Azure Data Engineering
Azure Data Engineering is a discipline focused on designing, building, and maintaining data systems and pipelines using Microsoft’s Azure cloud platform. It involves leveraging various Azure services to handle the full lifecycle of data management, from ingestion and storage to processing and analysis. Key aspects of Azure Data Engineering include:
- Data Ingestion: Collecting data from diverse sources, such as on-premises systems, cloud services, or external data providers, using tools like Azure Data Factory, which orchestrates and automates data workflows.
- Data Storage: Storing data in scalable and secure environments. Azure offers options such as Azure Data Lake Storage for large-scale data lakes and Azure Blob Storage for unstructured data, allowing for efficient data management and retrieval.
- Data Processing: Transforming and processing data to derive insights. This can be achieved using Azure Synapse Analytics, which integrates big data and data warehousing capabilities, or Azure Databricks, which provides a unified analytics platform based on Apache Spark.
- Data Integration: Combining and integrating data from various sources to provide a cohesive view. Azure Synapse Analytics and Azure Data Factory are commonly used for data integration tasks.
- Data Analysis: Utilizing advanced analytics and machine learning to extract valuable insights from data. Azure provides services like Azure Machine Learning and Azure Synapse Analytics to support these activities.
- Data Security and Governance: Ensuring data is protected and complies with regulations through Azure’s built-in security features and governance tools, including Azure Policy and Azure Security Center.
Overall, Azure Data Engineering enables organizations to build robust, scalable data solutions that support data-driven decision-making and operational efficiency.
Original price was: ₹30,000.00.₹24,999.00Current price is: ₹24,999.00.
Course Overview
Azure Data Engineering involves designing, building, and managing data pipelines and systems using Microsoft’s Azure cloud platform. It encompasses a range of activities such as data ingestion, storage, processing, and integration to ensure efficient and scalable data workflows. Key components include Azure Data Factory for orchestration, Azure Data Lake for storage, Azure Synapse Analytics for data integration and analytics, and Azure SQL Database for relational data management. The goal is to enable organizations to gather, process, and analyze large volumes of data effectively to drive insights and decision-making.