Microsoft Azure Data Lake Storage Service (Gen1 & Gen2)
What you'll learn
- 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
Course content
- Preview02:35
- 01:29Before you start...
- 00:01Demo Resources and PPT
Requirements
- Basic Database concepts
Description
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.
Intended Audience
Anyone interested in learning Azure Data Lake Storage Service
Level
Beginners and intermediate level
I have a few crash courses (Free) for absolute beginners, you can find links on my website.
Prerequisites
There is no prerequisite for this course
Basic understanding of Data warehouse and Database, in general, will help you understand quickly.
Language
English
If you are not comfortable in English, please do not take a course, captions are not good enough to understand the course.
What's inside
Video lectures, PPTs, Demo Resources, Quiz, Assignment, other important links
Full lifetime access with all future updates
Certificate of course completion
30-Day Money-Back Guarantee
Some students Feedback
One of the most amazing courses i have ever taken on Udemy. Please don't hesitate to take this course. The instructor is really professional and has a great experience about the subject of the course. - Khadija Badary
Very nicely explained most of the concepts. a must have course for beginners - Manoranjan Swain
I appreciate this course explaining everything in great detail for a beginner. This will assist me in overcoming challenges at my work - Benjamin Curtis
Good course for Beginners. Labs are really helpful to grasp the concept. Thank you - Sapna
Who this course is for:
- Anyone interested in Azure’s big data analytics services
- Microsoft Azure Data Engineers
- Database and BI developers
- Database Administrators
- Data Analyst or similar profiles
Instructor
![Eshant Garg](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.6 Instructor Rating
- 6,355 Reviews
- 39,970 Students
- 12 Courses
13 years of extensive professional experience with expertise in Microsoft Database and Business Intelligence Solutions, Advanced Analytics, Reporting and Azure cloud computing technologies
CERTIFICATIONS
- DP-200: Implementing an Azure Data Solution
- DP-201: Designing an Azure Data Solution
- Microsoft Certified Technology specialist (MCTS) – SQL Server Database development
- Information Technology Infrastructure Library (ITIL V3) Certified
SPECIALITY
Azure : Data Lake, Data Factory, Synapse Analytics (DW), PolyBase, Stream Analytics & Storage
Big Data Tech : HDInsgiht, Databricks, CosmosDB, Hadoop, Spark, PySpark, Hive, Sqoop
Database versions : Microsoft SQL Server 2005-2016, NoSQL
Languages : T-SQL, USQL, Python, MDX, DAX, PySpark
BI Tools : SSRS, SSIS, SSAS, Power BI
I have been messing around with data for more than a decade now, I love to work on Database internals, performance tuning, and optimization, Database design, modeling, and implementation especially using Microsoft SQL Server and Azure database and analytics technologies.
As a developer and architect, I have worked closely with customers, users, and colleagues to support business solutions across a variety of industries including healthcare, insurance, finance, and government ranging from small companies to fortune 500 companies. These experiences provided opportunities to see varied implementations, troubleshoot performance-related problems, give guidance on design, and provide consultation on optimization, availability, and recoverability.
I helped in End to End Implementations of many database projects, providing team leadership and project management, requirements gathering, specification documentation, functional/technical design, Data modeling & solution architecture.
Outside of the technical world, I love yoga and meditation. I am a student of ancient yogic text Bhagavad Gita and love to discuss and practice philosophical teachings.