The Use of Big Data in Achieving Sustainable Development Goals

Big data is everywhere, and all sorts of businesses, non-profits, governments and other groups use it to improve their understanding of certain topics and improve their practices. Big data is quite a buzzword, but its definition is relatively straightforward — it refers to any data that is high-volume, gets collected frequently or covers a wide variety of topics. If you want to learn big data and data science then you can take data science courses that are offered by Intellipaat.

This kind of data when organized and analyzed adequately can be quite valuable. Marketing teams use it to learn more about their customer base, healthcare professionals can use it to calculate someone’s chance of contracting a disease like Covid-19, and cities can use it to optimize traffic flow, and it can also help in saving wildlife.

Big data also has the potential to help significantly improve the quality of life for much of the world’s population. The United Nations, governments, not-for-profits and other groups are using big data to help achieve the UN’s sustainable development goals or SDGs — a set of 17 targets related to protecting the natural environment, reducing inequality, improving health outcomes and other things that will make life better around the world.

How Can We Use Big Data to Achieve SDGs?

There are many ways in which we could use data to improve our understanding of our progress towards the SDGs, determine how best to meet those targets and ensure accountability. The United Nations has set up a task team to explore how to use big data to help achieve the SDGs. A survey by the task team found that big data projects most frequently focused on the “no poverty” goal and that mobile phone data was the most common data source.

Pulse Lab Jakarta, a joint effort between the United Nations and the government of Indonesia, is working on various big data projects related to the SDGs. One of their projects is the Vulnerability Analysis Monitoring Platform for Impact of Regional Events (VAMPIRE) platform, which analyzes satellite imagery and creates maps that incorporate anomalies related to climate and rainfall to help track slow-onset climate changes.

Another project, the Manitoba Bioeconomy Atlas, comes from the International Institute for Sustainable Development and involves that creation of a web-based spatial inventory of biomass sources. Biomass producers can use the data to optimally locate biomass refineries, and biomass consumers can use it to source biomass and calculate costs.

There are many other potential uses for big data related to the SDGs. Mobile phone data, for instance, could be used to track the movement of populations, such as refugees, to improve preparations. Data analysis could help predict changes in food prices. The possibilities are virtually endless.

What Are the Challenges and Risks?

The opportunities related to big data are plentiful, but there are also numerous challenges and risks. Collecting, storing and analyzing large amounts of data is in itself challenging. It requires advanced technology and infrastructure, which can be expensive. This limits the access of less developed countries to this technology. In the survey by the UN’s bid data task team, the team received much higher response rates from high-income countries than lower-income ones.

Privacy is another significant concern. It’s essential that those processing respect the rights of those they collect data from. The fact that much data is collected passively can complicate this. Even removing sensitive information from data sets may not always be enough to guarantee privacy, since people could be identified by combining information from multiple data sets. Those handling personal data need to take steps to protect subjects’ privacy.

The UN, through several of its groups, has issued recommendations and guidelines for the use of big data related to SDGs. Among the goals of these guidelines is ensuring privacy and increasing access to data worldwide. The private and public sectors, as well as countries and organizations from around the world, will have to work together to accomplish the UN’s SDGs and to ensure that we can take full advantage of the benefits big data and machine learning can provide related to achieving them.