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BI:Business Intelligence (BI) solution
   

You require easy, efficient and complete BI system to support and assure your business strategy.

Currently, BI has become a crucial area in terms of company’s strategy and executing, and also causes great challenges in making decisions. As we know, precise and objective data is the premise of scientific decisions. All decisions of departments should depend on data analysis and support, first, on reality and then on truth.

1

Evolution of BI

2

Early Management Information Systems 3 Analyzing Data from Operational Systems

4

Why OLTP Is Not Suitable for Analytical Reporting

5

Data Extract Processing 6 Issues with Data Extract Programs

7

Productivity Issues with Extract Processing

8

Data Quality Issues with Extract Processing 9 Data Warehousing and Business Intelligence
10 Advantages of Warehouse Processing Environments 11 Advantages of Warehouse Processing Environments 12 Business Intelligence: Definition and Purpose
13 Success Factors for a Dynamic Business Environment 14 Business Drivers for Data Warehouses 15 Business Intelligence: Requirements
16 Problem: Multivendor, Unintegrated Environment 17 Introduction to Microsoft Business Intelligence Tools and Applications 18 Microsoft’s Complete and Integrated Solution
19 Microsoft Business Intelligence Architecture        


 1.Evolution of BI Back
Executive information systems (EIS) Evolution of BI
Decision support systems (DSS)
Data warehousing (DW) and business intelligence (BI)
 

 2.Early Management Information Systems Back
MIS systems provided business data. Early Management 
Information Systems
Reports were developed on request.
Reports provided little analysis capability.
Decision support tools gave personal ad hoc access to data.
 
 3.Analyzing Data from Operational Systems Back
Data structures are complex.
Analyzing Data from Operational Systems
Systems are designed for high performance and throughput
Data is not meaningfully represented.
Data is dispersed.
OLTPsystems may be unsuitable for intensive queries.
 
 4.Why OLTP Is Not Suitable for Analytical Reporting Back

OLTP

Analytical Reporting

nformation to support day-to-day service

Historical information to analyze

Data stored at transaction level

Data needs to be integrated

Database design: Normalized

Database design: Denormalized, star schema

 5.Data Extract Processing  Back
End-user computing offloaded from the operational environment
User’s own data
 
 6.Issues with Data Extract Programs   Back
 7.Productivity Issues with Extract Processing  Back
Duplicated effort
Multiple technologies
Obsolete reports
No common metadata
 
 8.Data Quality Issues with Extract Processing  Back

No common time basis

Different calculation algorithms Different levels of extraction

Different levels of granularity

Different data field names Different data field meanings

Missing information

No data correction rules No drill-down capability

 9.Data Warehousing and Business Intelligence Back
 10.Advantages of Warehouse Processing Environments  Back
Controlled Early Management 
Information Systems
Reliable
Quality information
Single source of data
 
 11.Advantages of Warehouse Processing Environments  Back

No duplication of effort

No need for tools to support many technologies No disparity in data, meaning, or representation

No time period conflict

No algorithm confusion No drill-down restrictions

 12.Business Intelligence: Definition and Purpose Back
  “Business intelligence is the process of transforming data into information and through discovery transforming that information into knowledge.” – Gartner Group
  The purpose of business intelligence is to convert the volume of data into business value through analytical reporting.
  Evolution of BI
 13.Success Factors for a Dynamic Business Environment Back

Know the business

Reinvent to face new challenges
Invest in products

Invest in customers

Retain customers Invest in technology

Improve access to business information

Provide superior services and products Be profitable

 14.Business Drivers for Data Warehouses  Back
Provide supporting information systems  
Get quality information:  
 
- Reduce costs
- Streamline the business
- Improve margins
 
 15.Business Intelligence: Requirements Back

Efficient design of data warehouses

Enterprise reporting Ad hoc query and analysis (relational and multidimensional)

Advanced analytics

Integration with portals Easy administration

Integrated environment and/or tools  

 16.Problem: Multivendor, Unintegrated Environment Back
 
 17.Introduction to Microsoft Business Intelligence Tools and Applications Back

Microsoft SQL Server Integration Services (SSIS)

Microsoft SQL Server Analysis Services (SSAS) Microsoft SQL Server Reporting Services (SSRS)

Microsoft PerformancePoint Server 2007

Microsoft Sharepoint Server 2007 Microsoft Search Server 2008

Microsoft Project Server 2007 Microsoft Communication Server 2007    

 18.Microsoft’s Complete and Integrated Solution      Back
 

 18.Microsoft Business Intelligence Architecture      Back
 


 
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