Posted: 27 Sep. 2022

Big data, big environmental impact?

Data-based insights can be a force for good, if treated with care

The good news is that big data is showing the world how our actions are causing environmental harm. This opens up opportunities to make more sustainable choices, and even reverse the damage. The bad news? Handling that data requires a staggering amount of energy. 

Some people call data the new oil. It’s certainly a valuable commodity, being traded by companies to feed AI algorithms. Some of the data we willingly give up, and some of it’s ‘data exhaust’ – acquired passively as we interact with digital products or services1.  Collectively, it’s all ‘big data’. And, like oil, it’s mined and processed at a cost to the earth. 

Before we get into the damage, let’s shine a spotlight on how big data can actually help our environment. The patterns the data yields provide insights, which can be used to encourage environmentally sustainable behaviour. Or they might show how we, or our machines, are causing harm: leaking toxins, expending extra energy, wasting water, etc.  

So companies can actually use big data as a tool to become more sustainable, by looking at how people interact with the world around them, and spot opportunities to improve. You’re probably familiar with the UN’s Sustainable Development Goals; the UN acknowledges that big data can play a factor in SDG progress (and so can you)2.   


Admitting the problem

Of course, the very act of using big data causes damage (especially cloud computing)3,  because creating, storing, updating, indexing and copying data all requires resources. It’s been said that if all the data centres in the world were a country, they would be the fifth-largest consumers of energy4.    

What’s more, data that is unintentionally duplicated, incorrect and/or unused also eats up time, money and energy. It’s an issue that should be addressed strategically and operationally. As a responsible big data user, your critical task is to have a well-thought-out strategy to analyse and use the data.  


Operational and strategic mindset 

If your business goals aren’t appropriately and clearly linked to the data, someone will spend a lot of unnecessary energy (human and electric) wading through useless data that will produce incorrect analyses. If your strategy leads you to realise certain data should be migrated, take extra care to preserve the data quality; migration can mutate data fields.  

After you have a data strategy in place, there are operational steps you can take to help minimise energy use:  

• Consider the efficiency of your IT systems, if energy prices haven’t already driven you to do so. Collecting and processing information consumes vast amounts of electricity. Initiatives like the Green Big Data Project aim to enhance computing performance while reducing energy waste5.   

• Spare a thought for the energy output of your servers, and whether you can improve it by enlisting a cloud service provider, after you’ve done your ‘housekeeping’.  

• Ensure that the data you store is of the right quality and easily found, for effective and efficient processing. Picture two data sets that include the same information but it’s displayed in different ways, or was entered manually with mistakes (by an employee or a customer). By trying, and failing, to reconcile those sets, incorrect conclusions may easily be drawn…or no conclusions at all. 

When carefully tended to and accompanied by a solid strategy and sensible operational practices, big data can not only produce incredible insights and innovations, it can actually contribute to a more sustainable world. We just need to be mindful of what we process and store, and why.  


Deloitte helps clients form a strategy and design the right operational frameworks to responsibly handle big data. We help address questions like: How much pollution do your systems emit? Is your data of the right quality and does it fit with your analysis strategy? Will your data migration preserve the quality of your data? And how can your data be more accessible, easy to use and complete? 

1 United Nations, “Big data for sustainable development”,, last accessed July 13, 2022. 

2 Ibid. 

3Federica Lucivero, “Big data, big waste? A reflection on the environmental sustainability of big data initiatives”, Science and Engineering Ethics 26, 1009-1030 (2020),,waste%20production%20and%20CO2, last accessed July 13, 2022. 

4Ohad Shalev, “Minimizing the carbon footprint of data analysis, maximizing sustainability for data centers”, VentureBeat, June 4, 2022,, last accessed August 1, 2022. 

5 CERN, “Green Big Data Project”,, last accessed August 17, 2022. 


Eric Onderdelinden

Eric Onderdelinden


I'm a very experienced enterprise architect and lead the Enterprise Architecture offering within the Netherlands. I'm specialized in Enterprise Architecture with a focus on the private sector. Besides in depth knowledge of Industrial processes and products I bring a wealth of experience in data and technology , including cloud services and desired agility, to the table. Recent assignments include pre-merger assessment and post merger integration. I work on project dealing with application portfolio rationalization, business case development and TCO. I publish on a regular basis in IT and business magazines. I support companies worldwide with the establishment and maturing of their EA practice. I'm a teacher in the master class enterprise architecture organized by the NAF. Besides that I'm a memebr of the board for Platfrom Digitale Wendbaarheid. Currently I'm working on a PhD concerning the value contribution of IS in M&A.