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Data Analytics Product Carbon Footprint

Sweeft DAPCF - Assessing the Carbon Footprint of Data Analytics Products
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The rapid escalation of data analytics in driving organizational decision-making processes underscores the urgency to evaluate its environmental impact, particularly the carbon footprint associated with Data Analytics Products (DAPs). This study introduces a novel methodology for calculating the Data Analytics Product Carbon Footprint (DAPCF), encompassing cloud operations, data transfer, and embodied emissions. Leveraging insights from the Software Carbon Intensity (SCI) specification, this framework aims to provide a holistic view of the carbon emissions from DAPs. By dissecting the components of DAPCF and applying them to a case study, this paper elucidates the pathways through which organizations can mitigate their digital environmental footprint, aligning ICT practices with global sustainability goals.


The Information and Communications Technology (ICT) sector stands at the crossroads of innovation and environmental responsibility. As data becomes the linchpin of operational efficiency and strategic insight, Data Analytics Products (DAPs) have emerged as critical tools in harnessing this potential. However, the environmental ramifications of these technologies, particularly their carbon footprint, remain an area of significant concern and under-examination.


The urgency to address the carbon footprint of ICT operations has been underscored by the growing body of research highlighting the sector's substantial contribution to global greenhouse gas (GHG) emissions. With studies suggesting ICT could account for up to 14% of global emissions by 2040, the sustainability of digital operations has come under scrutiny. Data analytics, with its intensive data processing and storage requirements, but also the data transfer to devices is particularly impactful. These operations, primarily hosted in cloud environments, demand considerable energy resources, contributing to the carbon footprint of digital products.


The Software Carbon Intensity (SCI) specification, developed by the Green Software Foundation, offers a pioneering approach to calculating and reducing the carbon emissions of software systems. By focusing on operational emissions, embodied emissions, and energy efficiency, the SCI provides a comprehensive framework for understanding and mitigating the environmental impact of software operations. However, the application of SCI principles to the specific context of DAPs necessitates a tailored methodology that accounts for the unique characteristics of these products.


This study aims to bridge this gap by proposing a detailed methodology for assessing the Data Analytics Product Carbon Footprint (DAPCF). Drawing on the principles outlined in the SCI specification, this methodology extends the focus to encompass the entirety of a DAP's lifecycle — from cloud operations and data transfer to the embodied emissions of end-user devices. This approach not only aligns with the SCI's emphasis on comprehensive emissions assessment but also addresses the need for sector-specific methodologies capable of guiding sustainability efforts within the realm of data analytics.


In developing the DAPCF methodology, this study contributes to a deeper understanding of the environmental impact of data analytics. By delineating the components of DAPCF and illustrating their application through a case study, we highlight the potential for significant emissions reduction. Furthermore, this methodology serves as a foundation for organizations seeking to align their data analytics practices with broader sustainability goals, offering a path toward more environmentally responsible ICT operations.

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Guest
Mar 05
Rated 5 out of 5 stars.

Eye opening :)

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Guest
Feb 19
Rated 5 out of 5 stars.

What an interesting reading... keep it up!

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Guest
Feb 18
Rated 5 out of 5 stars.

Insightful

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