Presented by:

As a Senior Program Manager on Azure Data at Microsoft, Rony is responsible for building the next generation of Big Data products for enterprise customers. Rony’s main focus area is designing and developing experiences to make it seamless for enterprise customers to run Big Data and Advanced analytics workload anywhere. Rony has a PhD in Computer Science and has several research papers published in IEEE/ACM, Springer book chapters and journal publications. His PhD Thesis was on " Stock Prediction Analyzing Investor Sentiments".

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Azure Data Studio is a cross-platform database tool for data professionals using the Microsoft family of on-premises and cloud data platforms on Windows, MacOS, and Linux. We have introduced support for PostgreSQL database in Azure Data Studio to support your database development in modern editor experience with Intellisense, code snippets, source control integration, and an integrated terminal. It is engineered with the data platform user in mind, with built in charting of query result sets and customizable dashboards. The Azure Data Studio extension for PostgreSQL is backed up with a Tools API service that provides data management and high performant query execution capabilities.

Azure Data Studio also offers a modern, keyboard-focused PostgreSQL coding experience that makes your everyday tasks easier with built-in features, such as multiple tab windows, a rich SQL editor, IntelliSense, keyword completion, code snippets, code navigation, and source control integration (Git). Run on-demand SQL queries, view and save results as text, JSON, or Excel. Edit data, organize your favorite database connections, and browse database objects in a familiar object browsing experience.

Azure Data Studio also offers a rich Notebook experience with backend Jupyter for local Python development which would allow PostgreSQL developers to run their Machine Learning based workloads using Python and Machine Learning Packages.

Date:
2019 March 22 13:00
Duration:
50 min
Room:
Riverside Ballroom
Conference:
Postgres Conference
Language:
Track:
Data
Difficulty:
Easy