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Cognos 8 BI Transformer Fundamentals. Objectives  At the end of this module, you should be able to:  discuss the basics of OLAP analysis  discuss the.

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Presentation on theme: "Cognos 8 BI Transformer Fundamentals. Objectives  At the end of this module, you should be able to:  discuss the basics of OLAP analysis  discuss the."— Presentation transcript:

1 Cognos 8 BI Transformer Fundamentals

2 Objectives  At the end of this module, you should be able to:  discuss the basics of OLAP analysis  discuss the importance of business requirements  review PowerPlay and Cognos 8 BI components  define a model

3  Business intelligence allows people to:  use corporate data to support decision-making  explore and analyze data to reveal trends within a business Raw Data Organized Information Better Business Decisions Business Intelligence

4 Quarter Month Type Customer Line Brand Number Country Branch Sales Rep Quantity Cost Margin Combination 1 Quarter Month Type Customer Line Brand Number Country Branch Sales Rep Quantity Cost Margin Combination 2 When? Time (2001) Who? Customers (Channels) What? Product (Type) Where? Location (Region) Result? Indicator (Revenue) Comprehensive Sales Analysis Multidimensional Analysis

5 PowerPlay Reports PowerCube Users Benefits of Transformer  Transformer is:  easy to customize  flexible and portable  designed for production environments

6  The business requirements impact every aspect of the PowerPlay model and cube.  By keeping these requirements at the center of your design, you can better serve the decision- makers in your organization. Business Requirements Dimensional Modeling Technical Architecture Design Physical Design Data Staging Design End-User Application Specification Deployment Planning Maintenance and Growth Project Planning and Management Business Requirements

7 Data Source SELECT Table.Column_Name FROM(Products OUTER JOIN Customers ON Products.Product_Number=Customers.Customer_Number) GROUP BY... Transformer Model PowerCube Transformer What is a Model?

8  Transformer can save models as the following two types of files: .mdl - a model stored in ASCII file format is a smaller size, compatible between versions of Transformer, and can be used for find and replace activities .py? - a model stored in binary file format is a larger size, version-specific, and quicker to load Model Types

9 1. Import your data source  Do I have the data that meets my needs and my user’s needs? 2. Create and examine your measures  Do they reflect how you measure the performance of your business? 3. Create and examine your dimensions and levels  Do they allow effective data analysis? 4. Create and test your PowerCubes  Does it provide the right information in a way that is easy to understand and work with? From Model to PowerCube

10  a structure that stores data multidimensionally and provides:  secure data access  fast retrieval of data  can be distributed across a network or to individual computers. What is a PowerCube?

11  A PowerCube is a generated, binary Transformer model ready to be viewed and analyzed in PowerPlay. What is a PowerCube? (cont'd)

12 Measures  A measure can:  provide quantifiable results that gauge the success of your business  address primarily numeric questions  add perspective to your data

13  Dimensions represent the highest level of data.  Levels represent a logical hierarchy of that data. Order Date Products Locations Years Quarters Months Product Line Product Type Product Name Sales Territory Country City Dim 1 Dim 2 Dim 3 Dim 4Dim 5 Staff Name Question to be answered When What Where Who How Dimensions Levels What are Dimensions and Levels?

14 When What Where Who How Order Date Locations Retailer Types Margin Ranges Products Dim 1 Dim 2 Dim 3 Dim 4Dim 5 Dimension Name Years Quarters Months Product Line Product Type Product Name Sales Territory Country City Retailer Type Margin Range Staff Name Levels 2 1 3 4 Additional Dimensions  Add dimensions or exception dimensions to further define your application.

15 The Locations Dimension Northern Europe Sweden Kista Categories: Norway Denmark Finland Level: Sales Territory Categories: Level: Country Level: City Category:  Categories are individual data elements that populate a level in a dimension. What are Categories/MEMBERS?

16 Summary  At the end of this module, you should be able to:  discuss the basics of OLAP analysis  discuss the importance of business requirements  review PowerPlay and Cognos 8 BI components  define a model


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