Unlock Limitless Data Potential with Azure Data Lake

A highly scalable, parallel, and secure file system in the cloud, meticulously optimized for big data analytics and enterprise-wide data strategies.

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Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. It removes the complexities of ingesting and storing all of your data while making it faster to get up and running with batch, streaming, and interactive analytics.

Azure Data Lake works with existing IT investments for identity, management, and security for simplified data management and governance. It also integrates seamlessly with operational stores and data warehouses so you can extend current data applications.

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Store, Process, Analyze - Any Data, Any Scale

Benefits of Using Azure Data Lake

Experience unparalleled scalability, performance, and robust security for all your data initiatives.

No limits

On number of files, size of individual files, total amount of data stored, how long data can be stored, and ingestion throughput.

Low latency and high throughput

Workloads for ingesting streaming data, ensuring rapid processing.

Stores all data types

Store structured, semi-structured, and unstructured data with ease.

Highly available

With Local & Geo Redundant Storage options for robust data protection.

Hadoop-compatible

Via WebHDFS REST API. Supported by leading Hadoop distributions and HDInsight.

Provides POSIX-style permissions

For RBAC (Role-Based Access Control).

Integrates seamlessly

With your existing IT investment.

Transparent server-side encryption

Ensures data is always encrypted at rest and in-flight.

Affordable and cost-effective

Making enterprise-grade data storage accessible.

Enterprise-grade security, auditing, and support

Comprehensive security measures for peace of mind.

Advanced Analytics Pattern in Azure

Azure Data Lake is pivotal in constructing robust analytics pipelines, ingesting data from diverse sources for comprehensive processing and actionable insight generation.

Acquiring Data (Sources)

Sensors and IoT (unstructured)
Logs, files, and media (unstructured)
Business/custom apps (structured)

Acquiring Data (Methods & Tools)

Pull data from source
Source pushes data
Azure Data Factory

Storage Core

Azure Storage/Data Lake Store

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