Top Data Warehouse Interview Questions
The data warehouse is the most secure storage system of any information for the business or the organization. This data warehouse works as the library of the historical data that can be analyzed or retrieved as per the requirements of the business to perform decision making. In this Data Warehouse Interview Questions article, we have consolidated the list of all the common questions that most companies usually ask during their session of interviews. We highly recommend you go through every question twice before going to the Data warehouse job interview. You don’t need to go anywhere for finding the answers, we have listed them as well for your convenience.
Most Frequently Asked Data Warehouse Interview Questions
A data warehouse is designed to separate the analysis of bigger data and processes the query from the transactional processes that are focused on writing.
We opt data warehouse instead of a database because of the benefits listed below:
- It enables historical insight.
- Enhances the quality of Data
- Boost the efficiency
- Drives the revenue
- It increases the speed of data analytics
- It provides data security
- It has very much higher query performance and insights
Relational database (RDBMS). This database allows you to store detailed, consolidated, and company-wide data. It is based out on the design of “Star schema” and it is established by the various data marts that are integrated through dimensions and confirmed facts.
However, the best database software for the data warehouses will depend on your requirements.
It demonstrates one of the most common ways of planning the blueprints of the definite and summed up information of the data warehouse. The objective of data warehouse modeling is to foster a diagram portraying the reality, or if nothing else a piece of the reality, which the data warehouse is expected to help.
|Enterprise Data Warehouse||Operational Data Store||Data Mart|
|It gives the controlled database for decision support throughout the enterprise.||Under its scope, it has a broad enterprise which is unlikely a real enterprise Data warehouse. In this, data gets refreshed in rare real-time and it is being used for daily business activity.||It is a sub-part of the data warehouse. It is designed for particular lines of business, hence support for a particular reason.|
|Data Warehousing||Data Mining|
|It is defined as a huge database that is designed to carry out analytical processes.||It is defined as the process that determines the hidden relationships in patterns among different sets of data.|
|It is used to combine huge sets of data.||It determines the useful meaning and insights from large sets of data.|
|It can easily store large quantities of data of any organization.||It is used to identify the patterns, frauds, and relationships in an organization.|
|Data warehousing can be performed by engineers.||Data mining is performed by businessmen with the help of engineers.|
|OLTP stands for Online Transaction Processing.||OLAP stands for Online Analytical Processing.|
|It has fundamental business tasks||It has Multi-dimensional business tasks|
|It is used to normalize small database||It is used to denormalize large database|
|It supports simple queries by users||It supports complex queries by the system.|
To build the data warehouse, one needs to follow the below steps:
- Gather all the business requirements.
- Necessary sources should be identified.
- Identify the facts.
- Dimensions should be defined.
- Attributes should be defined.
- Redefine the attributes and dimensions, if they are required.
- Organize the hierarchy of Attribute
- Define relationships.
- Assign unique identifiers.
|Basis||Structured Data||Unstructured Data|
|Searching||Easy using SQL-based approaches||May require the use of special tools|
|Storage||It requires more storage to accommodate defined data structures.||In this, some forms require less storage; others have large file formats, requiring more storage.|
|Format||It has a predefined format that uses alphanumeric characters.||It has typically non-character-oriented digital representations.|
In Data warehouses, there are three types of dimensional modeling:
- Conceptual Modeling
- Physical Modeling
- Logical Modeling
In the data warehouse, bus architecture is made up of the set of tightly combined data marts that gets their potential from fact tables and conformed dimensions.
1. Conformed dimensions
it is defined and implemented only once so that it is meant to be the same thing wherever it is being used.
2. Fact Tables:
which are conformed includes the things that derive revenue, profit, standard costs, and standard price.
In the data warehouse, a snowflake schema is the variation of the star schema. It is the form of dimensional modeling where dimensions are being stored in multiple related dimension tables. It is majorly used to improve the performance of certain queries.
A real-time data warehouse collects, cleanses, stores transforms, and circulates the information in real-time. Benefits of a real-time data warehouse:
- Faster Decisions
- Faster Recovery
- No Batch Windows
- Ideal Data Load
|ER Modelling||Dimensional Modelling|
|It supports OLTP||It supports OLAP|
|ER Modelling is always normalized||Dimensional Modelling is always denormalized|
|It removes the redundancy.||It permits redundancy.|
|This model for organization or enterprise is very hard for people to visualize and keep in their heads||This model is very easy to understand.|
This is it! We came to the end of this blog on the Data Warehouse Interview Questions. We hope you found this one helpful and are now feeling more confident about your upcoming interviews. If you think we are missing out on something, do not hesitate to tell us. Do share your feedback in the comments section.
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