ในยุคแห่งข้อมูล ใครที่รู้จักใช้ข้อมูลย่อมได้เปรียบ โดยใช้เครื่องมือที่เรียกกันว่า Big Data และ Data Analytics เริ่มจากสิ่งที่ใกล้ตัวเราก่อนอย่างการช้อปปิ้งออนไลน์ ไปจนถึงแคมเปญหาเสียงที่ดังที่สุดในโลกของโดนัลทรัมป์...
Read More4 วัน
100,000 บาท (อบรมไม่เกิน 10 ท่าน)
In-house
ติดต่อเรา
1. Getting Started with Pentaho Data Integration | |
Pentaho Data Integration and Pentaho BI Suite | |
Installing PDI | |
Launching the PDI Graphical Designer – Spoon | |
Introducing transformations | |
Installing useful related software | |
2. Getting Started with Transformations | |
Designing and previewing transformations | |
Understanding PDI data and metadata | |
Handling errors | |
3. Creating Basic Task Flows | |
Introducing jobs | |
Designing and running jobs | |
Running transformations from a Job | |
Understanding and changing the flow of execution | |
Managing files | |
Knowing the basics about Kettle variables | |
4. Reading and Writing Files | |
Reading data from files | |
Outputting data to files | |
Working with Big Data and cloud sources (AWS S3, HDFS) |
5. Manipulating PDI Data and Metadata | |
Manipulating simple fields | |
Working with complex structures | |
6. Controlling the Flow of Data | |
Filtering data | |
Splitting streams unconditionally | |
Splitting the stream based on conditions | |
Merging streams in several ways | |
Looking up data | |
7. Cleansing, Validating, and Fixing Data | |
Cleansing data | |
Validating data | |
Treating invalid data by splitting and merging streams | |
8. Manipulating Data by Coding | |
Doing simple tasks with the JavaScript step | |
Parsing unstructured files with JavaScript | |
Doing simple tasks with the Java Class step | |
Getting the most out of the Java Class step | |
Avoiding coding using purpose-built steps |
9. Transforming the Dataset | |
Sorting data | |
Working on groups of rows | |
Converting rows to columns | |
Normalizing data | |
Going forward and backward across rows | |
10. Performing Basic Operations with Databases | |
Connecting to a database and exploring its content | |
Previewing and getting data from a database | |
Inserting, updating, and deleting data | |
Verifying a connection, running DDL scripts, and doing other useful tasks | |
Looking up data in different ways | |
11. Loading Data Marts with PDI | |
Preparing the environment | |
Introducing dimensional modeling | |
Loading dimensions with data | |
Loading fact tables | |
12. Creating Portable and Reusable Transformations | |
Defining and using Kettle variables | |
Creating reusable Transformations | |
Making the data flow between transformations | |
Executing transformations in an iterative way |
13. Implementing Metadata Injection | |
Introducing metadata injection | |
Discovering metadata and injecting it | |
Identifying use cases to implement metadata injection | |
14. Creating Advanced Jobs | |
Enhancing your processes with the use of variables | |
Accessing copied rows for different purposes | |
Working with filelists | |
Executing jobs in an iterative way | |
15. Launching Transformations and Jobs from the Command Line | |
Using the Pan and Kitchen utilities | |
Supplying named parameters and variables | |
Using command-line arguments | |
Sending the output of executions to log files | |
Automating the execution | |
16. Best Practices for Designing and Deploying a PDI Project | |
Setting up a new project | |
Best practices to design jobs and transformations | |
Maximizing the performance | |
Deploying the project in different environments |
1. Getting Started with Pentaho Data Integration | |
Pentaho Data Integration and Pentaho BI Suite | |
Installing PDI | |
Launching the PDI Graphical Designer – Spoon | |
Introducing transformations | |
Installing useful related software | |
2. Getting Started with Transformations | |
Designing and previewing transformations | |
Understanding PDI data and metadata | |
Handling errors | |
3. Creating Basic Task Flows | |
Introducing jobs | |
Designing and running jobs | |
Running transformations from a Job | |
Understanding and changing the flow of execution | |
Managing files | |
Knowing the basics about Kettle variables | |
4. Reading and Writing Files | |
Reading data from files | |
Outputting data to files | |
Working with Big Data and cloud sources (AWS S3, HDFS) |
5. Manipulating PDI Data and Metadata | |
Manipulating simple fields | |
Working with complex structures | |
6. Controlling the Flow of Data | |
Filtering data | |
Splitting streams unconditionally | |
Splitting the stream based on conditions | |
Merging streams in several ways | |
Looking up data | |
7. Cleansing, Validating, and Fixing Data | |
Cleansing data | |
Validating data | |
Treating invalid data by splitting and merging streams | |
8. Manipulating Data by Coding | |
Doing simple tasks with the JavaScript step | |
Parsing unstructured files with JavaScript | |
Doing simple tasks with the Java Class step | |
Getting the most out of the Java Class step | |
Avoiding coding using purpose-built steps |
9. Transforming the Dataset | |
Sorting data | |
Working on groups of rows | |
Converting rows to columns | |
Normalizing data | |
Going forward and backward across rows | |
10. Performing Basic Operations with Databases | |
Connecting to a database and exploring its content | |
Previewing and getting data from a database | |
Inserting, updating, and deleting data | |
Verifying a connection, running DDL scripts, and doing other useful tasks | |
Looking up data in different ways | |
11. Loading Data Marts with PDI | |
Preparing the environment | |
Introducing dimensional modeling | |
Loading dimensions with data | |
Loading fact tables | |
12. Creating Portable and Reusable Transformations | |
Defining and using Kettle variables | |
Creating reusable Transformations | |
Making the data flow between transformations | |
Executing transformations in an iterative way |
13. Implementing Metadata Injection | |
Introducing metadata injection | |
Discovering metadata and injecting it | |
Identifying use cases to implement metadata injection | |
14. Creating Advanced Jobs | |
Enhancing your processes with the use of variables | |
Accessing copied rows for different purposes | |
Working with filelists | |
Executing jobs in an iterative way | |
15. Launching Transformations and Jobs from the Command Line | |
Using the Pan and Kitchen utilities | |
Supplying named parameters and variables | |
Using command-line arguments | |
Sending the output of executions to log files | |
Automating the execution | |
16. Best Practices for Designing and Deploying a PDI Project | |
Setting up a new project | |
Best practices to design jobs and transformations | |
Maximizing the performance | |
Deploying the project in different environments |
4 วัน
100,000 บาท (อบรมไม่เกิน 10 ท่าน)
In-house
ติดต่อเรา
1. Getting Started with Pentaho Data Integration | |
Pentaho Data Integration and Pentaho BI Suite | |
Installing PDI | |
Launching the PDI Graphical Designer – Spoon | |
Introducing transformations | |
Installing useful related software | |
2. Getting Started with Transformations | |
Designing and previewing transformations | |
Understanding PDI data and metadata | |
Handling errors | |
3. Creating Basic Task Flows | |
Introducing jobs | |
Designing and running jobs | |
Running transformations from a Job | |
Understanding and changing the flow of execution | |
Managing files | |
Knowing the basics about Kettle variables | |
4. Reading and Writing Files | |
Reading data from files | |
Outputting data to files | |
Working with Big Data and cloud sources (AWS S3, HDFS) |
5. Manipulating PDI Data and Metadata | |
Manipulating simple fields | |
Working with complex structures | |
6. Controlling the Flow of Data | |
Filtering data | |
Splitting streams unconditionally | |
Splitting the stream based on conditions | |
Merging streams in several ways | |
Looking up data | |
7. Cleansing, Validating, and Fixing Data | |
Cleansing data | |
Validating data | |
Treating invalid data by splitting and merging streams | |
8. Manipulating Data by Coding | |
Doing simple tasks with the JavaScript step | |
Parsing unstructured files with JavaScript | |
Doing simple tasks with the Java Class step | |
Getting the most out of the Java Class step | |
Avoiding coding using purpose-built steps |
9. Transforming the Dataset | |
Sorting data | |
Working on groups of rows | |
Converting rows to columns | |
Normalizing data | |
Going forward and backward across rows | |
10. Performing Basic Operations with Databases | |
Connecting to a database and exploring its content | |
Previewing and getting data from a database | |
Inserting, updating, and deleting data | |
Verifying a connection, running DDL scripts, and doing other useful tasks | |
Looking up data in different ways | |
11. Loading Data Marts with PDI | |
Preparing the environment | |
Introducing dimensional modeling | |
Loading dimensions with data | |
Loading fact tables | |
12. Creating Portable and Reusable Transformations | |
Defining and using Kettle variables | |
Creating reusable Transformations | |
Making the data flow between transformations | |
Executing transformations in an iterative way |
13. Implementing Metadata Injection | |
Introducing metadata injection | |
Discovering metadata and injecting it | |
Identifying use cases to implement metadata injection | |
14. Creating Advanced Jobs | |
Enhancing your processes with the use of variables | |
Accessing copied rows for different purposes | |
Working with filelists | |
Executing jobs in an iterative way | |
15. Launching Transformations and Jobs from the Command Line | |
Using the Pan and Kitchen utilities | |
Supplying named parameters and variables | |
Using command-line arguments | |
Sending the output of executions to log files | |
Automating the execution | |
16. Best Practices for Designing and Deploying a PDI Project | |
Setting up a new project | |
Best practices to design jobs and transformations | |
Maximizing the performance | |
Deploying the project in different environments |
ด้วยสาระน่ารู้ต่างๆจากเรา Going Jesse Co., Ltd.
ในยุคแห่งข้อมูล ใครที่รู้จักใช้ข้อมูลย่อมได้เปรียบ โดยใช้เครื่องมือที่เรียกกันว่า Big Data และ Data Analytics เริ่มจากสิ่งที่ใกล้ตัวเราก่อนอย่างการช้อปปิ้งออนไลน์ ไปจนถึงแคมเปญหาเสียงที่ดังที่สุดในโลกของโดนัลทรัมป์...
Read Moreยุคนี้เป็นยุคที่เทคโนโลยีใหม่ ๆ เข้ามามีบทบาทในชีวิตเรามากขึ้นเรื่อย ๆ ดิจิทัลเทคโนโลยีได้เปลี่ยน Business Landscape ให้ต่างไปจากเดิมทำให้ Operating Model การทำธุรกิจต้องเปลี่ยนตามไปด้วย วิธีการทำงานจะกลายเป็นดิจิทัล...
Read Moreเรื่องเกี่ยวกับ Data Science ว่ามันคืออะไร ทำให้คนถึงพูดถึงกันเยอะ และมันสำคัญอย่างไรต่อโลกธุรกิจ ออกตัวก่อนว่าผมเองทำงานในด้าน Data แต่ก็ไม่ได้ครอบคลุมทั้งหมดใน Data Science (เพราะมันกว้างมากๆ)...
Read MoreWhat are you looking for?