The meeting covered setting up an ETL pipeline using SSIS in Visual Studio to load sales and related data from various Excel and CSV files into a Microsoft SQL Server "my shop" database.
Step-by-step tasks included creating SSIS projects, configuring data sources and destinations, designing and executing data flows, and defining new tables in SQL Server.
Attendees ensured tables were properly structured and verified successful data loading.
Discussions included handling possible data conversion errors and structuring fields for optimal storage.
Action Items
(not specified – Team/Owner TBD): Review data conversion for any future data type issues encountered during ETL loads.
(not specified – Team/Owner TBD): Add primary and foreign keys to tables where required after initial data load.
Setting Up ETL Pipeline for Sales Data
SSIS in Microsoft Visual Studio was used to create a new project to handle the ETL process.
A data flow task was created with an Excel file as the source and SQL Server as the destination.
Database "my shop" on server "Acer" was selected as the target; tables in the database were initially empty.
Creating and Configuring Tables
A new table "sales" was created with columns mapped from the spreadsheet, assigning appropriate data types (integers for IDs and keys, varchar for names, float for cost/price, etc.).
Adjustments were made to field sizes for efficiency (e.g., setting integer types where feasible, reducing varchar lengths).
Primary key designated on "transaction ID"; other potential constraints mentioned but not fully implemented in meeting.
Data Loading Execution and Validation
Data flow was executed successfully with no errors; SSIS process confirmed as complete.
Verification performed by checking the existence and structure of the new "sales" table in SQL Server.
Additional ETL tasks were created for other Excel files: "category" and "customer", each with their own new table definitions in SQL Server.
A CSV file ("marketing expenses") was also loaded, using a flat file connection in SSIS and mapped to a new table.
All destination tables were validated in SQL Server upon completion.
Potential Issues and Error Handling
Mentioned the potential for data type mismatches and need for data conversion, though detailed error resolution steps were not shown as the demonstration was educational.
Advised that foreign and primary keys could be added to tables after initial data loading.
Decisions
Loaded sales, category, customer, and marketing expenses data from Excel/CSV into "my shop" SQL Server database — Rationale: To enable structured storage and access for business analytics.
Open Questions / Follow-Ups
Should any data type conversion errors arise in the future, develop a standard resolution process.
Confirmation needed on data integrity and if all foreign/primary keys should be enforced post-load.
Assign clear owners for ongoing data management and key constraint tasks.