Microsoft is announcing Azure Synapse Analytics, a new analytics service that brings together enterprise data warehousing and Big Data analytics.

A statement explained that it uses either serverless on-demand or provisioned resources, at scale, to ingest, prepare, manage, and serve data for business intelligence and machine learning needs.

Azure Synapse is essentially the next evolution of the existing Azure SQL Data Warehouse, claiming to be the first and only analytics system to have run all TPC-H queries - a decision support benchmark - at petabyte-scale.

Businesses can continue running existing data warehouse workloads in production with Azure Synapse, automatically benefitting from the new capabilities which are in preview. Azure Synapse will also offer an ecosystem of partners like Databricks, Informatica, Accenture, Talend, Attunity, Pragmatic Works and Adatis.

Data professionals can query both relational and non-relational data using the familiar SQL language, while for mission-critical workloads, they can easily optimise the performance of all queries with intelligent workload management, workload isolation and limitless concurrency.

It is also integrated with Power BI and Azure Machine Learning to expand the discovery of insights from data and apply machine learning models to apps.

Data engineers can use a code-free visual environment for managing data pipelines, while Microsoft also promised that data scientists can build proofs of concept in minutes and business analysts can securely access datasets and use Power BI to build dashboards, all while using the same analytics service.

In terms of security, Azure Synapse has automated threat detection and always-on data encryption. “And for fine-grained access control, businesses can help ensure data stays safe and private using column-level security and native row-level security, as well as dynamic data masking to automatically protect sensitive data in real-time,” read the statement.

Rohan Kumar corporate vice president at Azure Data, explained: “Today, businesses are forced to maintain two types of analytical systems, data warehouses and data lakes – data warehouses provide critical insights on business health, while data lakes can uncover important signals on customers, products, employees and processes.

“Both are critical, yet operate independently of one another, which can lead to uninformed decisions – at the same time, businesses need to unlock insights from all their data to stay competitive and fuel innovation with purpose,” he added.

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