Oracle Autonomous Database, the world’s first and only true autonomous database, is at the heart of data management in this programme.
Niti Aayog vice chairperson (Photo: AFP)
Niti Aayog has selected Oracle to help it modernise vital IT infrastructure in 112 most backward districts as part of its Aspirational Districts Programme, the think-tank announced on Thursday.
These 112 districts constitute 28 per cent of country’s population (nearly 1.4 billion). The new cloud solution aims to aid district magistrates to improve overall performance and transform the quality of life of citizens.
“Data-driven decisions will help identify the strengths and weaknesses of these districts and pave the way for their progress. By using a range of Oracle Cloud services, we are looking to fast-track their transformation by providing simplified data access, increased process automation and real-time data governance,” said NITI Aayog CEO Amitabh Kant.
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The programme uses data to identify top performing districts. These could be Dantewada in Chhattisgarh, Nandurbar in Maharashtra, Dahod in Gujarat, Kupwara in Jammu & Kashmir, Vizianagaram in Andhra Pradesh, or Godda in Jharkhand, among others.
The weaker performing districts are encouraged to catch-up with top performers. This is accomplished by competing with, and learning from the top players in the spirit of competitive and cooperative collaboration.
Oracle Autonomous Database, the world’s first and only true autonomous database, is at the heart of data management in this programme. Being self-driving, self-securing and self-repairing it requires a minimal IT team and resources to support it.
“Oracle has committed nearly 30 years in India, serving its people, the government and enterprise firms. With a range of Oracle Cloud services, we look forward to support this programme’s success and facilitate the creation of a new India,” said Shailender Kumar, Regional Managing Director, Oracle India.
Highly secure by nature, the system and the data the Oracle Autonomous Database manages are protected from system failure and attack by machine learning (ML) and automation.
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