Recently, Microsoft has announced a product that seems to blend together to give end-to-end analytics at a very large scale on its cloud platform with Synapse Analytics.
Over the years, we have seen mass migration to the cloud as businesses signed up by the thousands to capture the advantages of flexible, large–scale computing and data storage. But in the last five years or so, what we saw was that the next iteration of that tech revolution, in which companies would use their growing stores of data to get more tangible business insights that had slowed down.
Data is spread across big data lakes, data warehousing, data pipelines and it’s difficult to translate the benefits of data into actionable analytics. Recently, Microsoft has announced a product that seems to blend all of that together to give end-to-end analytics at a very large scale on its cloud platform with Synapse Analytics, which is a rebrand of Azure SQL Data Warehouse — first announced in 2015.
What’s Unique About Azure Synapse Analytics?
Synapse Analytics aims to unify a range of analytics workloads, including data warehouse, data lake, machine learning and data pipelines that act as a bridge between all those things. The core data warehouse engine has been ramped up with novel features to go against other cloud data warehouse platforms directly, including the ability to include workloads through explicitly provisioned or on-demand (serverless) infrastructure, each with its specific pricing model.
The biggest highlight is the integration of Apache Spark, Azure Data Lake Storage and Azure Data Factory with a unified web user interface. The powerful combination of Spark with Azure Data Lake Storage (ADLS) and Azure Data Factory together on the UI, gives users the control over both data warehouse/data lakes and accommodate data preparation and management.
The cloud wars are intensifying on things like big data analytics and BI vendors, which means large vendors are upping their game constantly with new features. It also proves that despite huge acquisitions sprees like Tableau from Salesforce and Looker from Google may not be enough to compete with utility and ease of use as in the case of Synapse. Microsoft proved with the launch that innovative resources with existing products can satisfy customer needs, operationalise analytics more fluidly, and give security and compliance to enterprise users more smoothly.
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Vishal Chawla is a senior tech journalist at Analytics India Magazine and writes about AI, data analytics, cybersecurity, cloud computing, and blockchain. Vishal also hosts AIM's video podcast called Simulated Reality- featuring tech leaders, AI experts, and innovative startups of India.