Post on 22-Dec-2015
description
Introduction to Business Intelligence
What is Business
Intelligence ?
What is Business Intelligence?
“BI results when organizational , business and are designed and implemented with the goal of the strategic and operational capabilities of a wide range of internal and external .”
- International Data Corporation (IDC)
culture processes technologies
improving decision-making
stakeholders
What is Business Intelligence?
Culture, processes and technologies to improve decision making for stakeholders.
Business Intelligence history
In 1989, Howard Dresner proposed "business intelligence" as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."
Related data disciplines
• data mining• statistical analysis• forecasting• decision support
BI is used everywhere
FACTS: DATA→INFORMATION→KNOWLEDGE Facts are just actual or hypothetical representations. Data is the individual raw facts that are
out of context, have no meaning, and are difficult to understand
in context, have meaning and can be readily understood.
Information is a set of data in context that is relevant to one or more entities at a point in time or for a period of time.
Knowledge is the fact or condition of knowing something with familiarity gained through experience or association.
OLTP vs. OLAP
OnLine Transaction Processing (OLTP) systems are used for handling transactional data and optimized for performance during Read/Write operations specifically for a faster response (Relational Modeling).
Online Analytical Processing (OLAP) systems are read-only and are specifically meant for analytical purposes (Dimensional Modeling).
Small OLTP database
Business Issue: A customer’s order was seriously delayed.
Manager: Why?Order Fulfillment: Supplier issue.
Simple Business Question:Who was our product supplier?
1
23
4
Small OLTP database
1
23
4
5
6
7
8
9
1011
1228
33
42 89
Large OLTP database
The Data Warehouse
A data warehouse is a for all or parts of the that an 's various business systems
- Bill Inmon
central repository significantdata enterprise
collect
The Data Warehouse
Central repository for all significant data that an enterprise collects.
Extract, Transform and Load (ETL)
ETL tools perform three functions to move data from one place to another:
Extract data from sources such as ERP or CRM applications;
Transform that data into a common format that fits with other data in the warehouse; and,
Load the data into the data warehouse for analysis.
Ralph Kimball Bill Inmon
Star Schema Snowflake Schema
Vs.
Data Warehouse: Data Model
Data Model: Star Schema
1 to Many
Data Model: Snowflake Schema
1 to Many to Many
The OLAP Cube
Data Warehouse: Fact & Dimensions
Fact Measure
• What the business does Business Process
• Usually describes an action or event (verb)
Fact Tables: contain measure columns and dimension key columns
Measure: numerical values that can be aggregatedDimension: group of attributes that describe a business process
Attribute: characteristics of a dimension member
• Fact Internet Sales• Sales Amount• Discount Amount• Profit• Profit Margin
• Dim Customer• Name• Gender• Yearly Income
• Dim Product• Color• Size
Data Warehouse: Relationships
Business Process: Sales
DimCustomers
DimTime
DimProducts
FactOrders
FactOrdersKeyDimProductsKeyDimCustomersKeyDimTimeKeyMeasure QuantityMeasure PriceMeasure Discount
Fact:37 Lemons were sold during April in our Chicago stores.
Measure: Units sold
Dim
en
sio
n:
Pro
duct
Dimension: Time
Dim
ensi
on: G
eogr
aphy
Members, Leaf and Nonleaf Cells (aggregation)
Calculated by MDX
Dimension
Dimension
Dimension
Members
Data warehouse and data marts
Typical Business Intelligence Lifecycle
Layers of Business Intelligence
Business Intelligence In Microsoft
Presentation• SQL Server Reporting Services• SharePoint • Performance Point• Excel
Analysis• SQL Server Analysis Services• PowerPivot
E.T.L• SQL Server Integration Services• Excel
BI Layers at Microsoft
BI Microsoft Tools
SQL Server Data Tools
Microsoft SQL Server Analysis Services (SSAS)
Delivers business intelligence applications with: OLAP (Unified Dimensional Model (UDM))
Data mining.
Design, create, and manage multidimensional structures that contain data aggregated from other data sources, such as relational databases.
Unified Dimensional Model (UDM) provides a bridge between the
user and the data sources
The user issues queries against the UDM using a variety of client tools, such as Microsoft Excel.
Benefits: Greatly enriches the user model.
Provides high performance queries supporting interactive analysis, even over large data volumes.
Captures business rules in the model to support richer analysis.
Supports ‘closing the loop’: letting users can act upon the data they see.
Accessing the Data Sources Directly
SELECT Quotas.QuotaAmount, Quotas.EmployeeId, …
FROM OPENROWSET('SQLOLEDB','seattle1'; 'Sales'; 'MyPass',
'SELECT * FROM Forecasts.dbo.SalesQuota’ ) As Quotas
SELECT Sales.SalesAmount, Sales.EmployeeId, …
FROM OPENROWSET('SQLOLEDB','seattle2'; ‘Orders'; 'MyPass2',
'SELECT * FROM Sales.dbo.EmpSales’ ) As Sales
HR
Sales
Accessing the Data Sources by UDM
UDM contentsQuery
Sales Amount and Quota by Product Category
Multidimensional Expressions (MDX)
Query language used to work with and retrieve multidimensional data in (SSAS)
Based on the XML for Analysis (XMLA) specification
Used for:
Return data to a client application from a SSAS cube.
Format query results.
Perform cube design tasks, including the definition of calculated members, named sets, scoped assignments, and key performance indicators (KPIs).
Perform administrative tasks, including dimension and cell security.
MDX Sample
SELECT
{ [Measures].[Sales Amount],
[Measures].[Tax Amount] } ON COLUMNS,
{ [Date].[Fiscal].[Fiscal Year].&[2006],
[Date].[Fiscal].[Fiscal Year].&[2007] } ON ROWS
FROM [Adventure Works]
WHERE ( [Sales Territory].[Southwest] )
Thank you