Big Data & the Sustainable Development Goals: Measuring & Achieving Development Progress in the Big Data Era

Name: Pornthiya Tungkijrat (唐夕雅) 
Student ID: M0869827 

The Sustainable Development Goals (SDGs) outline explicit, time-bound, and measurable targets for national development plans in sync with global concerns for climate security, equality, and development. With 169 multi-dimensional targets to be achieved by 2030, this ambitious program requires 232 statistical indicators or performance metrics from every country to monitor progress towards the SDGs.

Although this data collecting and storing capacity opens up incredible opportunities for monitoring, analyzing, and addressing inequality and under-development, the collection of granular data of developing economies by the National Statistical Systems is a difficult feat and spells trouble for the adequate implementation of the SDGs. There is still a systemic lag in the availability, access, and usability of this critical data for the countries most in need.
The United Nations has taken steps to better realize the opportunities presented by big data for the “global collective” while remaining in line with privacy concerns, ethics, and state sovereignty.

Big Problems 

With many developing countries having limited resources and under-developed data collection systems to compile basic socio-economic statistics, the key issue is whether the SDGs and the production of new indicators are realistic and attainable globally. Data is critical for global, regional, and national policymaking, and without access to raw material, accountability for national development, and a genuine effort to meet SDGs is questionable.

In many countries facing the worst inequality indicators, including many nations in South East Asia, downstream data needs are fundamentally neglected. Additionally, for developed countries, although national interest and ownership are mentioned, the national collection of data and the degree of data sharing is ignored. Rather, a general encouragement of openness defines the SDGs.  In this way, there is a high risk of inequality and bias, with concerning gaps between the data haves and have-nots already expanding. Factors such as language, poverty, lack of education and technology infrastructure are all goals to be addressed by the SDGs but are contributing issues crippling the use of big data to achieve such goals.


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