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The Sustainable Development Goals (SDGs) will be powered up by Big Data analysis!

To completely implement and analyze progress on Sustainable Development Goals, decision makers require a lot of information and statistics which are perfect, timely, adequately disaggregated, applicable, accessible as well as pretty easy to use. Data accessibility and quality have gradually enhanced over the period of time. Though, statistical volume still requires solidification, and when it comes to data literacy, it has to be evolved at every level of the decision making process. This will need a lot of organized efforts on the part of data creators and users from numerous data solutions. It will also require a host of innovative techniques to produce and implement the data and statistics while addressing the multi-layered obstacles of sustainable development.


The UN Global Goals. Source: United Nations

With a host of SDG indicators to review, Big Data can easily supplement customary data sources in order to keep a better track of the development plans. The Sustainable Development Goals basically provide particular, time-bound, and computable objectives in collaboration with the national development strategies as well as the priorities. Though, with more than 230 SDG indicator; a plenty of which need proper disaggregation by various parameters like location, gender, income, age, and a host of other appropriate dimensions—gathering the required granular data in order to review all SDGs as well as their objectives is not at all an easy feat for the existing national statistical systems (NSS).

In order to understand the level of capability of the national statistical systems specifically for the SDG era, The United Nations Economic and Social Commission takes into account the 22 nations’ experience in disseminating the SDG indicators as well as using a host of different varieties of data sources.

The national statistical organizations recently reported that disaggregation of the stats by location for a plenty of different SDG indicators. Although, the disaggregation is pretty scant for a few of the SDG indicators. However, it is all the more thinner when it comes to specifically the disabled population as well as the indigenous peoples.

Now, most of the NSOs have happily acknowledged that the one and only technique through which they will be able to fulfill SDGs’ disaggregated data needs is to make good use of the innovative procedures and data sources.

A plenty of governmental bodies are already using small area estimation (SAE) techniques which ae aimed to enhance the direct survey approximations particularly small areas (or tiny sub-populations) with supplementary data inputs like the census records). SAE methods help to attain more granular information on poverty or nutrition.

Some of the popular NSOs also informed about their existing levels of access to inflight photos/satellite images, phone data, web-scraped online costs data as well as the social media data. A plenty of the respondents see Big Data as a fruitful new way to address the not so happening data gaps for SDGs. However, just a few very less number have Big Data projects at the moment.

Big Data gathered from a host of search engines, electronic gadgets, social media, as well as from a variety of sensors tracking gadgets and satellite images now offer a novel information source to the NSSs, which includes 3 Vs volume, velocity, as well as variety. And, this beautifully supports the statistics which are gathered from the traditional sources. Big Data is presently being progressively explored for several different types of development purposes.

Large number of the respondents see For example, in Jakarta, Twitter interactions on the cost of rice have offered a ground-breaking way to review the actual costs. In Philippines, World Bank is working in collaboration with the ride-hailing service supplier in order to launch Open Traffic Initiative. They are presently using the company’s driver data in order to get almost real-time traffic information and related statistics, like flow, speed, as well as information about the delays at intersections. This information will help to study critical parts of traffic management.

The United Nations Statistics Division has already developed a thorough record of Big Data projects. And this inventory contains both previous as well as the existing undertakings based on the making use of scanner information from the supermarket chains as well as other retailers. It also includes information about the online prices attained from web-scraping. This is used to generate price catalogues in many countries.

Big Data as a very fresh and innovative way to fill in the present data gaps for SDGs. It just that we have to expand its usage. More and more projects have to start using the power of Big Data analytics Solutions in India as well.

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