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Azure Data Lake

What is Azure Data Lake? (Need and How)

Azure Data Lake is a Microsoft's scalable cloud platform on Azure, ideal for data storage and analytics by data scientists, analysts, and developers.

Meaning of Azure Data Lake

A data lake is basically a place where large amounts of raw data or data in its native format are stored. When compared to a data warehouse which stores data in files or folders (hierarchical structure), data lakes provide unlimited space, unrestricted file size, and a number of ways to access data, along with the tools necessary to analyze, query, and process it. Data items in a data lake are assigned unique identifiers and metadata tags. Using this method, data can be retrieved from the data lake and a smaller set of relevant data can then be analyzed. Furthermore, data can also be stored in data lakes prior to being curated and moved into data warehouses.

There Are Various Types Of Data That Can Be Stored In A Data Lake, Including:

  • Human-generated data (e.g. blogs, emails, tweets)
  • Machine data (e.g. log files, Internet of Things, sensor readings)
  • Sales data, inventory data, ticketing data, etc.
  • Visuals, audio, and video

The purpose of a data lake is to provide large amounts of detailed source data that can then be analyzed for mining, graphing, clustering, and statistics. Businesses and organizations can benefit from data analytics by creating churn models, estimating customer churn rates, visualizing customer segments, and identifying customer segments.

In What Ways Does Azure Data Lake Work?

The Data Lake platform is based on Azure Blob Storage, a cloud-based object storage solution from Microsoft.The Data Lake platform is based on Azure Blob Storage, a cloud-based object storage solution from Microsoft. The solution features low-cost, tiered storage with high-availability and disaster recovery capabilities. It is integrated with other Azure services, including Azure Data Factory, which can be used to create and run extract, transform, and load (ETL) and extract, load, and transform (ELT) processes.

This solution uses the YARN (Yet Another Resource Negotiator) cluster management platform for Apache Hadoop. As well as servers in Azure SQL Database and Azure SQL Data Warehouse, it can scale dynamically across SQL servers within the data lake.

To use the Azure Data Lake, you will need to create a free account on the Microsoft Azure portal. All Azure services can be accessed within the portal.

Why Do You Need Azure Data Lake?

Organizations that want to benefit from big data can use the Azure Data Lake solution. Developers, data scientists, and analysts can access a data platform that stores data in any format and size as well as processes and analyzes it across multiple platforms and programming languages. It can be used in conjunction with your existing identity management and security solutions. Additionally, it integrates with other data warehouses and cloud environments. The following is a list of the types of organizations it can be useful for:

Data Warehousing

The solution can be used for integrating any type of enterprise data into a single data warehouse since it supports any type of data.

IoT Capabilities

Multiple devices can stream data to the Azure platform in real time.

Hybrid Cloud Support

A big data infrastructure on-premises can be extended to the Azure cloud by using the Azure HDInsight component.

Features for enterprises

Microsoft manages and supports the environment, and it has enterprise features for security, encryption, and governance. Azure supports the extension of on-premises security solutions and controls to the cloud.

Deployment Speed

With the Azure Data Lake solution, you can start using it pretty quickly. The portal provides access to all components, and no servers or infrastructure need to be installed or managed.

READ MORE: How The Adoption Of Data Lake As A Service Is Transforming The Businesses

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