MSBI
Microsoft Business Intelligence is a power full suite and an ETL
(Extract Transform and Load) tool helps to find solutions for BI and data
mining queries. It uses visual studio and SQL Server. The three main components
of MSBI is SSIS-integration tool, SSAS-analysis tool, SSRS-reporting tool. It
will effectively analysis data to drive value to the organization. User can
create ad-hoc transactional report and a workspace to share in the spread
sheet. This tool facilitates user to access accurate information and work
quickly to take better business decisions this enhance business agility.
Note: Simply
Business intelligence is a broad category of applications and technologies for
gathering, storing, analyzing and providing access to data to help enterprise
users make better business decisions.
BI Applications: BI
applications include the activities of decision support systems, query and
reporting, online analytical processing, statistical analysis, forecasting and
data mining.
Dimensional Data Model: Dimensional
data model is used in data ware housing systems that means designing facts,
dimensions, hierarchy.
§ Dimension table :
The dimension table provides hierarchy and detailed information
about the attributes.
For Example:
Dim product, Dim customer and Dim time etc.
§ Fact table:
A fact table is a table that contains measures. Note: Measure is
a numerical value and it is key value to analyze your business data and it also
evaluates the performance of the organization.
Data Ware House
Concepts
Data ware housing is a Relational data base it has its own
characteristics.
Time variant Integrated Data Base
TINS Non-volatile Subject
Oriented
(1) Time
Variant: Data ware house is a time variant data base source, the
business users perform analysis on their business information with respect to
various time period.
(2) Integrated Data base: Data
ware house is built by integrate the data various operational sources into
single data base.
(3) Non –
Volatile: Once the source data is inserted into the data ware
housing it doesn’t reflect the changes since it is static or read only data.
(4) Subject Oriented Data
ware house is a subject oriented data base and it stores specific data about
specific department in the complete organization. It is also known as data
mart.
Note :- Data
mart is also known as HPQS (High Performance Query Structures) Data warehousing
Architectures: In designing data models for data ware houses or data marts, the
most commonly used schema types are,
1.
Star schema
2.
Snowflake Schema
The star schema data ware housing design contains at least one
fact table and surrounded by dimension tables like a star tech dimension is
represented as a single table. The primary key in each dimension table is related
to foreign key in the fact table. Note:
1.
A simple star schema consists of one fact table and a complex
star schema have more than have more than one fact table.
2.
All measures in the fact table are related to all the dimension
tables.
The Snow Flake schema is an extension to star schema, where each
point of the star schema explodes or divides into more points. In star schema
each dimension is represented by a single dimension table, where as
in a snow flake schema the dimension table is normalized into multiple look up
tables, each representing a level in the dimensional hierarchy.
In the above data ware housing schema example, we have three
lookup tables (Dim category, Dim product sub category and Dim address type).
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