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Introduction to SQL Server Analysis Services

SQL Server Analysis Services (SSAS)

Need of Analytical Applications

To create multidimensional objects and to provide multidimensional analysis, we require analytical applications

EX: COGNOS, BO, MICROSTRATEGEY, SSAS, HYPERION, OBIEE ETC………

  • SSAS, COGNOS, MICROSTARTEGY ……. ETC Tools are pure MOLOP tools

Structure of Multidimensional Objects:

Generally dimension modeling structure (star schema, snow flake Schema etc) used for multidimensional objects providing many- many relationship with E-R modeling is difficult

Multidimensional Object Usage (Cube Usage):

It provides support to end user (or) client by using various tools and applications

Screenshot_81

SSAS Components and Operations

  1. Cube designing
  2. Cube creation
  3. Writing calculations
  4. Performing actions
  5. Implementing KPIS (Key performance indicators)
  6. Creating and working with partitions
  7. Providing Multilanguage support using trans\
  8. Designing the aggregations
  9. Creating named calculation and queries

Sample Project

Textile Manufacturing Industry

Description:

  • A text tile manufacturing industry manufactures various types of shirts, trousers, etc……
  • Shirts also are different various (half hand, full hand services) etc … trousers also with different various (full, half, ¾) etc….
  • These product sale is happens different location in different time zones (time period)
  • Various raw material requires are (chemical, oils, cloths etc….) to manufactures this products
  • There are different storage areas ( go down, item keeping units) to maintain the product storage
  • For this project client require an analytical solution where they can take appropriate discussions on the business

STEPS REQUIRED FROM END TO END TO IMPLIMENT THE ABOVE PROJRCT

  1. Need to collect the discussions from major to minor
  2. According to the discussions analytical team collects or gathers the required business information from the project
  3. Analyzing the business requirements
  4. Identifying dimensions and facts for the above business and creating   LDM’s (logical data modeling )
  5. Converting LDM’s to PDM’s (physical data modeling)
  6. Based on the PDM’s we go for designing of the dimensional model (star schema , snow flake schema …. Etc  )
  7. Writing code to the design document in analysis services for analytical application (BO, cognos, Hyperion ….. etc)

Note: except the last step remaining all steps are platform independent

Conclusion:

For the above business, technical team identifies (data modulators, data designers, data architectures, domain experts, SME’s (subject modern experts)) the below dimension and fact tables

Dimensions ad fact tables:

a) Time dimension

b) Product dimension

c) Location dimension

d) Raw material dimension

e) Item storage unit dimension (ISU dimension)N

One fact table for the above all dimensions

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