Azure Data Lake Storage Gen2 (ADLS Gen2)

Overview

Azure Data Lake Storage Gen2 (ADLS Gen2) is Microsoft’s enterprise-grade cloud storage service designed for big data analytics workloads.

This guide walks through the complete setup process, including:

• Create Azure Storage Account
• Configure ADLS Gen2
• Enable Hierarchical Namespace
• Deploy Storage Account
• Create Blob Container
• Upload Dataset
• Verify Uploaded Files

Architecture

Step 1 — Create Azure Storage Account

Step 2 — Configure Storage Account

Configure:

• Subscription
• Resource Group
• Storage Account Name
• Region
• Primary Service

Configure the storage account with the following settings:

Click Next

Step 3 — Enable Azure Data Lake Storage Gen2

Enable the Hierarchical Namespace.

This converts Azure Blob Storage into Azure Data Lake Storage Gen2.

Configuration:

• ✅ Enable Hierarchical Namespace
• Access Tier = Hot

Step 4 — Deploy Storage Account

Azure validates the configuration and deploys the storage account.

After deployment completes,

Step 5 — Create Blob Container

Container Name ecomm-raw-data

Step 6 — Open the Container

Open the newly created container.

Container ecomm-raw-data. You are now ready to upload the dataset.

Step 7 — Upload Dataset

Drag & Drop your files or browse manually.

Example datasets

• brands.csv
• category.csv
• customers.csv
• date.csv
• products.csv
• order_items.csv
• order_returns.csv
• order_shipments.csv

Step 8 — Verify Uploaded Files

After uploading, verify that all folders/files are available.

Expected Dataset

https://freedatacamp.org/wp-content/uploads/2026/09/dataset.tar

• brands/
• category/
• customers/
• date/
• products/
• order_items/
• order_returns/
• order_shipments/

Final Data Lake Structure

Storage Account
│
└── ecomm-raw-data
    │
    ├── brands/
    ├── category/
    ├── customers/
    ├── date/
    ├── products/
    ├── order_items/
    ├── order_returns/
    └── order_shipments/

Best Practices

• Use lowercase storage account names.
• Enable Hierarchical Namespace for Data Lake workloads.
• Use meaningful container names.
• Organize datasets into separate folders.
• Enable RBAC using Microsoft Entra ID.
• Enable Soft Delete and Versioning.
• Configure Lifecycle Management policies.
• Restrict public access to containers.
• Monitor storage usage using Azure Monitor.

Key Benefits