The document is a presentation about open source ETL (extract, transform, load) using Talend Open Studio. It introduces the presenter and defines ETL as a process of extracting data from outside sources, transforming it to fit operational needs, and loading it into a target database or data warehouse. It then discusses Talend Open Studio as an open source ETL tool and provides software suites for ETL. The presentation concludes with an example of hands-on ETL using Talend Open Studio.

1. Open Source ETL using Talend Open Studio
Lu´ Santos
ıs
luis@luissantos.pt
February 14, 2013
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2. Overview
1 Who am i?
2 What is ETL?
3 ETL Software Suites
4 Talend Open Studio for Data Integration
5 Hands on
6 Conclusion
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3. Warning!!!
This presentation was created using Latex
Why?
Because i can!
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4. Who am i?
Lu´ Santos luis@luissantos.pt
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5. Who am i?
Software Engineer and
Mathematics Student
Open Source addicted
PHP and Java Developer
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6. What is ETL?
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7. What is ETL?
In computing, Extract, Transform and Load (ETL) refers to a
process in database usage and especially in data warehousing
that involves:
Extracting data from outside sources
Transforming it to fit operational needs (which can include
quality levels)
Loading it into the end target (database, more specifically,
operational data store, data mart or data warehouse)
(2013, http://en.wikipedia.org/wiki/Extract, transform, load)
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8. ETL Software Suites
Pentaho Data Integration (Kettle)
SQL Server Integration Services
Talend Open Studio for Data Integration
etc...
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9. Talend Open Studio for Data Integration
Talend Open Studio is a set of tools for developing, testing, deploying and
application integration projects.
Talend Open Studio for Big Data
Bonita Open Solution (BPM)
Talend Open Studio for Data Integration
Talend Open Studio for Data Quality
Talend ESB
Talend Open Studio for MDM
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10. Datasource(rer)s
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11. Datasources (Extract and Load)
Mysql, MSSQL, Oracle, Sqlite, FirebirdSQL, XLS, CSV, XML, SOAP,
REST, HTTP, FTP, SSH, Imap
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12. Transformers
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13. Transformers (Transform)
Sort data
Convert data
Cross data between datasources
Filter data
Fuzzy search
Normalize and Denormalize data
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14. Where and how ?
Where ?
Multi-platform ( Linux, MacOs, BSD-* even on windows )
You just need a JVM (Java Virtual Machine)
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15. Where and how ?
Where ?
Multi-platform ( Linux, MacOs, BSD-* even on windows )
You just need a JVM (Java Virtual Machine)
How ?
Execute it from your favorite programming language using syscalls
Command line
From your JVM based application (Java, Groovy, JRuby)
Webservices runing on the top Java App Server (Tomcat, Glassfish)
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16. Hands on
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17. Hands on
Querying data
Joining data from multiple datasources
Filtering and sorting data
Exporting data
Deploying your job
Calling it from PHP
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18. Database Schema
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19. Example
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20. ”With great power comes great responsability.”
(Voltair)
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21. The End
email: luis@luissantos.pt
twitter: @santosluis87
linkedin: https://www.linkedin.com/in/luissantos87
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