“Data Warehouse Manager Frequently Asked Questions in various Warehouse Manager job interviews by interviewer. The set of questions are here to ensures that you offer a perfect answer posed to you. So get preparation for your new job interview”
A data warehouse contains historical information that is made available for analysis of the business whereas an operational database contains current information that is required to run the business.
Normalization splits up the data into additional tables.
The fact table allows the data to be represented in the detailed manner. It has an association with the dimensional table.
The steps that are required to design the fact table includes:
Identify the business process for analysis so that all the process can be defined and used with the complete details provided by the business process.
Identify the measures, constraints, facts and keys before designing the fact table. The questions have to be asked during the business process regarding the table that has to be created and the purpose of it.
Identify the dimensions for facts like product dimensions, location, time, etc. This phase also include the analysis of the components that are required to be involved.
List of the columns takes place that describe the dimension and the lowest level of detail is to be found out to be used in the fact table.
Business intelligence is required everywhere and it is most importantly required in data warehousing due to the technologies that are getting used in it. It allows the applications and the practices to be performed according to the business rules and regulations. Business intelligence consists of collection, integration, analysis and the presentation of the information that is used to make business related decisions. This is also used to build business related system like decision support system that provide historical, current and predictive data that can be used in the favor of setting up the environment of the database system. It uses computer based techniques to extract the information from many resources and analyze it according to the industry. It is used to provide nearly accurate decision making system.
Warehouse manager is responsible for the warehouse management process. The warehouse manager consist of third party system software, C programs and shell scripts. The size and complexity of warehouse manager varies between specific solutions.
A dimension is something that qualifies a quantity (measure).
For an example, consider this: If I just say… “20kg”, it does not mean anything. But if I say, "20kg of Rice (Product) is sold to Ramesh (customer) on 5th April (date)", then that gives a meaningful sense. These product, customer and dates are some dimension that qualified the measure - 20kg.
Dimensions are mutually independent. Technically speaking, a dimension is a data element that categorizes each item in a data set into non-overlapping regions.
Data cube helps us to represent the data in multiple dimensions. The data cube is defined by dimensions and facts.
Cubes are logical representation of multidimensional data. The edge of the cube has the dimension members,and the body of the cube contains the data values.
Dimensional normalization allows the database related problems to be solved. It is used to remove the redundant attributes that are used as de-normalized dimensions. Dimensions consist of sub-dimensions that are joined together in one. The dimensional normalization is not used due to the fact that it makes:
☛ Data structure more complex and due to which the performance can be degraded as it requires lots of joining of tables and keep the relations intact.
☛ The space is not utilized properly and use of more space is required.
☛ The query performance suffers when aggregating or retrieving many dimensional values. This requires proper analysis and making of operational reports are necessary.
Subject oriented signifies that the data warehouse stores the information around a particular subject such as product, customer, sales, etc.
A data warehouse helps to integrate data and store them historically so that we can analyze different aspects of business including, performance analysis, trend, prediction etc. over a given time frame and use the result of our analysis to improve the efficiency of business processes.
In datawarehousing, loops are existing between the tables. If there is a loop between the tables, then the query generation will take more time and it creates ambiguity. It is advised to avoid loop between the tables.
Following need to be done to start the database:
☛ Start an Instance
☛ Mount the database
☛ Open the database
Following are the differences between OLTP and OLAP:
OLTP:
Data is from original data source
Simple queries by users
Normalized small database
Fundamental business tasks
OLAP:
Data is from various data sources
Complex queries by system
De-normalized Large Database
Multi-dimensional business tasks
Time dimensions are usually loaded through all possible dates in a year and it can be done through a program. Here, 100 years can be represented with one row per day.
ER diagram is abbreviated as Entity-Relationship diagram which illustrates the interrelationships between the entities in the database. This diagram shows the structure of each tables and the links between the tables.
A load manager performs the operations required to extract and load the process. The size and complexity of load manager varies between specific solutions from data warehouse to data warehouse.
Following are the ETL tools available:
☛ Informatica
☛ Data Stage
☛ Oracle
☛ Warehouse Builder
☛ Ab Initio
☛ Data Junction
Core dimension is nothing but a Dimension table which is used as dedicated for single fact table or datamart.
ODS is abbreviated as Operational Data Store and it is a repository of real time operational data rather than long term trend data.
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