Different services in Azure data engineer.
In an Azure Data Engineer course, learners typically encounter various Azure services crucial for data engineering tasks. Here's a brief description of key services used in such a course:
Azure Data Factory: A cloud-based ETL (Extract, Transform, Load) service facilitating the creation of data-driven workflows for data movement and transformation.
Azure Databricks: An Apache Spark-based analytics platform enabling big data processing, machine learning, and collaborative data science.
Azure Synapse Analytics: Combines enterprise data warehousing and big data analytics, allowing for data integration, exploration, and advanced analytics.
Azure HDInsight: Fully managed open-source analytics service for Apache Hadoop, Spark, Hive, Kafka, and more, providing scalable data processing capabilities.
Azure Cosmos DB: A globally distributed, multi-model database service supporting various data models (document, key-value, graph, column-family) with high availability and low latency.
Azure SQL Database: A fully managed relational database service offering SQL Server capabilities, ensuring security, performance, and scalability.
Azure Data Lake Storage: Secure, scalable storage for big data analytics, enabling analytics across multiple platforms and languages.
Azure Stream Analytics: Real-time analytics service to process and analyze streaming data for insights and immediate action.
Azure Blob Storage: Object storage service for unstructured data, suitable for serving documents, images, videos, logs, backups, and more.
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