I want to share my journey through a challenging task. The task was to analyze and transform retail invoice data collected monthly from February to May. . It demonstrates real-time data ingestion, processing, storage, and live analytics of different tools. The project utilizes a combination of Excel, SSIS, Power BI, SQL Server, and Power BI.
The project consists of a scalable, data pipeline that processes, and stores data using different services and technologies.
- Data Analysis: Analyze data using Excel And Power Pivot.
- Data Pipeline (SSIS): Managed by SSIS To move And preprocess Into SQL Server.
- Data Processing (SQL Server ):
- First Step Cleaning Data And Drop Unwanted Columns.
- The second step builds Star Schema For Dimensions Tables And Fact and stores the results in SQL Server.
- Third Step Move Data From the Sql Server To Power Bi.
- Data Visualization: Processed data is displayed on Power BI for reporting.
- Excel: Data processing and analyzing data.
- SSIS: Move Data Pipline.
- SQL Server: Stores processed data and results.
- Power BI: Real-time dashboards for visualizing processed data.
- Microsoft Excel.
- SSISe.
- SQL Server.
- Power BI: Set up Power BI to visualize the data.
- Excel: Ensure Data is Good And Make Some Analysis.
- SSIS: Use SSIS to manage and Move Data From Excel To SSIS.
- SQL Server: SQL will process the data To Make Star Schema And Dim, Fact.
- Visualize Data in Power BI: Open Power BI and ensure real-time data is visualized from SQL Server.
