This repository is an attempt to solve the series of assignments presented during an ensias's course about datawarehouses. However, I will be using docker which means it will be slightly harder to implement, but I think it's worth it because containers are much more flexible and portable than establishing a local database.
| Atelier | Location |
|---|---|
| Installation et Exploration des bases de données AdventureWorks2019 et AdventureWorksDW2019 | Atelier 1 |
| Mise en place d’un Datawarehouse | Atelier 2 |
| Loading Data and Using Data Compression and Indexes | Atelier 3 |
| Extraction de données à partir d’un fichier plat | Atelier 4 |
| Slowly Changing Dimensions | Atelier 5 |
| Analyse et édition de rapports des données OLAP | Atelier 6 |
| Création et Mise en œuvre d’un DTW pour l’analyse des données de vente sur internet | Projet |
1. Make sure you have Docker downloaded
git clone https://github.com/Ignema/MSSQL-DTW-TP.git
docker build . -t <IMAGE-NAME> --build-arg SERVER=<SERVER-NAME> --build-arg MSSQL_SA_PASSWORD=<YOUR-PASSWORD>
For your server name, the default if left unspecified is localhost.
If unspecified, the default password will be myPassword30.
docker run --name <CONTAINER-NAME> -p 1433:1433 -d <IMAGE-NAME>
If you don't specify a value for your container name then docker will generate a random name for you.
scripts/windows/mount.bat <CONTAINER-NAME> <YOUR-PASSWORD>
source scripts/linux/mount.sh <CONTAINER-NAME> <YOUR-PASSWORD>
- SQL Server Management Studio
- Azure Data Studio
- Visual Studio (If you plan on using SSIS and SSDT then use this one.)
- Visual Studio Code
- SQL Server (myssql)
- ERD Editor
- BONUS: Docker
scripts/windows/schema.bat <SERVER-NAME> <DATABASE-NAME> <USER-NAME> <YOUR-PASSWORD>
source scripts/linux/schma.sh <SERVER-NAME> <DATABASE-NAME> <USER-NAME> <YOUR-PASSWORD>