Explained: Birth of a Data Democracy


Recently, the committee headed by former Infosys vice chairman Kris Gopalakrishnan had submitted its findings and arguing for a separate law to regulate the commercial use of non-personal data.

  • In 2018, an expert group headed by former Supreme Court judge B.N. Srikrishna had similarly argued for legislation to regulate the use of personal information by data-mining companies.
  • A Data Democracy describes a methodological framework of values and actions that benefit and minimize any harm to the public or the typical user.

Need of Data Democracy

  • Protection of data generated by public: The idea behind regulation of personal and non-personal data is the data generated by the public has to be protected.
  • Laws on Data Regulation: The laws provide the legal architecture to protect the data privacy of both an individual and the society as a collective.
  • Increase in Internet Users and Potential market for Data: There is already a third of the population which is using smartphones and has the power of 10x of generating data and this segment will only grow exponentially creating probably the largest market for data in the world.
  • Indians are economically poor but data-rich: An individual’s data in India is far more valuable than their current material worth and this mismatch in potential and reality is what provides an opportunity for an individual to monetize their data.
  • Public and Personal Wealth Creation: The idea of data democracy is that one accorded political power and the other is designed to deliver economic empowerment in which data will be harvested for public and personal wealth creation.

Principles of Data Democracy

  • The average end user can access information in any digital format and data quality is must.
  • The non-specialists should be able to gather and analyze data or engage in self-service without requiring outside help, specifically from IT.
  • The individual private data needs to be protected, as decreed by the General Data Protection Regulation (GDPR).
  • Technologies such as Augmented Analytics, NoSQL, dashboards, and self-service tools, like those created by Collibra, Teradata, and Unilog, play an important part in empowering non-technical people in a Data Democracy.
  • The Data Ethics are required to be followed in order to guide Data Democracies.

Why Data Democratization is crucial for Business?

  • Data democratization is a game changer: Data democratization will catapult companies to new heights of performance as everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data.
  • Faster Decision Making: The ability to instantly access and understand data will translate into faster decision making, and that will translate into more agile teams.
  • Understanding anomalies and Informing Proactively: When things happen in a good or bad sense, and the right people are proactively informed, those people can dig into and understand those anomalies and be proactively informed.
  • Intentionally working on Data Democratization: Businesses that wish to benefit from data democratization will have to create it intentionally which means an organizational investment must be made in terms of budget, software, and training.

Challenges associated with Data Democracy

  • Delay in framing laws for data regulation: While the effort to carve out a law for protecting personal data is a work in progress as it is still making its way through Parliament and the Union government is yet to articulate its view on the findings of the Gopalakrishnan committee.
  • Mismanagement or misinterpretation of data: There is no democracy without checks and balances and mismanagement or misinterpretation of data is a real concern.
  • Although the proposed benefits are real, implementing data democracy involves serious caveats in technology, culture, and business requirements.
  • The core issue is that neither data democracy nor self-service analytics can function entirely without the intervention from Information Technology departments and data scientists.
  • The typical problems include cases where:
    • Users fail to understand the data or analysis
    • Users create unintended technical impediments such as personal data silos
    • Data is not properly governed or secured
    • User-created models are inadequate or incorrect
    • Data scientists must do more work preparing data rather than taking on higher-value tasks

Way Forward

  • Establishing Contactless Infrastructure: Especially in the aftermath of covid-19 and the fillip to contactless behaviour, the building blocks for a scalable model to harvest the mass of data generated as Indians rapidly expand their digital footprint.
  • Individual Consent to mine Data: We tend to view the only use of data to be to fatten the bottom line of platforms such as Google and Facebook which harvest this personal data, mostly without consent and there is urgent need of data protection laws.
  • Fast track the privacy law: The onus is on the politicians to fast track the privacy law protecting and regulating the use of personal and non-personal data.
  • Center of Excellence for management of data: A center of excellence is recommended to keep the use of data on the straight and narrow and it should have a goal to drive adoption of data usage which is made possible by owning data accuracy, curation, sharing, and training.
  • Data democratization is the future of managing big data and realizing its value and businesses armed with the right tools and understanding are succeeding today because they are arming all their employees with the knowledge necessary to make smart decisions and provide better customer experiences.

Source: LiveMint

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