Azure Data Engineering

  Structure a Data Lake Using the Medallion Architecture One popular and effective approach is the medallion architecture, which introduces a layered structure — bronze, silver, and gold — to manage data pipelines more logically and systematically. Let’s explore how this architecture helps in building a scalable and performance-optimized data lake. In the world of big data and analytics, efficiently organizing and processing massive volumes of data is critical for success. Structure a Data Lake Using the Medallion Architecture 1. Introduction to the Medallion Architecture The medallion architecture is a data design pattern used to incrementally improve the quality of data through structured layers. The core idea is to ingest raw data into a "bronze" layer, refine and clean it in the "silver" layer, and present the final analytical dataset in the "gold" layer. This design provides a clean separation of concerns, enables debugging, and simplifies gove...

  Azure Hot, Cool & Archive Storage Tiers Explained Microsoft Azure offers three main storage access tiers: hot, cool, and archive. These tiers help businesses manage their data cost-effectively depending on how often the data is accessed. In today’s cloud-driven world, data storage is no longer just about capacity—it's about choosing the right performance and cost strategy. Azure Hot, Cool & Archive Storage Tiers Explained 1. Hot Tier: For Frequently Accessed Data This might include transactional data, active business files, or recently uploaded content that needs quick and regular retrieval. The storage cost for the hot tier is higher compared to other tiers, but the access cost is low, making it ideal for active workloads. For professionals enrolled in the Azure Data Engineer Course Online , understanding this tier is crucial. It's often used in real-time applications where high-speed access is necessary, such as e-commerce platforms or financial dashboards...

  Secure Data in Azure Data Lake Using RBAC and ACLs Azure Data Lake Storage (ADLS) provides enterprise-grade capabilities to manage access to big data. This article walks you through how to secure data in Azure Data Lake using Role-Based Access Control (RBAC) and Access Control Lists (ACLs), which are essential tools for any data engineer. In today's cloud-first data ecosystem, securing sensitive information is non-negotiable. Secure Data in Azure Data Lake Using RBAC and ACLs 1. Understand the Basics of Azure Data Lake Security Before diving into configuration, it's important to grasp the core security model of Azure Data Lake. Microsoft uses a layered security model: ·          Authentication: Azure Active Directory (Azure AD) handles user identity. ·          Authorization: Controlled via RBAC and ACLs. RBAC controls access to resources in Azure at the management level , whereas AC...