Zen and The Art of Data Maintenance: Ways Data Pros Can Help the Environment

The earth does not belong to man. Man belongs to the earth. All things are connected like the blood that unites us all. Man did not weave the web of life, He is merely a strand in it. Whatever he does to the web, he does to himself.
Chief Seattle

The earth’s environmental circumstance desperately needs help.

But we are busy. I often feel overloaded and ask myself, ‘Does anything I do regarding the environment really help or really matter that much?’

There is a fundamental truth that provides insight to this question. We are not separate from the earth. Everything is interconnected. Each person is like a cell within a body. Each cell is part of the whole that makes a person. Likewise, each person is part of the whole that makes the earth.

Thus, let’s recognize and act upon this. No matter what the consequences of our actions to help the environment, taking actions to assist the whole yields positive returns. When we serve the whole, what often follows is more peace, contentment, health, and fulfillment. And whatever actions we take to help our earth makes a difference.  And, yes, we feel better when we do this.

In my previous column articles, I have talked about environmental facts and human dynamics,[i] and now let’s discuss what we, as data professions, can do. We have unique skills that can help.

Since this is one of humanity’s greatest existential challenges, wouldn’t it make sense if we, as data professionals, came to the table more and offered our specialized skills? For example, we could help in the areas of data strategy, data modeling, data literacy, data science, data storytelling, data analytics, data governance and many other aspects of data management. Let’s explore some possibilities.

Data Strategy

When we are creating data strategies, we could ask questions such as:

  • How are ESG (environment, social, and governance) factors related to our organization’s goals?
  • How can we incorporate data to help us to meet these goals?

Data strategies could include:

  • The use of data analytics to assess our environmental impact,
  • Data science algorithms to help predict what actions could result in more beneficial results for ESG
  • Use of data modeling to capture the data needs to perform ESG measurements
  • Data storytelling to share how our organization’s actions have made a difference
  • Data visualizations to help illustrate what is happening in our environment and what types of effects could be possible

Environmental factors are becoming increasingly important to the value of an organization. Investors are looking at ESG metrics when considering where to invest. For example, in a recent study, 75% of the investors surveyed were interested in the robustness of an organization’s planning for climate risks. [ii] Socially conscious investors, such as BlackRock, use the ESG criteria to screen for potential investments and BlackRock now offers more than 150 mutual funds and exchange traded funds (ETF) that adhere to ESG standards. [iii]  

Let’s begin including ESG data in every data strategy we develop.

Data Modelling

On every data modeling project, let’s ask what the ESG data requirements are and model them.

We could provide common ways to capture this information in many different formats. For example, we could provide entity-relationship (ER) models that captures data model entities such as the ‘organization’ and its associated ‘organization metrics’, that are for a particular ‘standard time frame’ and ‘metric type’. Subtypes of metric type could be ‘environmental metric’, ‘social metric’, ‘governance metric’ and ‘economic metric’. Alternatively, we could provide data models in other formats such as Data Vault models with this type of information in hubs, links, and satellites. Or we could provide graph data models, for example, with this information in subjects, predicates, and objects (for Resource Description Framework data models), or in nodes, relationships and properties (for property graph data models).

We could provide star schema models that capture fact tables with environmental measures such as the amount of greenhouse gas emissions, water usage, or other measures such as the below table illustrates within our fact table. These measures could be sliced and diced by dimensions such as ‘organization unit’, ‘time’, ‘geographical boundary’, and ‘product type’.

Environmental Risks Environmental Metrics
Carbon Emissions (“Greenhouse Gas” or “GHG” Emissions) ● Amount of GHG emissions (Mtons)
● Emissions intensity (Emissions per unit or m$ revenue)
Energy Efficiency ● Amount of energy used (mj)
● Energy intensity (Energy per unit or m$ revenue)
Waste ● Amount of waste generated (Mtons)
● Waste intensity (Waste per unit or m$ revenue)
Product Life Cycle ● % product from recycled materials
● % product recyclable or compostable (including packaging)


Data Science

We need to use our unique skills in data science to answer questions such as:

  • What is our organization’s carbon footprint and what is the expected carbon footprint over time if we act in a similar fashion? What are the predictions if and when we change our actions? What factors and actions would be most important to reduce our footprint?
    • In what areas or processes can we most effectively reduce negative environmental influences such as pollution or greenhouse gas emissions? What is the return on investment (ROI) of changing these?
    • What are the correlations and causes between various factors? For example, how do increases in greenhouse gas emissions affect our profits and revenues? What risks arise from increased pollution created by our organization?

We must begin to opportunities to offer data science models and insights to help answer the above questions (as well as many other questions).

The graph below, showing the correlation between climate disasters and atmospheric CO2 levels, is just one example of the many ways that we can provide information and insights stemming from data science efforts. Graphs like this could be used to garner support for your organization’s efforts to reduce its carbon footprint.

Click to view larger [v]

Data Storytelling

We use our data storytelling skills to improve business leaders’ understanding of the impacts of certain activities in the business. Perhaps we could use these same skills to help better understand our own business’ environmental data and its impacts, which could then inspire needed actions.

For instance, consider the data from NASA stating that “Sea level continues to rise at a rate of about one-eighth of an inch per year.”[vi]

One may think, ‘So what?! This seems minor.’

However, many sources have shown how this trend can lead to disastrous consequences.  For example:

This can lead to major economic impacts including escalating insurance costs. First Street Foundation predicts that substantially more properties will have flood risks and the cost of that potential flood damage will increase dramatically[vii] not to mention significant raises in all types of insurance.

Rising sea levels can have a profound effect on the way many people live. This is one of many factors that can lead to mass migration and displacement issues. The U.S. Department of Defense recently stated that ‘the climate crisis is a profoundly destabilizing force for the world’ and that climate change factors ‘threaten millions with drought, hunger and displacement.’

So, let’s skillfully use data storytelling to motivate people to take action on a local level.

Data Literacy

There is a great deal of data available regarding the environment, yet data can be manipulated to help parties achieve their specific agendas.

We, as data professionals, could use our knowledge of data principles to point out misinformation or data fallacies and move towards a better understanding of what is happening.

For example, there have been some information sources that have claimed that solar factors are mainly responsible for global warming and not human activity.[viii] Yet, there are many other sources that claim that our human behavior is largely responsible for global warming.[ix]

We could help sift through issues like these and facilitate better understanding by applying data literacy capabilities.

Other Data Disciplines

In addition to the above areas, we can apply many other disciplines in data management to help our environment such as:

  • Using data governance and data quality skills to better understand the quality of environmental information related to our organization and how to govern the usage of this type of data
  • Using data analytics skills to describe our organization’s impact on the environment, predict various outcomes given various scenarios, and prescribe beneficial solutions
  • Using data visualization and storytelling skills to provide tools to better illustrate our organization’s effect on the environment
  • And using a plethora of other disciplines to help environmentally such as data mining, predictive analytics, machine learning, AI, etc.

Other Things We Can Do

In addition to using our skills, we, as data professionals, can:

  • Ask questions about how our organization is addressing environmental concerns
  • Provide ‘environment and data’ talks via brown bag lunches
  • Give executive presentations about data and our environment
  • Get involved in small projects, for example, develop methods to capture environmental metrics and measurements within a small area of our organizations
  • Provide suggestions to executives on ways to help environmentally within our organizations like recycling, reducing packaging materials, better climate control in our buildings, and so on.
  • Suggest various environmental challenges or contests specific to your organization

Finally, several data professionals (including myself and other prominent data leaders) have formed a group called the Eco Data Group. If you would like to join and help create content (articles, presentations, videos, blogs, etc.) that will inspire positive environments actions, please see our website www.ecodatagroup.com or email us at ecodatagrp@gmail.com. An example of one our activities is that the presentations Claudia Imhoff (a member in our Eco Data Group) and I have started giving on creating sustainability metrics. If there are opportunities to present this for any data professional group or organization, we would be happy to do so.


What is happening with our environment represents one of the most important and existential issues of our time. We, as data professionals, have a great opportunity to offer our unique skills in mitigating environmental changes.

[i] https://tdan.com/zen-and-the-art-of-data-maintenance-does-data-alone-inspire-environmental-actions/28510

[ii] https://www.ey.com/en_us/assurance/how-will-esg-performance-shape-your-future

[iii] https://www.foxbusiness.com/financials/larry-finks-blackrock-benefit-esg

[iv] https://www.fe.training/free-resources/valuation/esg-metrics/

[v] https://arxiv.org/ftp/arxiv/papers/1404/1404.7469.pdf

[vi] https://climate.nasa.gov/vital-signs/global-temperature/

[vii] https://www.nhpr.org/climate-change/2021-04-22/how-risk-from-climate-change-will-reshape-flood-insurance-in-n-h-and-new-england

[viii] https://www.nature.com/articles/s41598-019-45584-3#Sec6

[ix] https://www.nbcnews.com/science/environment/earths-energy-imbalance-removes-almost-doubt-human-made-climate-change-rcna1562

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Len Silverston

Len Silverston

Len Silverston is a best-selling author, consultant, speaker and internationally acclaimed expert and thought leader in the fields of data governance, data modeling, data management, and in the human dynamics of integrating information data. He is the author of The Data Model Resource Book series (Volumes 1, 2, and 3), which describe hundreds of reusable data models. The volume 1 book was rated #12 on the Computer Literacy Best Seller List and his volume 1 and 2 books have been translated into Chinese and in 2009, he co-authored “The Data Model Resource Book, Volume 3, Universal Patterns for Data Modeling”, which has been translated into Korean. Mr. Silverston has published many articles and has been a keynote speaker at many international data conferences. He is the winner of the DAMA (Data Administration Management Association) International Professional Achievement Award and the DAMA International Community Award. He has given many keynotes and has received the highest speaker rating at several international conferences. Mr. Silverston's company, Universal Data Models, LLC, http://www.universaldatamodels.com provides consulting, training, publications, and software to enable information integration as well as people integration. - He is also a personal and corporate mindfulness coach, trainer, and teacher and has studied and taught many forms of spirituality and life development skills for over thirty years. He has attended, staffed and/or led hundreds of days of silent, intensive retreats as well as dozens of life development workshops. After intensive practice in Zen, he was ordained as a Zen Priest in 2011. ‘Kensho’ Len Silverston provides ongoing ‘Zen With Len’ (http://www.zenwithlen.com) individual and corporate coaching, seminars, meditation gatherings, and retreats.

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