In: Computer Science
4. How does a RDBMS support a Business Intelligence (BI) app?
5. What is a difference between a data warehouse vs. data mart?
6. Who are some primary users for a data warehouse environment?
Decision support system (DSS) :- It is a information system which supports business or organizational decision-making activities.
DSS provide management, operations and planning level of organization.
A properly designed DSS is an interactive software-based system use to help decision makers compile useful information from a combination of raw data.
Historical data analysis, used in every facet of business and life, is well-developed and mature. Although such information is not always directly actionable, it's an important part of DSS because it reports past performance and highlights areas that need attention.
Some example :
Business intelligence (BI): It's largely based on historical data, BI solutions allow users to develop and run queries which are used to guide and support decision-making.
ERP dashboards: User-configurable
dashboards which allow managers to monitor a variety of performance
indicators.
Source Data Available in DSS
There are three key elements of DSS include
Organizational data : Relevant information and knowledge
A model: Mathematical and statistical formulae that represent the business and analyze data
User interface: Dashboards or other interfaces allowing users to interact with and view results
Tools used to generate reports
Database reporting tools allow us to create reports based on the data stored in our database or data warehouse.
Two of the most popular types of databases are relational and NoSQL.
Relational databases store data in tabular relations and managed through a database management system.
Database reporting and database reporting tools rely on
connections to a relational database management system
(RDBMS)
The most popular types of relational database management systems
are
Structured Query Language (SQL) is used by database reporting tools to query and manage data in relational database management systems. Once a connection is established to a RDBMS, database reporting tools then can present data in reports and dashboards.
Difference Between Data warehouse and Data mart
Data warehouse | Data mart |
1.Data warehouse is centralised system. | 1.Data mart is decentralised system. |
2.In This Lightly Denormalization take place. | 2.In this highly Denormalization take place. |
3.It is Top-down model | 3.It is Bottom-up model. |
4. Difficult to build warehouse | 4. Easy to build mart |
5.Data warehouse has long life | 5.Data mart has short life than data warehouse |
6.It is vast in size | 6. It is small in size |
7. Data warehouse is flexible | 7.Data mart is not flexible |
8. It is data- oriented in nature | 8. It is project- Oriented in nature |
Primary use for data warehouse environment
In an organization, a data warehouse is used by many users to perform various activities. These users may range from executive level users to operational level users. The requirements however differ from these users as executive level users mostly involves in finding new patterns, trends, threats etc.
all of users can be categorized into three different categories as
follow:-
Explorer :-
In general, Explorer is a user who dig deep in to large data sets
to seek for unknown patterns and unsuspected information that are
very much valuable for the organization
Farmer :-
In general, Farmer is a user that harvests information from known
data. Farmers are the users who knows what they are looking for and
what they need at all times. These types of users are the most
frequent users of the data warehouse as they always search for
known data to find what they need.
Tourist :-
In general tourist is a type of user that browse information as and when they need. These users use the data warehouse very rarely and they are the users who least use the data warehouse.