of data related to a specific business line. Data Mart is small and used in querying or analyzing a specific set of data, for example, data related to “Sales”, “Customers”, “Order” etc.

Q9. What is the Operational Data Store (ODS)?

Answer:
This is the most asked Data Warehousing Interview Questions in an interview. An ODS is the type of database which stores data that is used by operational systems before storing into a data warehouse. It serves as the intermediate database. An ODS contains short-term data whereas a data warehouse contains historical data.

Q10. Explain Data Warehouse architecture.

Answer:
It includes the following stages:

• Data Source layer: In this stage, data is collected from various sources and stored in a relational database. Data includes social media data, operational data, transactional data and many more.
• Data Staging layer: In this stage data from the data source layer is extracted and processed because data will be from various sources and with different formats. The extracted data will be subjected to quality checks and end results will be clean and organized data that will be loaded into the data warehouse.
• Data Storage layer: This layer is where the data from the staging area will be stored as a single central repository. Depending upon the business requirements storage could be a data warehouse, data mart or an Operational Data Store.
• Data Presentation layer: This layer is used by users to access the data. Users can perform various queries or run some analysis to perform reports.

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