
Extracting and Transforming Data in SSIS
SSIS is the main on-premises ETL (Extract, Transform, and Load) tool from Microsoft, and it's heavily utilized for data engineering on SQL Server. In this course, you'll learn how to install and configure SSIS, and develop ETL packages with it.
Learning Journey Context
Works well as a continuation after mastering Data Science fundamentals. It bridges the gap toward advanced, production-level engineering.
Relevant for: Data Scientist, Data Analyst, Machine Learning Engineer.
💡This course fits perfectly into our comprehensiveData Science Learning Path. Explore the ecosystem to see how it compares to other foundational skills.
Quick Facts
What You’ll Learn
Data engineering is in the backbone of advanced analytics, business intelligence, and machine learning activities, and is also one of the most exciting and rewarding professions in the IT industry today. SSIS is the main SQL Server tool for achieving ETL (Extract, Transform, and Load) goals, whether you are: Building a data warehouseRansforming unstructured or semi-structured files into valuable insights, orLoading massive amounts of information for data sciences operationsIn this SSIS tutorial, Extracting and Transforming Data in SSIS, you'll learn how to use SSIS to create and execute ETL Packages. First, you'll discover how to use conditional logic and loops to control your data flow. Next, you'll delve into integrating data from sources other than databases. Then, you'll explore additional processes, scripts, and packages to expand your ETL capabilities beyond SSIS. Finally, you'll learn how to transform data using Data Flow operations, and pipe data by Split, Merge, and Union operations. By the end of this tutorial, you'll be able to use SSIS to execute fundamental ETL processes.
Outcomes
- Course Overview : 1min.
- Understanding the SSIS Interface : 17mins.
- Building Your First SSIS Package : 17mins.
- Defining Common Control Flow Operations : 35mins.
- Integrating Advanced Control Flow Operations : 30mins.
- Transforming Data with Data Flow Operations : 45mins.
- Piping Data with Data Flow Operations : 19mins.
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