June 18, 2021 4:49 am
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Microsoft launches Azure Databricks, AI tools for developers

Microsoft has launched a new data platform technologies and cross-platform developer tools aimed increasing developers’ productivity and simplify app development

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Global technology giant Microsoft has announced new data platform technologies and cross-platform developer tools aimed increasing the developers’ productivity and simplify app development. The company launched a new AI-powered platform “Azure Databricks” during an event for developers.

Designed in collaboration with the founders of Apache Spark, Databricks analytics platform delivers one-click setup, streamlined workflows and an interactive workspace. The platform will enable organisations to provide self-service analytics and machine learning over all data with enterprise-grade performance and governance, Microsoft said in a statement.

“With today’s intelligent cloud, emerging technologies like Artificial Intelligence (AI) have the potential to change every facet of how we interact with the world,” said Scott Guthrie, Executive Vice President in a statement.

“Developers are in the forefront of shaping that potential. We’re announcing new tools and services that help developers build applications and services for the AI-driven future, using the platforms, languages and collaboration tools they already know and love,” he added.

Microsoft is releasing tools designed to help developers, development teams and data scientists collaborate and work together more efficiently for application development, deployment and management.

The company announced the general availability of a “Visual Studio App Centre”. Developers can use App Centre to increase productivity and accelerate application lifecycle, freeing them to spend more time on new features and better user experiences. Developers and data scientists can also develop AI models with all the productivity of Visual Studio, on frameworks and languages. Microsoft also announced “Azure IoT Edge” that will enable AI, advanced analytics and machine learning for the Internet of Things (IoT) powered devices.

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