For those who want to learn the basic concepts of data warehouse and warehousing, what better way than to read about common data warehouse interview questions and their answers? These data warehouse interview questions will attempt to explain standard data warehousing terms and important considerations. Below are 7 data warehouse interview questions you can study.
1. What is a data warehouse?
Among all data warehouse interview questions, this is of course the most basic, yet most important. A data warehouse is an electronic data storage used for supporting intelligent business decisions though the collection, consolidation, and organization of data for future evaluation and reporting.
2. Why is it important to use data warehouses?
The use of data warehouses is important since it greatly aids in the accurate reporting of various chief business processes. They considerably help in integrating and historically storing data from a host of various sources to present a point of truth value regarding business decisions in a given period to enhance an organization’s processes. They are likewise commonly utilized for data mining to aid in predicting forecasts and trends, performance evaluations, as well recognition of patterns among others.
3. What is the standard procedure for creating a data warehouse?
This is also one of the most crucial data warehouse interview questions when learning about data warehouses. The standard procedure used to make a data warehouse is very similar to majority of database projects. Below are the common steps:
- identification and collection of requirements
- conducting dimensional modeling
- development of the data warehouse architecture which include the ODS or Operational Data Store
- designing OLAP cubes and the relational database
- development of applications to be used for maintaining stored data
- development of applications to be utilized for analysis
- testing and deploying the completed data warehouse system
4. What is a data mart?
In general, a data mart is developed for one main subject matter. A business usually have data regarding different business matters such as for sales, marketing, human resources, or finance contained in one data warehouse but stored in separate data marts.
5. Is there a difference between OLAP and OLTP?
OLAP or online analytical processing is the system used for analyzing and reporting data, while OTLP or online transaction processing is the system utilized for the collection of data to be stored in the data warehouse. While OLAP are intentionally de-normalized to implement faster retrieval of data via SELECT functions, OLTP are intentionally normalized for UPDATE and INSERT functions.
6. What is a dimensional model?
A dimensional model is made up of fact and dimension tables. The fact tables are for storing foreign keys and various transactional measurements from dimensional tables in order to qualify data. Its main purpose is to implement easier and faster retrieval of data. It should be designed according to user requirements to fully support direct and easy access, effortless maintenance, and so that it will be capable of adapting to modifications later on.
Likewise, the design model should be a functioning relational database capable of supporting OLAP cubes for providing analysts with immediate results for their queries.
7. What is the Entity Relationship model?
The entity relationship or ER model is a specific data modeling method where the main purpose is data normalization via the redundancy reduction. A dimensional model differs from the ER model since in a dimensional model; the purpose is the de-normalization of data retrieval processes for faster operations.