# load python
library(reticulate)
use_python('C:/Users/Andrew/Anaconda3/')
use_condaenv(condaenv='my_ml', required=TRUE)
library(knitr)

Introduction

Azure Synapse Analytics is a limitless analytics service that brings together data integration, enterprise data warehousing, and big data analytics. It gives you the freedom to query data on your terms, using either serverless or dedicated resources—at scale. Azure Synapse brings these worlds together with a unified experience to ingest, explore, prepare, manage, and serve data for immediate BI and machine learning needs.

In this demo, we will walk through the necessary procedures to:

Create an Azure Synapse Environment

In order to create an Azure Synapse environment, several preparatory objects are needed:

In the image below, we create the Synapse workspace, storage account, and file system name in one single effort.

Initiate Azure Synapse Analytics

We can now launch Azure Synapse Analytics, which looks like the below image: