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Data Warehouse with Pentaho Data Integration

Data Warehouse with Pentaho Data Integration

Kuningan, Jakarta Selatan | 08 – 12 April 2019 | Fee at Proposal
Kuningan, Jakarta Selatan | 10 – 14 June 2019 | Fee at Proposal
Kuningan, Jakarta Selatan | 05 – 09 August 2019 | Fee at Proposal
Kuningan, Jakarta Selatan | 07 – 11 October 2019 | Fee at Proposal




Program Description:

 This program presents an overview of data warehouse, multi-dimensional, ETL concept, the extensive use of Pentaho Data Integration to build a powerful data warehouse solution. The practical approach of this program involved many cases we face before, so that participants will get a highly valuable skills from attending the class.



Program Objectives:

At the end of the program, the participants will be able to:

  • Understand the concepts and topics of Data Warehouse, Dimensional Modeling, OLAP and ETL
  • Use Pentaho Data Integration to build simple jobs / transformations
  • Consume data from several data sources
  • Build and Populating Fact and Dimensional tables
  • Apply troubleshooting techniques
  • Schedule job / transformation



Pentaho Data Integration Program Modules:

Module 1: Introduction to Data Warehouse

  • Data Warehouse
  • Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP)
  • Data Warehouse and OLAP
  • Delivering Solution with ETL (Extract, Transform, Load) Tool

Module 2: Installation and Configuration

  • Java Runtime Environment / Java Development Kit
  • Pentaho Data Integration
  • XAMPP package (Apache HTTP Server and MySQL)
  • SQLYog – a GUI based mysql client
  • Data and Script samples

Module 3: Short Introduction to MySQL

  • MySQL Storage Engines
  • Administering MySQL via PHPMyAdmin
  • PHI-Minimart sample database installation

Module 4: Pentaho Data Integration (Kettle)

  • Introducing Kettle as Pentaho’s ETL Suite
  • Architecture
  • Components
  • Spoon : Graphical UI Designer for job / transformation steps
  • Pan : Command line batch script for transformation execution
  • Kitchen : Command line batch script for transformation execution
  • Carte : Cluster server
  • Job / Transformation
  • Step and Hop
  • Row and Meta Data
  • Relation between job and transformation

Module 5: Getting Started with Spoon

  • File system and RDBMS based Repository
  • Spoon Development Environment
  • Database Connections
  • Job and Transformation
  • Creating job
  • Creating transformation
  • Calling transformation from job
  • Configuring Log

Module 6: Multi Dimensional Modelling

  • Normalized versus Multi Dimensional Model
  • Fact and Dimension Tables
  • Star Schema and Snowflake Schema
  • Tasks :
  • Create a Kettle transformation to map PHI-Minimart transactional database sample to dimensional modeling database
  • Create logs for each steps

Module 7: Change Data Capture (CDC)

  • What is CDC ?
  • Why CDC is so hard that heavily relied on data source ?
  • SQL Server 2008’s CDC feature demonstration
  • Tasks :
  • Create a Kettle transformation to map PHI-Minimart transactional database sample to dimensional modeling database
  • Create logs for each steps

Module 8: Slowly Changing Dimension (SCD)

  • Slowly Changing Dimension to solve master data historical problems
  • SCD Types
  • Use of Kettle’s step to solve several SCD types with several schema :
  • Insert / Update
  • Punch Through

Module 9: Orphan / Late Arrival

  • What is Late Arrival Dimension?
  • Typical Situations where Late Arrival occurs
  • Best practice of Late Arrival’s handling

Module 10: OLAP View of Multidimensional Data (Mondrian / JPivot)

  • Mondrian Installation
  • Creating scheme based on our fact and dimension tables
  • View and navigate our Cube using Web Browser

Module 11: Data Staging

  • What is Data Staging?
  • Background : Physical I/O versus In-Memory Processing
  • Task :
  • Create a transformation to join from 3 data sources : text file, Excel spreadsheet, and RDBMS
  • Create a currency staging table to solve sequential dependence problem

Module 12: Advance Controls

  • Environment Variables
  • Shared Objects
  • Error Handling
  • Email job results
  • Task :
  • Create a dynamic tables dump using variable and looping control
  • Refining existing transformations to use email alert

Module 13: Automation

  • Using Windows Task Scheduler to schedule ETL running job and transformation



Target Audience:

This program is designed for those new to Data Warehouse and ETL or need to understand the basics of Pentaho Data Integration.



Duration:

This program is 5 days of intensive training class.



Requirement:

Pentaho Analysis participants should possess:

  • Basic understanding one of several popular Database Management System (Oracle, SQL Server, MySQL, etc.) and of Structured Query Language (SQL)



VENUE AND TIME

Time                : 09.00AM – 05.00PM

Venue             : AXA Tower Kuningan City, Jl. Prof. Dr. Satrio Kav. 18, Setiabudi – Kuningan, Jakarta Selatan



INVESMENT

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