xREL.v3

.:PROUDLY PRESENTS:.
Cloud Academy Introduction to Azure Data Lake Store and Analytics
Release Date.: 06-09-2019
Type.: Bookware
Disks.: 33x15mb
Link.: https://cloudacademy.com

Release Notes

Course Description
Azure Data Lake Store (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.
ADLS is designed for big data analytics in a Hadoop
environment. It is compatible with Hadoop Distributed File
System (HDFS), so you can run your existing Hadoop jobs by
simply telling them to use your Azure data lake as the filesystem.
Alternatively, you can use Azure Data Lake Analytics (ADLA)
to do your big data processing tasks. It's a service that
automatically provisions resources to run processing jobs.
You don't have to figure out how big to make a cluster or
remember to tear down the cluster when a job is finished.
ADLA will take care of all of that for you. It is also
simpler to use than Hadoop MapReduce, since it includes a
language called U-SQL that brings together the benefits of
SQL and C#.
In this course, you will follow hands-on examples to import
data into ADLS, then secure, process, and export it.
Finally, you will learn how to troubleshoot processing jobs
and optimize I/O.
Learning Objectives

Get data into and out of ADL Store
Use the five layers of security to protect data in ADL Store
Use ADL Analytics to process data in a data lake
Troubleshoot errors in ADL Analytics jobs

Intended Audience

Anyone interested in Azure's big data analytics services

Prerequisites

Database experience
SQL experience (recommended)
Microsoft Azure account recommended (sign up for free trial
at https://azure.microsoft.com/free if you don't have an account)
This Course Includes

37 minutes of high-definition video
Many hands-on demos

Resources
The github repository for this course is at
https://github.com/cloudacademy/azure-data-lake.

Greetings fly out to:

Kodemusen, KoseBamsen

STM is back.
For all the ppl we worked with
in the past. We salute you.

NFO by NiMiTech
Updated: 09/09/2002