Data Science VS Data Analytics: Is There A Difference?

Share This Post


Businesses that are thriving today leverage data and insights.

Netflix analyzes users’ viewing habits to personalize content recommendations. Bank of America offers cash-back promos based on customers’ past purchases. UPS optimizes the flow of packages and helps employees make data-driven decisions and improvements.

These are just some of the many ways data can enhance business outcomes and performance. While data is critical, the benefits that organizations can get from it depends on how it is used and applied.

According to SiteCore, brands collect at least eight different types of data about customers. But “around 31% point to a lack of skills needed to properly use or analyze the data collected, and 42% don’t have the capabilities to integrate data collection.”

Data science and data analytics

Raw, unstructured, and structured data means nothing until it’s transformed into insights. This is where data science and data analytics come in.

Big buzzwords in recent years, data science and data analytics are two approaches that process and analyze data. People often interchange them but although both disciplines have similarities, they are also different in some ways.

What is data science?

Data science uses scientific methods to gather actionable information from large amounts of data. It finds which questions need answering using various techniques such as predictive analytics, machine learning, and statistics. Data science figures out how to obtain and apply data and insights to address a business need.

Source: UC Berkeley

For data science to produce meaningful intelligence, the process should go through the discipline’s whole lifestyle. This includes identifying questions, collecting and organizing data, translating results into solutions, and communicating the impact on business decisions and goals.

What is data analytics?

Meanwhile, data analytics is a subset of data science. It processes and interprets existing data. And then develops systems and presents findings through useful reports. Techniques in data analytics include statistics, data visualization, and communication skills.

Data analytics bridges the gap between data science and business analytics. It’s more focused than data science. The main goal of data analytics is to make insights not only accessible but also practical to the organization’s stakeholders.

In short, data analytics “determines what data is needed and how to present the findings,” and data science “builds the model to acquire the data.” Both fields use and rely on programming and computing methods to help businesses make decisions based on extracted, valuable conclusions.

The bottom line

Data science and data analytics are powerful approaches that are very interconnected and have overlapping use cases. Examples include recommender systems, fraud detection, customer-sentiment analysis, and digital marketing in most industries from gaming to healthcare.

So now, you might be asking, which one is better for your business? The answer depends on your goals. Because even under the most favorable situation, gaining impactful benefits can take a long time. You also have to make sure you are setting your business up for success as you transform it into an insights-driven organization. Typical things to consider include:

  • Putting up the right technologies
  • Investing in people with relevant skills
  • Embedding a data-first culture into processes

Data science and data analytics can help your organization better work together, build capabilities, reduce costs, facilitate innovation, and more. All areas are important for continuous improvement and growth.

Essentially, the two disciplines aim to understand the big picture—just like what Dealtale does. Dealtale democratizes data science and data analytics, so that any organization can grow effectively, based on insights rather than assumptions or best practices.

With Dealtale, you can bring all of your data together to enable big-picture analysis. As a result, you get to scale and boost performance. It takes only 10 minutes to set up. Activate our ‘Free Forever’ plan today at Dealtale’s Sign Up Page.

More to Explore


The Revenue Science Blog

Learn about the latest breakthroughs in
Revenue Science, geek out on quantum theories, and mastermind your next big marketing moves!