10
DATA WAREHOUSING & DATA MINING Submitted To: Submitted By: Johannes Hoppe Jayant Shah (M1000624) Ketan Sood (M1001626) Tarun Dahiya (M1001303)

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

Embed Size (px)

DESCRIPTION

5. ETL project by

Citation preview

Page 1: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

DATA WAREHOUSING &

DATA MINING

Submitted To: Submitted By:

Johannes Hoppe Jayant Shah (M1000624) Ketan Sood (M1001626) Tarun Dahiya (M1001303)

Page 2: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

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.

Page 3: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

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.

• ExtractThe data for the data warehouse can come from different sources and may be of different types.

• TransformTransformation of data with appropriate conversion, aggregation and cleaning also an important process to be planned for building a data warehouse.

• LoadSteps to be considered to load data with optimization by considering the multiple areas where the data is targeted to be loaded and retrieved .

Page 4: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

TOOLS USED

• MySQL Database• MySQL Workbench• Pentaho Data Integration (Open source ETL tool)

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

STEPS USED

1. DATA PREPARATION 1.1 Verifying the data in Excel sheet for different type of errors. 1.2 Preparing data base structure using MySQL.

2. DATA INTEGRATION 2.1 Extract the Data. 2.2 Transform the Data. 2.3 Load the Data.

Page 6: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

Categories of errors in the source file dealt with. (a few example)

• Incomplete• Incorrect• Inconsistency

1.1 Verifying the data in Excel (Source)

Page 7: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

1.2 Preparing data base structure

STEPS:

• Creating Schema.• Creating Table.• Creating Columns & assigning Primary Key.

Page 8: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

2. Data Integration

Page 9: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)

Q & A

Page 10: DMDW 5. Student Presentation - Pentaho Data Integration (Kettle)