Microsoft Azure Data Lake Storage Service (Gen1 & Gen2)

How to ingest, process and export data in Azure Data Lake using Databricks and HDInsight

  Eshant Garg

   Office Productivity, Microsoft, Microsoft Azure

  Language - English

   Published on 02/2022



Course Introduction

  • Azure Data Lake Storage Gen2 (ADLS) is a cloud-based repository for both structured and unstructured data. For example, you could use it to store everything from documents to images to social media streams.

  • The most effective way to do big data processing on Azure is to store your data in ADLS and then process it using Spark (which is essentially a faster version of Hadoop) on Azure Databricks.

  • In this course, you will follow hands-on examples to import data into ADLS and then securely access it and analyze it using Azure Databricks and Azure HDInsight.

  • You will also learn how to monitor and optimize your Data Lake Storage.

Expected Outcomes

After this course:

  • You will have a very good understanding of Data lake features and properties

  • You will learn about different tools and scenarios to ingest data into Data Lake.

  • You will learn about Data Lifecycle and Architecture around Data Lake

  • You will be doing end to end demos to ingest, process, and export data using Databricks and HDInsight.

  • You will learn about 5 layers of Data Security and how to configure them using the Azure portal.

  • You will also learn about different tools Azure provides to monitor Data Lake Storage service.

  • And finally, you will learn optimization techniques for Data Lake Storage.

What Will I Get ?

  • Microsoft Azure Data Lake

  • Different tools and scenarios to ingest data in to Data Lake

  • Data Lifecycle and Architecture around Data Lake

  • Use Azure Databricks and HDInsight to process data in ADLS

  • Five layers of security to protect Data Lake

  • Monitor the performance of your Data lake

  • Data Lake optimization Strategy


  • Basic Database concepts

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