How Data Science is Driving Innovation in Climate Change Research

Fighting Climate Change with Data

One fascinating example of how data science is helping to make the world a better place to live is in climate change research. A recent study by NASA Technical Reports Server (NTRS) provides an in-depth look at how massive amounts of data can be leveraged and analyzed to generate viable solutions to the threat of climate change.

As the report posits, climate science represents a big data domain that is experiencing unprecedented growth. The challenge lies in better understanding the implications of these vast datasets and deploying the right computational resources to build and deploy useful applications.

For instance, the report states, there’s a need to provide effective means for publishing large-scale scientific data collections and performing scientific analysis based on large quantities of data, quickly and efficiently. The job of data science is to help transform large scientific data collections into meaningful scientific knowledge, through which organizations can generate real solutions to fight climate change.

A recent Forbes article outlines some additional ways that data science is providing practical solutions to the climate change issue. For example, organizations can reduce their carbon footprint by utilizing sensors in their environments to keep track of carbon emissions; using IoT sensors to monitor waste and energy consumption; and analyzing raw, unstructured data to create actionable intelligence in renewable resources such as wind turbines.

Rapid Growth in AI Drives Better Climate Data Science

Modern data science has been supercharged by the growth of artificial intelligence and machine learning technologies. AI has a unique ability to find patterns in massive amounts of data faster than its human counterparts are able to. Data scientists can then use this to help discern viable solutions to many common problems.

According to IDC, investments in analytics and AI this year are forecast to grow to $185 billion, with a 12 percent CAGR through 2024. In fact, AI and machine learning are so popular in the data science space that the terms are now virtually synonymous with data science. According to Indeed, “AI” and “machine learning” were included in the job descriptions of 75 percent of data science jobs. Meanwhile, demand for workers with AI skills has more than doubled in the last three years.

Aspiring data scientists are increasingly looking to AI tools and programming languages like Python (the most popular language for AI and machine learning) to master their trade and lock down the top jobs. Data Science with Python training is a vital prerequisite to understanding important data science processes like data wrangling, exploration, visualization, hypothesis building, and testing.

Raise Your Skill Set to Prepare for Data Science Opportunities

It doesn’t take that much to begin the process of learning data science to fulfill your career goals and opportunities abound for those who want to apply their new skills to help prepare the world for a better future. First, it takes a fundamental understanding of the vital tools and analytical platforms that data scientists use every day.

The SAS data science platform is among the most popular for mastering advanced statistical concepts that are crucial for harnessing the power of data to solve real-world challenges. SAS training provides an all-encompassing look at data analytics techniques, including: 

• Clustering, linear regression, and decision trees
• Combining and modifying complex datasets
• Applying predictive modeling techniques to put raw data to work in real-world applications like climate change

Data Science with R is another core platform that leverages the R programming language to empower data exploration, data visualization, predictive analytics, and descriptive analytics. Data science professionals who undergo R skills training can master skills such as linear and non-linear regression models, data structures and packages, hypothesis testing, data visualization, and importing and exporting data in R.

It doesn’t matter where you think you’ll apply your data science expertise. There are plenty of applications and job opportunities out there, from building more responsive consumer-facing applications, targeted search, and digital marketing techniques to better speech recognition technologies and more impactful climate change research. All are valuable endeavors, and some may even make the world a better place for us all.  

Looking forward to a career as a Data Scientist? Test your understanding of the concepts with this Data Science with R Practice Test. Try answering now!

Want to Start or Boost Your Career in Data Science?

It’s an understatement that data science is one of the hottest careers out there. If you’re interested in building your career in the exciting field, Simplilearn’s Data Scientist Course covers everything you need to know. From the essential programming languages, Machine Learning techniques, visualization platforms, and Big Data frameworks, you can prepare to launch a career to do amazing things, including working on climate change.