What is Data Science? Why Does it Matter for Software Development?

What is Data Science? Why Does it Matter for Software Development?

When software developers understand how to leverage the power of data science for their projects can help them create better products, faster.

The beneficial use of data scientists in software development is industry agnostic.

Understanding how to both read, interpret and create meaningful insights and decision points from the data helps a digital marketer as much as it does a researcher in the field of bioinformatics.

This article will explore the importance of data science in software development by looking at how it’s being used today, what skills are needed to become a successful data scientist, and some examples of successful projects that have utilized data science.

Leveraging the power of software engineering data science for our own (and our clients’) software development projects has proven critical as a means of measuring KPIs for what matters most.

What is Data Science?

Data science is a rapidly evolving field of study that involves harnessing the power of data (and particularly big data sets) to gain valuable insights and inform business decisions.

It combines elements from multiple disciplines, such as mathematics, statistics, computer science, and artificial intelligence, to create sophisticated analytical models.

Data scientists use these models in data collection and data analysis with vast amounts of datasets from sources such as websites, social media, databases, clinical lab research and more.

Once the data has been collected and analyzed, the resulting insights can be used to inform decisions that enable businesses to make better use of their resources for maximum benefit.

For example, a data scientist could analyze website usage data to identify which pages are most popular with visitors or draw insights from customer surveys to improve the customer experience.

But the demand for data scientists as an individual field is actually shrinking:

data scientists are in decline

That’s because the profession is becoming extremely interdisciplinary.

That is, instead of just knowing data science employees now also need to know data engineering and software engineering, ensuring everything works together flawlessly.

Why Does Data Science Matter for Software Development?

Data science is increasingly important for software developers as well. By understanding how data science works and the insights it can uncover, software developers can use it to their advantage to create better, faster products.

For example, by collecting data from existing applications software developers can identify areas of improvement, such as user interface issues or potential features that can be implemented.

A number of our clients use our capabilities in data science to make informed decisions about the features and functions they wish to implement.

Additionally, they can use data analysis to optimize their development process, test products more effectively, troubleshoot problems quickly, and create personalized experiences for users.

By leveraging the power of data scientist skills, software engineers can realize cost savings, improve product quality and delivery times, and create more engaging user experiences.

Developing software with the end in mind is best served when the decision-making data is had at the outset.

What Skills Does a Data Scientist Need?

Although data science involves multiple disciplines, the most important skills for a successful data scientist include strong knowledge of:

  • mathematics
  • statistics
  • computer programming
  • data visualization
  • probability theory
  • machine learning
  • big data software systems

Additionally, data scientists need to be able to interpret and explain the results of their analysis in a way that is meaningful for stakeholders.

Typically software engineering focuses on one area and data analysis is another.

Today’s data scientists, need to play in both worlds.


It is also important to have a strong background in mathematics and statistics, as it is the basis of data science. Furthermore, software developers need to be comfortable working with large datasets and have experience in manipulating, organizing, and cleaning data. Finally, knowledge of programming languages such as Python or R is essential for successful data scientists.

How Data Science is Being Used in Software Development

Examples of Successful Projects that Have Utilized Data Science

Here are just a few examples of how our team has used data science with clients to implement real-world solutions.

  • Successfully implemented data science tools and techniques to build a predictive model for predicting customer churn, resulting in improved customer retention rate of 8%.
  • Developed an AI-based chatbot for a customer service application, resulting in 24% decrease in support tickets, saving the support team time. However, upon further data analysis we found the customer support experience declined because most users jumping on chat wanted to talk with a human that could help with their particular issue. The resulting fix was a hybrid approach between the two.
  • Developed healthcare software with a deep learning model to help doctors to more readily detect objects on medical images with over 98% accuracy, helping better diagnose diseases.

Leveraging the Power of Data Science for Your Own Dev Projects

Leveraging the power of data science for your own projects can help create better products that are faster to market.

Data science is a powerful tool that enables software developers to make informed decisions based on data, which can be used to build highly accurate predictive models and automate processes.

By leveraging the power of data science, software developers can drastically reduce the time it takes to develop and deploy applications, and also create more efficient solutions. Additionally, data science can be used to detect patterns in large datasets that can otherwise be overlooked.

Conclusion & Takeaways

In conclusion, data science is an essential tool for software developers who want to build better products faster.

Understanding the skills and techniques needed to go from being a machine learning engineer as well as leveraging data science can help create more efficient solutions and informed decision-making is essential in today’s fast-paced dev world.

And did we mention our software developers have good bedside manners?

Get in touch with us today about your next software development project.

Let our team of dedicated software engineers and data scientists take you to the next level!

Ryan is the VP of Operations for DEV.co. He brings over a decade of experience in managing custom website and software development projects for clients small and large, managing internal and external teams on meeting and exceeding client expectations--delivering projects on-time and within budget requirements. Ryan is based in El Paso, Texas.
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Ryan Nead