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DATA WAREHOUSING & DATA MINING Submitted To:Submitted By: Johannes Hoppe                                      Jayant Shah  (M1000624) KetanSood (M1001626) TarunDahiya (M1001303)
INTRODUCTION A data warehouse architecture is primarily based on the business processes of a business enterprise taking into consideration the data consolidation across the business enterprise with adequate security, data modelling and organization, extent of query requirements, meta data management and application, warehouse staging area planning for optimum bandwidth utilization and full technology implementation.
PROCESS ARCHITECTURE Describes the number of stages and how data is processed to convert  raw/transactional data into information for end usage. The data staging process includes three main areas of concerns or sub-processes for planning data warehouse architecture namely “Extract”, “Transform” and “Load”. These interrelated processes are sometimes referred to as an “ETL” process. ,[object Object],The data for the data warehouse can come from different sources and may be of different types. ,[object Object],Transformation of data with appropriate conversion, aggregation and cleaning also an important process to be planned for building  a data warehouse.  ,[object Object],Steps to be considered to load data with optimization by considering the multiple areas where the data is targeted to be loaded and retrieved .
TOOLS USED ,[object Object]
MySQL Workbench
Pentaho Data Integration (Open source ETL tool),[object Object]
1.1 Verifying the data in Excel (Source)  Categories of errors in the source file dealt with. (a few example) ,[object Object]
 Incorrect
 Inconsistency,[object Object]
 Creating Table.

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DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

  • 1. DATA WAREHOUSING & DATA MINING Submitted To:Submitted By: Johannes Hoppe Jayant Shah (M1000624) KetanSood (M1001626) TarunDahiya (M1001303)
  • 2. INTRODUCTION A data warehouse architecture is primarily based on the business processes of a business enterprise taking into consideration the data consolidation across the business enterprise with adequate security, data modelling and organization, extent of query requirements, meta data management and application, warehouse staging area planning for optimum bandwidth utilization and full technology implementation.
  • 3.
  • 4.
  • 6.
  • 7.
  • 9.
  • 11.
  • 12. Q & A