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Relevance and use of the article in UPSC prelims and mains examination: Dear aspirants to sum up this article we need to learn about government's digital india campaign and necessities for its success, technology itself is not complete unless the governance support it. please go through the article and find out that Prerequisite for Success of Digital India and that lies in well-managed data system surely that prove useful in unlocking new sources of economic estimates, fresh understanding into science and holding governments accountable.

The issue :

  • As technology becomes more accessible and cheaper, the data it generates is increasing in size more rapidly than ever before. While computing devices are getting smaller, data is getting bigger every day.
  • Both, enterprises and governments, are facing challenges to effectively manage the data. Data is produced each time a person uses bandwidth regular databases may not be sufficient for handling this load.
  • We need databases that are powerful enough to not only store data, but also be able to provide a platform for data analytics, quick user queries and security. This is where technology, like Very Large Databases or VLDBs, come into play. VLDBs are databases large enough to hold data ranging in terabytes, or even petabytes.

What is digital india campaign:

  • Digital India is a campaign launched by the Government of India to ensure that Government services are made available to citizens electronically by improving online infrastructure and by increasing Internet connectivity or by making the country digitally empowered in the field of technology and it is a collective effort of the Indian government to connect the diverse rural communities to the internet and provide them free access to basic online services.

What is Very Large Databases or VLDBs :

  • The most common definition of VLDB is a database that occupies more than 1 terabyte or contains several billion rows, although naturally this definition changes over time. Very large databases are often, but not necessarily, a core component in big data analysis.

Digital India and VLDB:

  • VLDB: is a necessary requirement for Success of Digital India, well-managed data can prove useful in unlocking new sources of economic estimates, fresh understanding into science and holding governments accountable.
  • Digital India programme, aims to connect every citizen of India using technology. It comes with its fair share of challenges, one of which is the amount of data that will be generated due to the numerous services entailed in it.

Services which can be improved by big data

  • Services like e-healthcare solutions, the Khoya Paya portal for lost and found children, Massive Open Online Courses (MOOCs), etc., will especially face a major challenge in terms of the amount of data they will be handling regularly.
  • These services will require Very Large Databases to contain their data. VLDB will provide the services a single source to store all their scattered data. But having a large enough database will not be a complete solution; accessing that data at high speeds, maintaining data confidentiality, integrity and availability will be equally important.

Challenges associated with digital india campaign while implementing big data :

  • ? The primary challenge Digital India services will face when incorporating VLDB into their systems
  • ? These are namely growing data volumes, maintaining data access speeds despite the increasing size of the database, ensuring data duplication is avoided to efficiently use the space in the database, efficiently managing data access permissions and ensuring data confidentiality and integrity. Special methods or techniques have to be developed to deal with each of the above mentioned challenges for VLDBs.
  • ? With multiple services being interlinked in the Digital India programme, a major concern would be the duplication of data within the same or across multiple databases.At the same time, it will be extremely necessary that data concurrency is maintained across these databases to ensure unhindered usage of each service.
  • ? Securing data against malicious users will be another very essential area to work upon.
  • Data classification and security policies should be defined and implemented.
  • ? Regular security testing of the databases and underlying infrastructure to ascertain vulnerabilities should be performed.
  • ? Suitable encryption techniques should be used to protect the confidentiality of information.
  • ? Solutions like database activity monitoring should be deployed for continuous monitoring for security issues.
  • ? Adequate data backup and restoration policies are defined and enforced in these systems.
  • ? Data access policies and processes should be defined as guiding principles for access management.
  • ? For critical data access, additional authentication mechanism such as multi-factor and biometric technique should be considered.

Conclusion :

  • Organisations have adopted VLDBs to effectively manage the large and heterogeneous data and are reaping its benefits. Due to the sheer complexity of the Digital India programme and the enormity of data it will produce, government organisations and departments may consider employing VLDB.
  • Digital India programme also need application of data science to build predictive and detective models for service efficiency and proactive decision making to bring in efficiency in services and improve citizen experience.


As technology becomes more accessible and cheaper, the data it generates is increasing in size more rapidly than ever before.discuss about this challenge in context of Digital India your Views that how VLDB(Very Large Databases) is can be used to overcome this problem?

(250 Words)

Suggested points :

  • Role of Information technology in today's life
  • Massive use of data.
  • Discuss about Digital india campaign and it's aims.
  • Challenges before this campaign.
  • Glimpse of VLDB.
  • How it can be administered in Digital india campaign.
  • Conclusion with suitable examples.


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Read 422 times Last modified on Thursday, 13 October 2016 11:10

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