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OLTP database - MySQL\n  2. NoSql database - MongoDB\n  3. Staging Data warehouse – PostgreSQL\n  4. Big data platform - Hadoop\n  5. Big data analytics platform – Spark\n  6. Business Intelligence Dashboard - IBM Cognos Analytics and Tableau\n  7. Data Pipelines - Apache Airflow\n### OLTP Database:\n  - [OLTP](https://github.com/mehassanhmood/DataEngineering-Project/tree/main/OLTP)\n  - We import the data in MySQL Database\n  - The loaded data along with sql query is retrieved and stored as a 'sql' file.\n### MongoDB:\n  - [NoSQL-MongoDB](https://github.com/mehassanhmood/DataEngineering-Project/tree/main/NoSQL-MongoDB)\n  - The data source is a .json file.\n  - The first step is connecting database and making a collection named 'electronics'\n      -This is done after establishing the connection with MongoAtlas and then running the *db-conn.js* file using mongo shell:\n        ```load('path/to/db-conn.js)```\n  - The next step is to load the data in the collection and save a copy of slected fields using *import-sxport.sh* file:\n      ```./import-export.sh```\n  - Finally we explore the loaded data using *mongodb-queries.js* file using mongo shell:\n      ```load('mongodb-queries.js)```\n### Staging Data Warehouse:\n  - [DataWarehousing-PostgreSQL](https://github.com/mehassanhmood/DataEngineering-Project/tree/main/DataWarehousing-PostgreSQL)\n  - This is for educational purposes only as a Data Warehouse requires reference data source and metadata.\n### Analytics:\n  - [Dashboards-BI](https://github.com/mehassanhmood/DataEngineering-Project/tree/main/Analytics)\n    1. Data Visualization for Understanding:\n       - Dashboards present complex data in visually intuitive formats.\n       - Visualization enhances comprehension, making data accessible to diverse stakeholders.\n    2. Real-Time Monitoring and Proactive Analysis:\n       - Dashboards offer real-time updates on key metrics for prompt decision-making.\n       - BI tools enable proactive problem identification by highlighting deviations and trends.\n    3. Informed Decision-Making with Actionable Insights:\n       - Dashboards provide a centralized source for actionable insights.\n       - BI facilitates data-driven decisions, fostering accountability and optimizing processes.\n### ETL:\n  - [ETL](https://github.com/mehassanhmood/DataEngineering-Project/tree/main/ETL)\n  - ETL serves as the backbone for integrating diverse data sources, ensuring a unified and consistent view across the organization.\n  - ETL enhances operational efficiency, facilitating timely and accurate data delivery to support informed decision-making in business processes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmehassanhmood%2Fdataengineering-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmehassanhmood%2Fdataengineering-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmehassanhmood%2Fdataengineering-project/lists"}