This guide is about how data analytics and data science can help make improvements with issues related to environmental, social, and economic sustainability.
For the analytics-minded and socially conscious, there are multi, new paths in which to launch your career in this Age of Information. The truth is that with good data you can take your prowess in analytics to thrive in a field that also benefits the planet.
Before we delve into big data and the tackling of environmental issues, let’s start with the basics.
What is Data Analytics?
The field that we refer to as “data analytics” is all-encompassing. It is a buzzword that is passed around a lot on job sites and in corporate settings, but its true meaning can be ambiguous.
In the simplest of terms, “data analytics” is defined as the process of studying data sets. The purpose is to find trends and extrapolate conclusions based on the info they contain. In the data world, these information pieces are referred to as “nuggets” of data or “data gems.” As the name denotes, data gems are tagged as such because they contain actionable intel.
The job skill of “data analytics” is carried out through software or specialized systems. Part of a data analyst’s expertise lies in their ability to apply these tools. Data experts are typically well-trained in an array of techniques that are ever-changing. There are also many branches and types.
Looking for more? Check out the complete data analytics guide.
What is Data Science?
Like data analytics, the field of data science branches out. It applies various methods and processes, through the use of science, algorithms, and systems to gain knowledge and insight. The extraction of this info may come from data that is structured, unstructured, or a combination. When we talk about data science, the following subjects are often presented and are important to put into words:
- Data Mining: This refers to the process by which a data scientist or data analyst mines copious amounts of data. The end goal is to identify patterns and trends. These aim to solve dilemmas in the business.
- Big Data: These are data sets that are deemed too complex or cumbersome. For this reason, they are to be manipulated by traditional software for data processing.
- Machine Learning: Referred to as ML, this is a field of study and a type of artificial intelligence. ML helps software apps to predict outcomes with increased precision. It is based on previous experiences and without being programmed. The end goal here is to bolster performance as it relates to specific tasks at hand.
If you’re like me, seeing is believing. To fully comprehend the power and importance of data, you need to observe how the above concepts are used in real and meaningful ways. Every day, companies from a wide range of industries leverage data to change the world. There are many ways in which data can make an impact (learn more about how with this complete data science guide). The focus of this piece is how it relates to sustainability.
What is Sustainability?
Sustainability is a goal in society, be it in the U.S. or abroad, that contains three pillars. They are:
In a nutshell, sustainability is about doing what is best to meet the needs of the “here and now.” And simultaneously consider the impact on the future. It is a constant balancing act. Sustainability is about acting in the present so as not to jeopardize the setting of generations to come.
How Data Can Increase and Support Sustainability
The concept of sustainability comes into play when we consider how to maintain it at all levels. Here, we refer to the global and individual levels, and that of the consumer. Sustainability is brought to light in terms of how practices in business impact other areas, i.e., the environment, economics, and our social structure. This topic is key among thought leaders all over the world.
In today’s marketplace, there is an increase in awareness to keep environmental issues on top of mind. Not to mention, the added pressure from investors, the public, and regulators to follow suit. For these reasons, top leaders are tasked with taking heed of their social responsibilities when building out their strategic plans. Analytics is a surefire way to put companies on the right path by bolstering insights.
Examples of Using Data to Solve Issues of Sustainability
Case Study One: IBM and Greenhouse Gas Emissions
In order to demonstrate how and where data can be used to increase efforts in sustainability, we need to examine cases in real life. It’s always good to start with a company that is recognized all over the world.
Let’s look at the recent merger and acquisition practices of IBM. A pioneer for sustainability, IBM took hold of its passion for the planet and combined it with what’s now in the IBM strategic plan.
In 2022, IBM took ownership of a top-notch software company, Envizi. This knowledge center set out to apply its expertise in data analytics (DA) to track and manage metrics in the environment. Through its partnership, IBM set out to succeed in its goal to make sustainability operational.
Envizi CEO and co-found David Solsky commented on the acquisition explaining, “…it is a transition to a structure that is going to allow us to scale at an unprecedented rate and globally help our clients accelerate progress toward their sustainability commitments.”
The acquisition stands to move the most forward-thinking companies toward better protection of the environment. Best practices include ESG indicators for energy and greenhouse gases. These help to take management of the planet to the next level.
To further substantiate their commitment to Mother Earth, IBM put together what is referred to as “IBM’s Environmental Intelligence Suite.” It uses tools to dig deep into the data, not only for the purpose of assessing the impact of business tactics on the environment. But also, to look at how the environment is affecting business.
IBM is one of many companies leading the way in corporate social responsibility and environmental sustainability. In a 2021 Forrester report, the former and latter tied as the third topmost concerns for organizations today. There is a definite trend in companies spanning the globe to step up efforts to do right by the planet. The repercussions of not making good on these key issues are many in terms of survival and growth. Business leaders understand the risks are too great not to take these matters seriously.
When you have the greatest minds in business, problem-solving for the biggest issues on earth, no stone is left unturned. Professionals who opt to make a career out of business intelligence (BI), in support of social issues, will be at the front and center of innovation.
Case Study Two: Dynamhex Climate Strategy and AI
When you see companies like IBM with a proven focus on the Earth, you know that analytics + sustainability is a career path that has staying power.
Large enterprises are not the only ones with a concern for the environment. There are many start-ups that are leading the way in big data and analytics for the same purpose. And using these tactics to confront issues in environments that are highly complex.
With proper backing, small firms have the ability to initiate real change. Here is the blueprint of a tech startup that spotted and filled a void in the marketplace. The U.S.-based company, Dynamhex, is a prime example. Dynamhex is at the forefront of the effort to propel climate action. They have set the stage for how tech can be used to transform the way the world responds to climate change.
Dynamhex uses AI to guide its clients in the building of what is referred to as a “climate impact strategy.” For companies that aim to make a difference, their energy data API platform will kickstart the process. Dynamhex is now uniquely helping orgs and individuals plot a roadmap for the reduction of carbon. The industry leader has triumphed in the public sector with intel that is unbiased and spurs action.
Dynamhex touts cutting-edge tools, i.e., big-data aggregation, visualization, and geospatial analytics. With these, enterprises can leverage Dynamhex’s platform for the management of accounting and emissions. The innovator uses AI-mediated analytics to reduce emissions. In short, companies can use data at the property level, i.e., buildings or households, to plot climate intelligence. They can zero in on areas that are marked as most responsible for climate change. Dynamhex brings to focus an understanding of greenhouse gas emissions per locale.
Dynamhex and its partners aim to make the transition in energy. They have collectively revolutionized the way in which the marketplace responds to the issue of climate change. Intelligence on the climate means that stakeholders can move forward with the knowledge that their decisions are data-driven.
Future Trends for Data and Sustainability
What large and small companies have accomplished in just the past decade is nothing short of transformative. If you are wondering which careers are trending worldwide, you have come to the right industry.
If this is any indication as to the magnitude of the issue and the monetary backing, look at the actions of JPMorgan Chase. The powerhouse announced its plans to finance and facilitate in excess of $2.5 trillion over a 10-year period, i.e., through the end of 2030. Their goal is to build solutions for the long term that will solve issues of climate change and help in the development of sustainability.
For a glimpse into the future, let’s look at a company that has made it its mission to protect the planet. See precisely how Equinix and their knowledge workers are to spend their days. Innovators for the good of the environment, Equinix has taken its competencies in high tech and its progressive mindset to carry out five core principles. These fall under the umbrella of its Center of the Future initiative.
- Generator-less data centers: This involves the building of a technology that yields data centers that are generator-less. The result of which is a cleaner, more efficient source of power for data centers.
- Renewable energy: A commitment to become climate-neutral, on the global scale, by the year 2030. And attain 100% renewable energy coverage for all data centers during this same timeframe.
- Airflow management: The containment of cold air and hot air leads to minimal amounts of mixing between the two. Efficient distribution of cooling air means that less power is needed for this effect. The oversight of airflow is hugely beneficial to data centers in warmer climates.
- High-density cooling: Working in the realm of cutting-edge technologies that are power-dense, spurred Equinix to take action and research and test inventive methods. They are adopting new liquid cooling methods that may set the standard in the data center industry.
- Intelligent power management: This refers to the maximization of energy inefficiency. This is made possible through the use of intelligent sensors. Such tools set out to spot potential sources of energy waste and modify them accordingly.
Key Points to Run With
It’s commendable to have spent some time laying out the key terms and getting to know the makings of a career path that is growing by leaps and bounds.
To further illustrate the impact of data on sustainability, take note of initiatives that are taking place all over the world. The UN has marked the 2020s as the “decade of action.” There is now an effort to tackle problems in the environment and economics. Sustainable Development Goals (SDGs), presented by the UN, are at the forefront. The thought process behind the attainment of these SDGs, there are 17, is that big data can play an important role in sustainability.
The fields of data analytics and data science may have previously been unknown to many. The key takeaway here is that data is solving big problems and in a big way. Imagine being a part of an effort to use inventive techniques to figure out the greatest issues that hurt our planet. From whichever corner of the earth you stand, you can be the data mind that invents in honor of your world.