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Big Data has transitioned from the next big marketing buzzword to common practice in most sectors. In this article, we discuss what big data is and how it applies to ESG analysis and investing.

What is Big Data?

IS IT 3 V’S, 4 V’S, 10 V’S?

When the Big Data challenge was first being defined and encountered by businesses, there were 3 key aspects, known as the 3 V’s of Big Data:


This speaks to the volume of data. The means that the amount of data has increased to the point that previous analysis and data collection methods are no longer viable. For example, with new satellite imagery available at higher resolution and at more frequent intervals, this data can no longer be feasibly stored and processed on an individual computer. Instead, “Cloud” data technologies are required to allow multiple servers to process and analyze the data at the same time.


Velocity is how quickly the data is becoming available. “Clickstream” data is all the clicks that you do online – basically an individual’s web browsing activity. When you have many users who you may be tracking, there may be hundreds (or hundreds of thousands) of events every second. This requires specialized software that can save and analyze this data as it becomes available.


Variety can speak to a few different issues with data, but this mainly means that as technology progresses, more data becomes available. For example, as the satellite imagery mentioned above becomes better and more accessible, new types of data also become available. There are now companies that utilize this new quantity and quality of satellite imagery to monitor the number of cars in parking lots during holiday seasons or measure the amount of parks and greenspace available to a community or neighborhood.


In recent years, there have been others here and here, suggesting are more than 3 V’s. These include Value, Variability, Veracity, Validity, Vulnerability, Volatility, and Visualization. These are all excellent additions when thinking about how Big Data fits into your business case or investment question. We recommend reading the linked articles above.

What is Big Data in the ESG space?

Well, first, all of the examples above apply to ESG questions!

ESG is an evolving space, and there is no single, correct way to analyze a given sustainability question. With that said, since about 2017, the balance of data and analytics available for ESG questions has decidedly moved into the realm of Big Data Science. Former approaches which tended to rely on Excel heavily, with basic linear weighting are dated and no longer competitive…Excel files have hit their size limits and the formulae available in excel are simply no longer capable of doing the sophisticated analysis required for building financial models in the ESG space.

Typical analysis, like measuring Diversity/Inclusion (the Social (S) in ESG) now utilize many different data sources and include methods from Academia (Mathematics and Social Sciences) such as measures of dissimilariy and entropy. These new approaches provide a more accurate and complex picture of “Diversity” and “Inclusion.” Portfolios that utilize these new approaches more closely align with investor goals and are more performant since they now can measure more accurately.

What are some of the types of Big Data that you use in your ESG investment analyses?

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