Important Data Science Facts You Cannot Miss | iCert GLObal

Growing Data and Its Impact With more internet users, data is being created at a rapid pace. Technology improvements are fueling this surge.

This increase is pushing companies to find new ways to use the data to make smarter decisions.

Websites such as eBay, Amazon, YouTube, and Netflix suggest products or shows you may enjoy. They do this by looking at your preferences. They do this by analyzing data like what you’ve searched for or watched before. This is where data science comes in.

Data science became popular in 2008, and since then, it has grown into a major field. It helps companies of all sizes find patterns in data. This lets them explore new markets, save money, work better, and stay ahead of competitors.

This guide shares key facts and stats about data science. Every future data scientist should know these by 2025.

What Is Data Science?

Data science studies large data sets. It uses scientific methods and tools to find useful information. It includes analyzing both organized (structured) data and messy (unstructured) data.

The data science process includes important tasks:

• Gathering data
• Cleaning it
• Processing the data
• Grouping similar entries
• Developing models for predictions
• Summarizing what was found

These tasks help ensure thorough analysis.

After discovering insights, data scientists continue their work. They explore the data further, apply statistical methods, and create visual charts. These charts help explain their findings to others.

Data Science Facts – Data Sources Every day, we create a huge amount of data. More people use mobile devices now. Internet access is better. Also, online shopping apps are popular.Data science organizes and studies information. This helps businesses make better decisions and grow.

Here are some important facts about data sources:

• About 70% of all data is created by users, such as the pictures, videos, and text shared on the internet. This is called user-generated content.
• 1.145 trillion megabytes of data are produced every day.
• In 2021, there were around 79 Zettabytes of data created, used, and stored globally.
• Around 91% of the data used in data science is text. Other types of data include 33% images, 15% video, and 11% audio.
• 90% of the data in the world is a copy (replicated data), while 10% is unique data.
• Between 80% to 90% of data worldwide is unstructured, meaning it's messy and hard to organize.
• The average internet user would need 181 million years to download all the data on the internet.
• In 2020, about two new professionals joined LinkedIn every second.
• The U.S. had 2,670 data centers in 2021, the most in the world.
• In 2020, each person created about 2.5 quintillion bytes of data every day.

Benefits of Data Science in 2024

Data science helps businesses in many ways. Here's how:

• 72% of manufacturing companies use advanced data analysis to increase productivity.
• By 2025, the healthcare data market could be worth $67.82 billion.
• In 2019, about 68% of international travel companies invested in data analysis tools. They aimed to improve their business.
• By 2024, the big data analytics market is expected to be worth $103 billion.
• Over 1,400 universities use data science. This helps improve graduation rates and lets students finish school faster.
• 95% of businesses struggle with managing messy (unstructured) data.
• Nearly 47% of people in a McKinsey survey think data science helps businesses succeed.

Fun Facts:

• 65 billion messages are sent daily on WhatsApp.
• Netflix saves $1 billion each year by using data science to keep customers.

Data Science Facts: Popular Programming Languages for Data Science

Technology is advancing quickly. AI, Machine Learning, and Data Science rely on strong algorithms to power smart models. To understand how these programs work, it's important to know how to code. Many programming languages are used for data science, but some are more popular.

Anaconda, a software company, says that 75% of data scientists often use Python in their work. Python is the most widely used language in data science, and it is expected to remain popular in the future.

Other languages commonly used by data scientists include:

• 36% prefer using R for data science tasks (according to a survey by Kaggle, a Google company).
• 15% of data scientists use JavaScript.
• 10% use Java.
• 9% rely on C/C++.
• 4% use C#.

Data Science Facts in 2024: Jobs and Salaries

Data science jobs are growing fast and pay well. Let’s take a look at some interesting facts about salaries and job opportunities in data science:

• In the United States, a Data Scientist earns an average salary of $117,212 per year. This figure comes from 18,000 salaries reported on Glassdoor.
• Each year, a data scientist’s salary can go up by about $2,000-$2,500.
• If you’re just starting out in data science, the average salary is around $85,000.
• A Data Scientist with 1-4 years of experience can earn about $96,000. If they have 5-9 years, that number rises to around $110,000.
• By 2026, it’s expected that there will be 11.5 million data science jobs!

Data Science Facts for the Future

Looking ahead, here are some exciting data science facts about the future:

• By 2024, 66% of people on Earth will be connected to the internet.
• By 2025, there will be 75 billion Internet of Things (IoT) devices, which is almost three times as many as in 2020.
• Data scientists will earn between $65,000 and $153,000 per year in the future.
• By 2024, there will be 3 times as many devices connected to the internet as there are people in the world!
• By 2024, there will be 149 zettabytes of data (that’s a huge amount) collected and stored. This is a lot more than the 2 zettabytes created in 2010.
• By 2026, the market for data science tools is expected to be worth $322.9 billion.

Become a Data Science Professional with iCert Global

If these facts excite you and you want to become a data science expert, we can help! We offer detailed courses to help you get started in this field. Check out our top programs and find the one that works best for you!

How to obtain Data Science certification? 

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Conclusion

Many fresh graduates believe they can't begin a career in data science. They think this happens because their university courses didn’t cover key topics, like big data analytics. Some seasoned professionals also feel unready. They didn’t get to update their skills. Not developing skills means they miss the hands-on experience employers want. If you're interested in data science and feel this way, iCert Gloabl can assist you.

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