Pentaho Kettle Solutions: Building Open Source ETL Solutions with Pentaho Data Integration

The ultimate resource on building and deploying data integration solutions with Kettle
Kettle is a scaleable and extensible open source ETL and data integration tool that lets you extract data from databases, flat and XML files, web services, ERP systems, and OLAP cubes. It provides over 120 built–in transformation steps to validate, cleanse, and conform data, as well as numerous options to load data into data warehouses and many other targets. Kettle is a comprehensive, low–cost alternative to traditional data integration tools like Informatica PowerCenter, IBM InfoSphere DataStage, and BusinessObjects Data Integrator.
This book explains in detail how to use Kettle to create, test, and deploy your own ETL and data integration solutions. You′ll learn to use Kettle′s programs to create transformations and jobs, use version control, audit data, and schedule your ETL solution. Then you′ll progress to more advanced concepts such as clustering and cloud computing, real–time data integration, loading a Data Vault model, and extending Kettle by building your own plugins. In addition, you′ll find hands–on examples and case studies that show exactly how to put Kettle′s features into practice.
Explore the components of the Kettle ETL toolset
Discover how to install and configure Kettle and connect it to various data sources and targets
Design and build every aspect of an ETL solution using Kettle
Learn how to load a data warehouse with Kettle
Understand the steps for deploying and scheduling ETL solutions
Gain the skills to integrate Kettle with third–party products
Learn to extend Kettle and build your own plugins
Use clustering and cloud computing to scale and improve the performance of your Kettle ETL solutions
Find out how to use Kettle for real–time data integration

Spis treści:
Introduction.
Part I Getting Started.
Chapter 1 ETL Primer.
Chapter 2 Kettle Concepts.
Chapter 3 Installation and Configuration.
Chapter 4 An Example ETL Solution—Sakila.
Part II ETL.
Chapter 5 ETL Subsystems.
Chapter 6 Data Extraction.
Chapter 7 Cleansing and Conforming.
Chapter 8 Handling Dimension Tables.
Chapter 9 Loading Fact Tables.
Chapter 10 Working with OLAP Data.
Part III Management and Deployment.
Chapter 11 ETL Development Lifecycle.
Chapter 12 Scheduling and Monitoring.
Chapter 13 Versioning and Migration.
Chapter 14 Lineage and Auditing.
Part IV Performance and Scalability.
Chapter 15 Performance Tuning.
Chapter 16 Parallelization, Clustering, and Partitioning.
Chapter 17 Dynamic Clustering in the Cloud.
Chapter 18 Real–Time Data Integration.
Part V Advanced Topics.
Chapter 19 Data Vault Management.
Chapter 20 Handling Complex Data Formats.
Chapter 21 Web Services.
Chapter 22 Kettle Integration.
Chapter 23 Extending Kettle.
Appendix A The Kettle Ecosystem.
Appendix B Kettle Enterprise Edition Features.
Appendix C Built–in Variables and Properties Reference.
Index.

Nota biograficzna:

Matt Casters is Founder of Kettle and works as Chief Data Integration at Pentaho, where he leads Kettle software development. Roland Bouman is an application developer focusing on open source web technology, databases, and business intelligence. Jos van Dongen is an independent business intelligence consultant and well–known author, analyst, and presenter.

Okładka tylna:

The ultimate resource on building and deploying data integration solutions with Kettle
Kettle is a scaleable and extensible open source ETL and data integration tool that lets you extract data from databases, flat and XML files, web services, ERP systems, and OLAP cubes. It provides over 120 built–in transformation steps to validate, cleanse, and conform data, as well as numerous options to load data into data warehouses and many other targets. Kettle is a comprehensive, low–cost alternative to traditional data integration tools like Informatica PowerCenter, IBM InfoSphere DataStage, and BusinessObjects Data Integrator.
This book explains in detail how to use Kettle to create, test, and deploy your own ETL and data integration solutions. You′ll learn to use Kettle′s programs to create transformations and jobs, use version control, audit data, and schedule your ETL solution. Then you′ll progress to more advanced concepts such as clustering and cloud computing, real–time data integration, loading a Data Vault model, and extending Kettle by building your own plugins. In addition, you′ll find hands–on examples and case studies that show exactly how to put Kettle′s features into practice.
Explore the components of the Kettle ETL toolset
Discover how to install and configure Kettle and connect it to various data sources and targets
Design and build every aspect of an ETL solution using Kettle
Learn how to load a data warehouse with Kettle
Understand the steps for deploying and scheduling ETL solutions
Gain the skills to integrate Kettle with third–party products
Learn to extend Kettle and build your own plugins
Use clustering and cloud computing to scale and improve the performance of your Kettle ETL solutions
Find out how to use Kettle for real–time data integration