Data Warehouse Manager Interview Preparation Guide
Strengthen your Warehouse Manager interview skills with our collection of 113 important questions. Each question is crafted to challenge your understanding and proficiency in Warehouse Manager. Suitable for all skill levels, these questions are essential for effective preparation. Dont miss out on our free PDF download, containing all 113 questions to help you succeed in your Warehouse Manager interview. Its an invaluable tool for reinforcing your knowledge and building confidence.113 Warehouse Manager Questions and Answers:
1 :: What is Datawarehousing?
A Datawarehouse is the repository of a data and it is used for Management decision support system. Datawarehouse consists of wide variety of data that has high level of business conditions at a single point in time.
In single sentence, it is repository of integrated information which can be available for queries and analysis.
In single sentence, it is repository of integrated information which can be available for queries and analysis.
2 :: Explain what are the steps involved in creating dimensional modeling process?
The business process of the dimensional modeling includes:
Choose The Business Process:In this, 4-step design method is followed that helps to provide the usability of the dimensional model. This allows the business process to be more systematic in representation and more helpful in explaining it as well. It includes the use of Business Process Modelling Notation (BPMN) or Unified Modelling Language (UML).
Declaring The Grain:After choosing the business process, the declaration of the model comes that consists of grains. The grain of the model provides the accurate description of the dimensional model and allows the focus should be shifted there.
Identify The Dimensions:In this phase, the identification of the dimension takes place in the dimensional model. The dimensions are defined in the grain that is defined in the declaration part above. Dimensions acts as a foundation of the fact table where the data gets collected that comes under the fact.
Identify The Facts:Defining the dimensions provides a way to create a table in which the fact data can be stored. These facts are populated on the basis of the numerical figures and facts.
Choose The Business Process:In this, 4-step design method is followed that helps to provide the usability of the dimensional model. This allows the business process to be more systematic in representation and more helpful in explaining it as well. It includes the use of Business Process Modelling Notation (BPMN) or Unified Modelling Language (UML).
Declaring The Grain:After choosing the business process, the declaration of the model comes that consists of grains. The grain of the model provides the accurate description of the dimensional model and allows the focus should be shifted there.
Identify The Dimensions:In this phase, the identification of the dimension takes place in the dimensional model. The dimensions are defined in the grain that is defined in the declaration part above. Dimensions acts as a foundation of the fact table where the data gets collected that comes under the fact.
Identify The Facts:Defining the dimensions provides a way to create a table in which the fact data can be stored. These facts are populated on the basis of the numerical figures and facts.
3 :: Explain the functions of a warehouse manager?
The warehouse manager performs consistency and referential integrity checks, creates the indexes, business views, partition views against the base data, transforms and merge the source data into the temporary store into the published data warehouse, backs up the data in the data warehouse, and archives the data that has reached the end of its captured life.
4 :: Explain the functions of data warehouse tools and utilities?
The functions performed by Data warehouse tool and utilities are
☛ Data Extraction,
☛ Data Cleaning,
☛ Data Transformation,
☛ Data Loading and Refreshing.
☛ Data Extraction,
☛ Data Cleaning,
☛ Data Transformation,
☛ Data Loading and Refreshing.
5 :: Tell me what do OLAP and OLTP stand for?
OLAP is an acronym for Online Analytical Processing and OLTP is an acronym of Online Transactional Processing.
6 :: What is non-additive Measures?
Non-additive measures are those which can not be used inside any numeric aggregation function (e.g. SUM(), AVG() etc.). One example of non-additive fact is any kind of ratio or percentage. Example, 5% profit margin, revenue to asset ratio etc. A non-numerical data can also be a non-additive measure when that data is stored in fact tables, e.g. some kind of varchar flags in the fact table.
7 :: What is the difference between OLTP and OLAP?
OLTP is the transaction system that collects business data. Whereas OLAP is the reporting and analysis system on that data.
OLTP systems are optimized for INSERT, UPDATE operations and therefore highly normalized. On the other hand, OLAP systems are deliberately denormalized for fast data retrieval through SELECT operations.
In a departmental shop, when we pay the prices at the check-out counter, the sales person at the counter keys-in all the data into a "Point-Of-Sales" machine. That data is transaction data and the related system is a OLTP system.
On the other hand, the manager of the store might want to view a report on out-of-stock materials, so that he can place purchase order for them. Such report will come out from OLAP system.
OLTP systems are optimized for INSERT, UPDATE operations and therefore highly normalized. On the other hand, OLAP systems are deliberately denormalized for fast data retrieval through SELECT operations.
In a departmental shop, when we pay the prices at the check-out counter, the sales person at the counter keys-in all the data into a "Point-Of-Sales" machine. That data is transaction data and the related system is a OLTP system.
On the other hand, the manager of the store might want to view a report on out-of-stock materials, so that he can place purchase order for them. Such report will come out from OLAP system.
8 :: Tell me what is Execution Plan?
Execution Plan is a plan which is used to the optimizer to select the combination of the steps.
9 :: Tell me what is the difference between ER Modeling and Dimensional Modeling?
ER modeling will have logical and physical model but Dimensional modeling will have only Physical model.
ER Modeling is used for normalizing the OLTP database design whereas Dimensional Modeling is used for de-normalizing the ROLAP and MOLAP design.
ER Modeling is used for normalizing the OLTP database design whereas Dimensional Modeling is used for de-normalizing the ROLAP and MOLAP design.
10 :: Explain me what is Metadata?
Metadata is defined as data about the data. The metadata contains information like number of columns used, fix width and limited width, ordering of fields and data types of the fields.