The power of data science in today’s world

According to Statistica, the global AI market was valued at $184.04 billion in 2024 and is expected to hit 826 billion by 2030. Data science and machine learning are a growing necessity for businesses and corporations are searching for talented individuals with the right skill sets.

Data of any kind is a necessity that helps companies make strategic decisions and troubleshoot challenges. As more businesses continue to see the power of data, we only expect an increasing number of companies to benefit from the ROI of the investment.

Data science is an interdisciplinary term that refers to math, coding, and business data. Without data science, businesses may struggle to make informed decisions with their finances and overall strategy. In this article, we’ll look at real-world problems that can benefit from data science and how businesses can leverage the power of data to streamline productivity and efficiency. Here’s everything you need to know:

Real-world problems solved by data science

Data science is used in the workplace to uncover patterns, improve operations, and streamline productivity. With the right data, businesses can not only solve problems but come to the table with creative solutions. Here are some real-world examples of how industries can benefit from data science.

Healthcare

The healthcare industry uses data collection tools to predict disease outbreaks. These datasets look at health records, health trends, and environmental data to predict the spread of future diseases. These datasets help Data Scientists develop a predicted risk score. A predicted risk score is a numerical value that offers insight into how likely a potential disease outbreak is. With a predicted risk score, healthcare industries can prepare for potential upticks in healthcare demands.

Data science is also used to develop tailored treatment plans for patients. With a patient’s health history and data, Data Scientists can create algorithms that provide personalized medicine recommendations based on the unique needs of the individual. This can help limit human error and ensure patients are getting the best possible care for their condition.

Climate change

Climate change is an ongoing concern that has widespread negative impacts on the world. Companies focused on making meaningful changes that can slow the risk of climate change frequently count on Data Scientists to analyze trends and patterns. For example, Data Scientists may analyze current and future weather patterns to predict future natural disasters. This can help improve safety and preventive measures while mitigating for specific communities.

Data Scientists can also use data to optimize renewable energy initiatives and reduce emissions. With data-driven decision-making, businesses and countries can prioritize renewable energy systems to reduce risk and lower costs.

Finance

Data science is commonly used in the finance industry to help detect fraud and predict future financial patterns. With fraud detection algorithms, banks can implement highly effective fraud prevention tools that protect client data and lead to fewer chargebacks. These tools can also help reduce financial loss and ensure businesses are compliant with industry fraud standards.

Investment firms can also use data science for predictive analytics. Predictive analytics can be used to mitigate financial risks, helping businesses maintain profitability during a downturn. These tools can also help investors improve their portfolios during potential market movements.

Retail and marketing

Marketers use data science in their day-to-day to make informed decisions about their marketing strategy and to streamline workplace productivity. Customer segmentation allows marketers to segment their campaigns based on a customer’s buying habits or demographics, which can help increase conversions and improve the customer experience. Built-in recommendation engines on your website can also keep prospects engaged with products or offers.

Social good

Lastly, data science can be used for social good. Many nonprofits and organizations are using artificial intelligence to identify human trafficking networks in specific communities. With the help of datasets, these businesses can discover patterns and identify potential victims.

Data Scientists can also use geospatial data to optimize disaster response initiatives. This can help victims and individuals in need access disaster relief quicker and more efficiently.

How data science solves problems: The workflow

Data is invaluable. It’s the driving force for innovation and is vital when developing data-driven strategies. While data science can be used in the workplace differently, there is a general workflow used by Data Scientists to help them solve problems. Here’s how it works:

1. Define the problem

The first step is to identify the problem. Whether you want to reduce patient waiting times at your healthcare facility or reduce client churn for your subscription product, narrowing down the problem will help you identify the correct datasets for your workflow.

2. Collect and clean the data

Once you know the problem, you collect and clean the data. This is the best way to ensure you use quality data relevant to your goals.

3. Build models

Data Scientists will then use the datasets to develop AI-driven algorithms. These algorithms help identify patterns and challenges. It can also be used to collect data for the specific problem you're working on.

4. Interpret results

Algorithms will identify patterns and use visualization or communication to interpret the results of the data. Data Scientists can then use the data to make informed decisions and adjustments to strategies.

5. Real-world action

Once the data has been interpreted, you can implement a new strategy to drive meaningful change.

Why data science is critical for the future

Businesses and governments are reliant on data. Data is used to help with decision-making and problem-solving. Whether it’s a large, global issue like climate change or something as small as customer segmentation. Data science provides business owners and leaders with key insight they need to make meaningful improvements in the future.

However, you must always take an ethical approach to data collecting and analyzing. As someone passionate about data science and machine learning, you'll want to ensure you use bias-free algorithms and fair data when evaluating outcomes and solving workplace problems.

How to get involved in data science

Careers in data science are expected to increase in the coming years. According to the U.S. Bureau of Labor, careers in data science are expected to grow 36% from 2023 to 2033. This is significantly faster than the average growth rate for careers. Data Scientists also make an average total pay of $100,282 per year in Canada. If you’re interested in a career, you’ll want to:

1. Grow your skills

To kickstart your data science career, you'll want to develop Python, R, SQL, machine learning, and data visualization skills. This will give you a competitive edge in interviews and ensure you’re prepared to handle the day-to-day tasks. Platforms like LearnPython.org can help you gain a better understanding of the skills needed for a career in data science. Kaggle also has some online courses to consider, including Introduction to Programming and Python.

Try out Lighthouse Labs' FREE SQL Essentials Course.

2. Enroll in an online bootcamp

Enrolling in a Data Science Bootcamp can also accelerate your learning and ensure you have the skills necessary for the job. The immersive, accelerated bootcamp model will teach you the skills you need to be a Data Scientist in just 12 or 30 weeks depending on the delivery method you choose. We have a 12-week, full-time, immersive bootcamp and a 30-week, part-time, flexible bootcamp available, both offering the same industry-aligned curriculum.

3. Test your problem-solving skills

If you aren't sure if a career in data science is right for you, consider testing your problem-solving skills through Kaggle competitions or open data projects. Kaggle Learn has a wide range of resources that can be used to grow your understanding of data science.

4. Leverage your domain knowledge

Undoubtedly, in-depth data science knowledge can help you solve industry-specific problems in the workplace. However, if you've worked in a different industry or business, you can call upon your past work experiences to make informed decisions in your new role. This can help you better make sense of data in different circumstances. It will also show interviewers that you are capable of troubleshooting and problem-solving at a high degree.

Wrapping up

Ready to take the next step in your career? Data science is a fulfilling career choice that offers many opportunities across various industries. Whether you want to work in healthcare or marketing, there are many career opportunities to look forward to once you have the necessary skills to excel.

As with any industry, the tech job market can be competitive. The best way to maintain a competitive edge during job interviews and ensure you understand the growing trends is to enroll in a Lighthouse Labs Data Science Bootcamp. Lighthouse Labs is here to help you strengthen your understanding of data science and walk you through real-world examples to better prepare you for your future career.

Attend our next Data Info Session to learn more about Lighthouse Labs and our Data Bootcamps.