This repository is a collection of data engineering projects utilizing a variety of Azure services and data engineering tools. It serves as a resource for learning and implementing data engineering solutions on the Azure platform.
- Introduction
- Azure Services
- Programming Languages and Tools
- Installation and Setup
- Contributing
- License
Data engineering on Azure involves using a suite of cloud services and tools to build scalable, efficient, and secure data processing solutions. This repository highlights the key Azure services and programming tools commonly used in the field of data engineering.
The following Azure services are commonly used in data engineering projects:
- Azure Data Factory: For orchestrating and automating data movement and transformation.
- Azure Databricks: An Apache Spark-based analytics platform optimized for Azure.
- Azure Stream Analytics: For real-time data stream processing.
- Azure Synapse Analytics: A unified analytics service that brings together big data and data warehousing.
- Azure HDInsight: A cloud distribution of Hadoop components.
- Azure Blob Storage: For storing unstructured data.
- Azure SQL Database: A managed relational database service.
- Azure Data Lake Storage: A scalable data lake solution for big data analytics.
- Azure Event Hubs: A big data streaming platform and event ingestion service.
- Azure IoT Hub: For connecting, monitoring, and managing IoT assets.
- Azure Functions: For running event-driven serverless code.
- Azure Machine Learning: For building and deploying machine learning models.
- Azure Cosmos DB: A globally distributed, multi-model database service.
In addition to Azure services, the following programming languages and tools are frequently used in data engineering:
- Python: A versatile programming language widely used for data processing and analysis.
- Scala: A language often used with Apache Spark for big data processing.
- PySpark: The Python API for Apache Spark.
- SQL: A standard language for querying and managing data in relational databases.
- Power BI: A business analytics tool for data visualization and reporting.
- Apache Kafka: A distributed event streaming platform.
- Apache Spark: A unified analytics engine for big data processing.
- Jupyter Notebooks: An open-source web application for creating and sharing documents with live code.
- Azure Data Studio: A cross-platform database tool for data professionals.
- Tableau: A data visualization tool for creating interactive and shareable dashboards.
To work with the projects in this repository, you will need:
- Azure Subscription: Sign up for an Azure account if you don't have one.
- Azure CLI: Install and configure the Azure Command-Line Interface.
- Development Environment: Set up your preferred IDE or text editor with the necessary extensions for Azure development.
Contributions are welcome! If you have improvements or new projects to add, please fork the repository, create a new branch, and submit a pull request.