Microsoft Azure Data Lake Storage Practice Exam

Microsoft Azure Data Lake Storage Practice Exam

Microsoft Azure Data Lake Storage is a cloud-based system where you can store and manage huge amounts of data. Think of it like a giant online storage locker for files, but designed to handle not just regular documents, but also complex data like videos, logs, and massive databases. It’s mainly used by businesses that collect large volumes of information and need a secure, flexible place to keep it.

With Azure Data Lake Storage, organizations can store both structured data (like spreadsheets) and unstructured data (like images or audio files) in one place. It’s built for high performance and can handle advanced data analysis tasks. This means companies can search, analyze, and learn from their data more easily—helping them make smarter decisions faster.

Who should take the Exam?

This exam is ideal for:

• Data Engineers
• Cloud Architects
• Data Analysts
• Database Administrators
• Professionals managing enterprise data infrastructure
• Students interested in cloud data storage
• Business Intelligence professionals
• Developers implementing big data pipelines

Skills Required

• Understanding of basic cloud concepts
• Familiarity with Microsoft Azure platform
• Knowledge of data formats (CSV, Parquet, JSON)
• Basics of data lakes and storage hierarchies
• Experience with analytics tools (preferred)

Knowledge Gained

• Configuring and provisioning Azure Data Lake Storage
• Managing storage accounts and hierarchical namespaces
• Securing data with access control and encryption
• Integrating ADLS with Azure Data Factory, Synapse, and Databricks
• Performing data ingestion and transformation
• Monitoring and optimizing storage performance
• Managing metadata and lifecycle policies
• Understanding cost optimization strategies

Course Outline

The Microsoft Azure Data Lake Storage Exam covers the following topics -

1. Introduction to Azure Data Lake Storage

• What is a Data Lake?
• Key features of ADLS
• ADLS Gen1 vs Gen2

2. Getting Started with ADLS

• Creating a storage account
• Understanding containers and file systems
• Navigating through Azure Portal and CLI

3. Data Storage Concepts

• Flat vs hierarchical namespace
• Working with files and folders
• Storage tiers and redundancy options

4. Security and Access Control

• Role-based access control (RBAC)
• Access control lists (ACLs)
• Encryption at rest and in transit

5. Data Ingestion and Integration

• Ingesting data with Azure Data Factory
• Integration with Azure Synapse and Databricks
• Using APIs and SDKs for ingestion

6. Working with Data

• Reading/writing data using Spark or Synapse
• Partitioning and organizing data efficiently
• Querying data in place with serverless engines

7. Monitoring and Optimization

• Enabling diagnostic logging
• Tracking performance and usage metrics
• Managing quotas and limits

8. Data Lifecycle and Governance

• Data retention policies
• Tagging and metadata management
• Implementing lifecycle rules

9. Cost Management

• Understanding ADLS pricing
• Estimating storage and transaction costs
• Optimizing for cost efficiency