Azure Synapse Analytics is a single resolution for all information wants like ingesting, processing, and serving the info. It delivers the unified expertise of information integration, information warehousing, and massive information analytics in a single workspace surroundings. Azure Synapse analytics could be simply built-in with different providers supplied by Azure like Azure Machine Studying, CosmosDB, and PowerBI. Microsoft rebranded SQL Information Warehousing into Azure Synapse Analytics with many new functionalities and options other than integrating a lot of the providers into it.
Earlier than Azure Synapse Analytics, there have been a number of instruments that have to be used for large information processing within the Azure cloud. A few of them are listed under which wants individually labored upon step-by-step to get the specified consequence.
- Azure information manufacturing facility
- Azure information lake
- Azure databricks
- SQL information warehousing
- PowerBI
After the introduction of azure synapse analytics, you’ll be able to carry out all these in a single service. All you want is to create an azure information lake storage after which create an azure synapse analytics workspace on high of it to get began together with your ETL operations, Large information processing, and PowerBI reporting integration -yes, PowerBI could be straight related to synapse analytics to generate reviews.
The primary benefit in synapse over different particular person providers is the liberty to question information by yourself phrases utilizing serverless or devoted sources at scale.
It brings collectively the three major parts beneath a single entity…
- SQL expertise utilized in information warehousing as synapse SQL
- Apache spark processing
- ADF pipelines for ETL/ELT as synapse pipelines
The above picture explains the most effective on what are the instruments that have to be handled large information processing earlier and the way azure synapse analytics simplified the whole ecosystem now.
As with every different azure information service, Microsoft gives us with a wealthy UI to work on known as azure synapse studio. Utilizing this not solely can create pipelines but in addition, we are able to use it to handle, monitor, and safe all our workflows. At the moment, Azure Synapse presents two analytics runtimes specifically SQL and Apache spark which we are able to use as per our wants. The DataLake storage that synapse can join straight is Azure DataLake gen2 other than this it helps 90+ information sources to ingest from.
Abstract
It is a primer or beginning step to know what azure synapse analytics is. I’ve deliberate a sequence of blogs on learn how to implement a synapse analytics mission in real-time with the demo.
Reference
Microsoft official docs
