Data & Analytics

Data and analytics are increasingly recognized as fundamental elements in achieving the Sustainable Development Goals (SDGs). These 17 goals, adopted by the United Nations in 2015, aim to address global challenges such as poverty, inequality, climate change, environmental degradation, peace, and justice. Each goal is interconnected, requiring a holistic approach to achieve sustainable development by 2030. Within this framework, SDG 17, "Partnerships for the Goals," is particularly crucial as it highlights the need for high-quality, timely, and reliable data to drive progress across all goals.

The importance of data and analytics in realizing the SDGs cannot be overstated. Accurate and insightful data is necessary for several key aspects: assessing current progress, identifying existing gaps, informing policy-making, and guiding the allocation of resources. For instance, in addressing SDG 1, "No Poverty," data helps in understanding the demographics of poverty, allowing for targeted interventions. Similarly, for SDG 3, "Good Health and Well-being," data analytics play a crucial role in tracking disease outbreaks, understanding health trends, and improving healthcare delivery.

In the education sector, under SDG 4, "Quality Education," data can inform about areas where educational resources are lacking or where dropout rates are high, guiding efforts to enhance education systems. Additionally, for SDG 13, "Climate Action," data is indispensable for understanding climate patterns, predicting future scenarios, and formulating strategies to mitigate and adapt to climate change.

Advancements in data collection and analytics methods have opened up new possibilities. Mobile technology, for example, has revolutionized data collection, enabling real-time gathering and dissemination of information even in remote areas. Remote sensing technologies, such as satellite imagery, provide critical data on environmental changes, agricultural patterns, and urban development. These methods not only expand the scope of data collection but also enhance its accuracy and timeliness.

However, challenges remain in harnessing the full potential of data for the SDGs. These include issues related to data availability, quality, accessibility, and interoperability. In many parts of the world, especially in developing countries, there is a significant data deficit. This gap hinders the ability to make informed decisions and effectively address the SDGs. Moreover, data collected must be reliable and relevant to be useful in policy formulation and implementation.

To overcome these challenges, partnerships between governments, private sector, academia, and civil society are vital. These collaborations can foster innovation in data collection and analytics, ensure data sharing, and build capacities for data analysis. Furthermore, there is a need for a global framework to standardize data collection and reporting methods, which will facilitate comparison and aggregation of data across regions and countries.

Front cover of Emerald Sky flight emissions report

Cirium has released the Flight Emissions Review, the official airline report giving stakeholders across the aviation sector an accurate, transparent, data-backed view of emissions performance.  The emissions calculation is built on the most accurate calculations available and its methodology is certified to ISAE 3000 with Reasonable Assurance.

The review includes

Big data shows significant potential for deep decarbonization in the transportation sector, while advances in artificial intelligence (AI) technologies help extracting valuable knowledge from such data. This study reviews the applications of big data and AI technologies in transportation, encompassing data accumulation, pattern understanding, and uncovering the intricate nexus between transportation activities and carbon emissions, ultimately providing insights for achieving carbon neutrality.
This piece demonstrates the extent to which switching to clean electricity can create co-benefits for climate and human health. Right timing given Trump's love of coal.
The model detailed in this article can be used to compute the climate effects of global aviation emissions under different conditions and provide the methodological guidance for researchers to analyze the effects of different climate change control measures.

This article presents a few-shot learning strategy using large language models (LLMs) to develop 2D geological cross-sections from sparse site investigation data.

Elsevier,

Geodata and AI, Volume 1, September 2024, 100004

This article provides a comprehensive review of differential privacy (DP) and its applications in geotechnical engineering

Elsevier,

Digital Chemical Engineering, Volume 14, March 2025, 100217

This research introduces APAH, an innovative IoT-based autonomous real-time monitoring system designed for industrial wastewater management, particularly in developing countries like India. By integrating multi-parameter sensors and advanced technologies such as machine learning, APAH continuously tracks key water quality metrics and enables timely interventions through automated controls and alerts, demonstrating significant improvements in water quality at industrial treatment plants in Maharashtra.

This article maps out the magnitude of conflicts between land use and renewable energy.
This paper supports SDG 3 with evidence of disparate effects of phased COVID-19 vaccine rollout on mental health across US populations, underlining the need for careful planning in future strategies for phased disease prevention and interventions.

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