# Azure Data Lake Storage

> Chapter 91 of the Courseiva AZ-900 curriculum — https://courseiva.com/learn/az-900/azure-data-lake

**Official objective:** 2.4 — Azure Architecture Services

## Introduction

This chapter covers Azure Data Lake Storage. AZ-900 tests under 2.4.

## A Massive Data Lake

A traditional data warehouse is structured for specific queries. A data lake is a massive storage area for raw data of any type, to be analyzed flexibly later.

## Core explanation

Data Lake Storage stores massive amounts of unstructured and structured data, supporting big-data analytics without the rigid structure of traditional warehouses. It's optimized for analytics workloads.

## Real-world context

An organization stores years of raw log files in a data lake, then analyzes them for patterns without pre-structuring the data.

## Exam focus

Objective 2.4 expects understanding of Data Lake as unstructured big-data storage.

## Step by step

1. **Create a Data Lake Storage account** — A storage account is provisioned.
2. **Load data** — Raw data of any type is loaded into the lake.
3. **Analyze** — Analytics tools query and analyze the data flexibly.

## Key takeaways

- Data Lake stores massive amounts of data flexibly.
- Optimized for analytics.
- Supports unstructured and structured data.

## FAQ

**What is Azure Data Lake Storage?**

It's a storage service optimized for big-data analytics, storing massive amounts of structured and unstructured data flexibly.

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Interactive version with quiz and diagrams: https://courseiva.com/learn/az-900/azure-data-lake