Azure Data Lake is a solution used by various organizations and industries, including retail, healthcare, finance, manufacturing, and more.
Azure Data Lake is a cloud-based data storage and analytics service offered by Microsoft Azure. It is designed to handle large volumes of data, including structured, semi-structured, and unstructured, and supports big data processing and analytics. Here is how it works:

Data Storage: Azure Data Lake provides scalable storage for data of any size and format. The data can be stored in either Data Lake Store or Data Lake Gen2, built on top of Azure Blob Storage. Data Lake Gen2 is a hierarchical file system that provides more efficient data management and better performance.
Data Ingestion: Data can be ingested into Data Lake from various sources, including Azure Blob Storage, Azure Event Hubs, Azure Stream Analytics, Azure Data Factory, and more. Data can be ingested in real-time or in batches.
Data Processing: Once the data is ingested, it can be processed using various big data processing tools such as Azure HDInsight, Azure Databricks, or Azure Data Lake Analytics. These tools support popular big data frameworks such as Hadoop, Spark, and Hive.
Data Analytics: Data can be analyzed using Azure Analysis Services, Power BI, or other third-party tools. These tools can provide insights into the data and help users make data-driven decisions.