By the end of this course, learners will be able to:

1. Understand ETL principles and the role of SSIS in the Microsoft data ecosystem.
2. Build and manage SSIS packages using Control Flow and Data Flow components.
3. Configure various source and destination types including OLE DB, flat files, and Excel.
4. Use transformations for data cleansing, conversion, sorting, joining, and aggregation.
5. Leverage conditional logic and advanced transformations like Lookup, Merge, and Sampling.
6. Utilize variables and parameters for dynamic ETL workflows.
7. Optimize SSIS packages for performance and scalability.
8. Deploy SSIS solutions in enterprise environments.
9. Automate and schedule packages using SQL Server Agent.
10. Prepare for roles in BI, data integration, or ETL development.

 Syllabus

Module 1: Introduction to ETL and SSIS

• ETL concepts and lifecycle
• Importance of SSIS in ETL workflows

Module 2: SSIS Architecture

• Overview of SSIS runtime engine
• Integration with SQL Server and SSMS

Module 3: SSIS Package Components

• Control Flow: Task sequencing and workflow management
• Data Flow: Handling data extraction, transformation, and loading
• Connection Managers: Managing source and destination links

Module 4: Configuring Data Sources

• Using OLE DB, Flat File, and Excel sources

Module 5: Configuring Data Destinations

• Writing to OLE DB, Flat File, and Excel destinations

Module 6: SSIS Transformations

• Basic Transformations: Data Conversion, Derived Column, Copy Column
• Conditional Logic: Conditional Split
• Aggregation & Sorting: Aggregate, Sort
• Joining & Merging: Merge, Merge Join, Union All
• Advanced: Lookup, OLE DB Command, Row & Percentage Sampling

Module 7: Multi-Cast Transformation

• Data duplication and multi-stream processing

Module 8: Variables and Parameters

• Dynamic configurations using variables
• Defining and using package parameters

On completion of this course, learners will receive a Course Completion Certificate from Uplatz, validating their expertise in building SSIS-based ETL solutions.

This certification demonstrates your capability in designing and managing ETL packages using SSIS—an essential skill for BI developers, data professionals, and database engineers.

Mastery of SSIS opens up opportunities across business intelligence, data engineering, and analytics domains. As data becomes central to enterprise operations, skilled ETL professionals are in high demand.

Job Roles Include:

1. SSIS Developer
2. ETL/Data Integration Developer
3. Business Intelligence Analyst
4. Data Warehouse Engineer
5. SQL Server Developer
6. Data Migration Specialist

Industries Hiring SSIS Professionals:

• Finance & Banking
• Healthcare & Insurance
• Retail & eCommerce
• IT Consulting & System Integration
• Government & Public Sector
• Manufacturing & Logistics

1. What is SSIS and why is it used?
   SSIS is a platform for building enterprise-level data integration and ETL packages using SQL Server technologies.
2. What are the core components of an SSIS package?
   Control Flow, Data Flow, Connection Managers, Event Handlers, and Variables.
3. What is the difference between Merge and Merge Join transformations?
   Merge combines sorted datasets with similar metadata, while Merge Join performs SQL-style joins on sorted datasets.
4. How does Lookup transformation work?
   It retrieves related data from a reference dataset during data flow, functioning like a SQL JOIN.
5. What are Connection Managers in SSIS?
   They define the connections to data sources and destinations such as databases, files, or Excel.
6. How can variables and parameters be used in SSIS?
   Variables provide dynamic runtime values within packages, while parameters pass external configuration values.
7. What is the use of Conditional Split in SSIS?
   It routes data rows based on specified conditions, similar to a SQL CASE statement.
8. What is the purpose of Multi-Cast transformation?
   It duplicates input data into multiple outputs for parallel processing.
9. How do you handle error rows in SSIS?
   Use error outputs in transformations to redirect failed records for logging or alternate processing.
10. How is an SSIS package deployed and scheduled?
    Packages are deployed to SQL Server and scheduled using SQL Server Agent or SSMS.

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