SQL Server ETL Pipeline with SSIS

SQL Server & Data Engineering Case Study

ETL pipeline project using SQL Server Integration Services to extract, transform, validate, and load data into reporting databases for analytics and Power BI reporting.

Watch Demo ETL Workflow Case Study Back to SQL Projects

SSIS SQL Server ETL Data Pipeline SSMS SQL Agent Power BI

ETL Workflow

A simplified view of how raw files and source data are prepared for reporting and analytics.

1. Source Data

CSV, Excel, or SQL source files

2. Staging Tables

Raw data loaded into SQL Server staging

3. SSIS Package

Automated extraction, transformation, and loading

4. Reporting Tables

Cleaned fact and dimension tables

5. Power BI

Dashboards and reporting datasets

Workflow: Source Files → SQL Server Staging → SSIS Package → Data Cleaning → Fact & Dimension Tables → Power BI Reporting

Business Problem

Business data often comes from multiple files and systems, such as CSV exports, Excel files, and operational databases. Manually importing and cleaning this data can be slow, repetitive, and prone to errors.

Reporting teams need a repeatable ETL process that can prepare clean and reliable data for SQL reporting, Power BI dashboards, and business analysis.

Solution

I developed ETL pipelines using SQL Server Integration Services to automate the process of extracting raw data, loading it into staging tables, applying transformations, validating records, and preparing reporting tables for analytics.

ETL Process

Extracted data from CSV, Excel, or SQL based source files
Loaded raw data into SQL Server staging tables
Applied transformations and business rules
Cleaned and standardized inconsistent values
Validated data before loading into reporting tables
Created reporting ready fact and dimension tables
Prepared clean datasets for Power BI dashboards and SQL reports

Key Features

Automated data loading process
Staging table design
Data type conversion and formatting
Duplicate and missing value checks
Transformation logic for reporting tables
Reusable ETL package structure
Reporting ready output for analytics

Tools Used

SSIS SQL Server SSMS SQL Agent CSV Excel ETL Power BI

Project Documentation

View the SQL Server Integration Services project documentation, workflow design, ETL process, and implementation details on GitHub.

View ETL Documentation

Business Value

This ETL process helps reduce manual data preparation, improves reporting consistency, increases data quality, and gives business users cleaner datasets for dashboards and analytics.

ETL Pipeline Benefits

Key benefits of building automated ETL pipelines for business reporting.

Reduced Manual Work

Automates repetitive data loading and preparation tasks that would otherwise be done manually.

Improved Data Quality

Applies validation, cleaning, and transformation rules before data is used for reporting.

Reliable Reporting

Creates consistent reporting tables that can be used by Power BI, SQL reports, and business users.