Making Big Data Sustainable – How 4 Different Industries are Using Data to Become More Sustainable 

Did you know more than of the world’s largest publicly traded companies have net zero targets for 2030?  Thanks to the UN’s Sustainable Development Goals, the need to employ more sustainable practices within organizations around the world has grown exponentially in the 2020s. However, due to the varying processes and sustainability needs across different industries, there is a call to take specific approaches to address the unique needs of each. For organizations to hit a net zero goal by 2050, all industries must commit to sustainability practices – starting with the data. 

Why is Big Data Not Traditionally Sustainable?

Traditional data practices often involve large data centers that consume enormous amounts of energy for storage, processing, and cooling. The carbon footprint of these operations is substantial.

Recently, the International Energy Agency (IEA) released its energy forecast for 2024 with the notable inclusion of the consumption required for data centers running for applications such as AI and cryptocurrency. They found that the energy needed to support the increased demand for data storage is expected to double by 2026, and AI uses as much energy as the entire country of Japan.

Furthermore, the rapid turnover of electronic devices used for data collection and processing contributes to electronic waste, further straining the environment.

This increase in consumption is a worrying reality of the near future of human technology, forcing industries to reevaluate their operations sooner rather than later.

How Big Data is Collected Across Different Industries


In agriculture, data collection surrounds precision farming techniques such as GPS-guided tractors and sensors to monitor soil health. Drones equipped with imaging technology are also used to gather data on crop conditions. 


The fishing industry relies on data from satellite tracking systems, sonar technology, and underwater cameras to monitor fish stocks and optimize fishing practices. 


In the energy sector, data is collected through sensors in power grids, monitoring equipment in renewable energy installations, and geological surveys for fossil fuel exploration. However, the high energy demand of data centers and the carbon footprint associated with fossil fuel extraction make traditional data practices in the energy industry less sustainable.

Consumer Packaged Goods (CPG)

In the CPG industry, data is collected through various means, including customer transactions, supply chain monitoring, and market research. The extensive use of packaging materials and the energy-intensive nature of production processes contribute to the industry’s environmental impact.

Methods for More Sustainable Big Data Practices

1. Renewable Energy for Data Centers:

Transitioning data centers to run on renewable energy sources, such as solar or wind power, can significantly reduce the environmental impact of data processing. Companies can also explore decentralized and edge computing, distributing computing resources closer to the source of data to minimize energy loss during transmission.

2. Edge Computing:

Utilizing edge computing can reduce the need for centralized data processing, enabling real-time data analysis closer to the point of data generation. This not only enhances efficiency but also lowers energy consumption by eliminating the need for extensive data transmission.

3. Sustainable Hardware Practices:

Embracing sustainable hardware practices, such as designing energy-efficient processors and using recycled materials in device manufacturing, can contribute to reducing the overall environmental impact of data collection devices.

4. Circular Economy Approaches:

Implementing circular economy principles involves extending the lifecycle of electronic devices through repair, refurbishment, and recycling. This reduces electronic waste and minimizes the environmental impact associated with the production and disposal of devices used for data collection.

Examples of Data-Driven Sustainability Initiatives Across Different Industries 

Agriculture – Climate Smart Agriculture 

A project led by the Food and Agriculture Organization (FAO) of the United Nations, this initiative helps optimize the crops during the different seasons of the year. Their approach is implemented through five action points: expanding the database with accurate data, supporting governance frameworks with real-time insights, strengthening national/local institutions, enhancing financing, and implementation. 

Fishing – Global Fishing Watch 

The Global Fishing Watch records the movement of vessels and fishing activity to create a map that helps prevent illegal fishing. The purpose is to use technology such as satellite imaging and machine learning to turn big data into actionable information and publicly share this knowledge to hold humans accountable for sustainable fishing practices. 

Energy – Nighttime Lights 

In a collaboration between the World Bank and the University of Michigan, they compared over 6 billion data points extracted from satellite imagery of nighttime light data across 600k villages in India over the span of 20 years. This was then turned into accessible data visualizations to aid citizens, governments, and investors in gaining actionable insights into the impact of electrification projects. 

CPG – Sustainable Packaging Coalition 

SPC is a collaborative network that works towards creating sustainable packaging by bringing stakeholders together to catalyze actionable improvements in the packing industry. They do this through 4 pillars: optimizing, innovation through technology, informed governance and policy, enhanced recycling technology (i.e. through AI), and sustainable packaging design strategy. 


By adopting more sustainable data acquisition practices and harnessing the power of analytics, organizations can not only mitigate the environmental impact of data operations but also drive positive change across varying sectors.

The journey towards sustainable big data is a collective effort that involves technological innovation, industry collaboration, and a commitment to a greener future.

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