There was a time when scientists were the backbone of every advancement that has impacted our world. Pioneers like Marie Curie, Newton, Einstein, Galileo, Edison, and many more, have shaped our knowledge and changed the way the world functions today by answering to the needs of society, and ultimately, the world.

Similarly, today and with the emergence of big data, we find the traffic of unstructured information overwhelming companies and increasing workloads. Just like scientists were the unsung heroes of yesterday, Data Scientists have become the unsung heroes of today as they translate data into key business success factors.

What is Data Science and why is Data Science so important?

First of all, we need to make it clear that data science is NOT computer science or computer engineering. While computer science is in charge of computation and applications, data science is in charge of data throughout its lifecycle – from storage to archiving – especially when it comes to insight and predictions.

Mainly, data scientists are in charge of analyzing, managing, and using data in useful ways that can become business solutions for companies.

You may be thinking that companies can simply hire statisticians to do so like they previously did. However, with the development of computing processes, cloud storage, and analytical tools, the world of statistics merged with computer science brought data science to life.

Data scientists need more than just math and statistics to be effective; a data scientist also needs knowledge of supply chain, finance, logistics, human resources, and so on. The more knowledge the data scientist may have, the more they are worth the investment a company is willing to make to hire them.

These modern-day wizards use algorithms, patterns, visualization tools, and machine learning to optimizing workflows and predict trends.

Not only do they make sense out of data, but they also study user behavior and habits through data gatherings such as the world wide web or software search history.

Why are Data Scientists the common-day heroes of companies?

Data Scientists have become an indispensable asset for companies as they are a key part of business success. While software maintains data, data scientists figure out how to utilize it to push businesses and markets forward.

If data is contained and maintained without it being utilized for actionable insight, every piece of datum that we have is rendered valueless.

Think of all the companies that made an incredible profit during the Covid-19 pandemic. They were able to be on top of their game because they were able to properly manage their information and assets, predict trends, personalize their customer experiences, and recreate effective teams while working remotely; all of which are tasks aided by data scientists.

Top 6 ways Data Scientists use their superpowers.

Risk and Fraud

Data Scientists may detect risk and fraud by being trained to investigate data that doesn’t seem to fit trends or patterns. Once detected, they can create alerts and respond effectively and efficiently saving companies millions in return.

Market Trends

Data Scientists may very well help product businesses identify when and how their items are best sold, helping marketing teams and sales with their predictions, strategies, and overall sales.

Personalized Customer Service

Data Scientists are also the people behind personalizing experiences for customers by providing other departments an understanding concerning their customers or audiences – depending on the industry – and helping them work on meeting customer needs.

Decision Making

These insights and predictions tremendously help upper-management in making significant decisions with lower risks across the company by measuring, tracking, and managing performance metrics.

Targeting Customers

Data scientists are also able to identify key groups by matching them with trends and data at hand, allowing organizations to tailor their services to potential customer groups.

Human Resources

Just like they collaborate with sales, marketing, and upper-management teams, data scientists may also work with human resources departments to identify potential employees that would fit companies like a glove using metadata on CVs as well as metrics from employment websites such as LinkedIn. It is also important to note that they may also take charge and analyze aptitude tests and games within the hiring process

Tools as the Backbone of Data Scientists

At this point, you should probably be convinced of why any company may need data scientists, even more so, why these modern wizards have become the backbone of any company’s success. But just like wizards need a wand, heroes need a cape, and scientists need their tools, data scientists are also rendered helpless without their data processing tools that allow them to collect, maintain, visualize, integrate, and manage data to begin with. Intalio offers tools for data integration, data processing, and data insight to help companies provide the right tools for data scientists by having control over information and be able to leverage workflow automation throughout the entire data lifecycle.

Find out more about intalio’s data governance tools.