If you’re considering a career in data science or data analytics, it’s important to know what each is. There are some key differences between the two that you should understand. Before you decide to go into either for a career, make sure you understand what you’re getting into.
Those with a sense of curiosity and a need to discover new information will enjoy a career in data science or data analytics. Let’s look at both fields and the differences.
What is Data Science?
According to Southern New Hampshire University, “A data scientist applies the scientific method and machine learning techniques to find patterns in data to make predictions.” As a data scientist, you will spend time looking for better ways to leverage data in the business world.
With statistical models and complex mathematical models, data scientists can help answer questions. They also write algorithms in this very math-heavy type of career.
What is Data Analytics?
While it’s important to have good math skills in data analytics, too, this type of career is not the same as data science. As a data analyst, you will use datasets and specific software to learn information in certain areas. You may need to understand why a marketing campaign worked very well in one region compared to another.
It’s common for data analysts to use graphic and visual design to present data. They will also need very strong communication skills. With a high level of business intelligence, you can become a successful data analyst.
Data Science vs Data Analytics: The Overlap
While data science and data analytics are quite different, they also have similarities. They both allow organizations to get the competitive advantage they need. A few of the similarities include:
- Technical-Based – Both data science and data analytics will use techniques from technical fields including information technology, computer science, and statistics.
- Interpret Big Data – Both will also look at large amounts of data to see the patterns. They may take a different look at the data, but both help to interpret big data.
- Have an Impact on Other Areas – Both data science and data analytics will impact other business areas including sales, marketing, operations, and product development.
These are the main similarities. While both data science and data analytics work in similar ways, they are also very different.
Data Science vs Data Analytics: The Differences
Data analytics can be considered a part of the life cycle of data science. However, they both are different in the way they work with data. Some of the key differences include:
- Educational Backgrounds – If you go into data science, you will likely have a bachelor’s degree in a mathematical or technical field. It’s also common to get a master’s degree for those working in this field. However, those in data analytics will likely have a bachelor’s degree in a larger variety of STEM subjects.
- Focus – Data science will look for patterns and insights from all types of data collected by a company. Data analytics will look more at specific questions and the answers to those questions.
- Tools and Techniques – Data science tends to use many different techniques including data mining, statistical models, and machine learning. On the other hand, data analytics will use more automatic processes and algorithms to come to a conclusion.
There are certainly differences between data science and data analytics. Let’s also look at how these two careers compare.
Going into Data Science as a Career
If you want to go into a career in data science, you will need the right education. Let’s look at the education you need, the salary you can earn, and which industries you might be able to work in.
If you want to go into a career in data science, you will need to spend four to seven years in college. A bachelor’s degree is often required. However, you can also use an online bootcamp course and become a data scientist in three to six months.
Many data scientists go on to get a master’s degree. There are a few educational paths to choose from.
According to Indeed.com, you can earn around $74K per year as a data scientist. However, top employers will pay more than double the average salary for skilled data scientists. If you work in a larger market, such as New York City, San Francisco, Austin, Irvine, or San Diego, you will likely earn a much higher salary, too.
If you decide to go into data science, you will work in one of many industries. It’s common for a data scientist to work in retail, healthcare, manufacturing, finance, and transportation.
Going into Data Analytics as a Career
If you want to become a data analyst, you will need the right skills. With a good education, you can earn a nice salary and work for top employers.
A bachelor’s degree in a STEM subject often is the first step to becoming a data analyst. You can also get certified in specific areas or even earn a master’s degree to advance your career.
In some cases, you can take specific courses online and become a data analyst. Courses in statistics, data visualization, SQL, and many other areas can help you become hirable.
According to Salary.com, the salary range for a data analyst goes from about $70K to nearly $89K. They put the actual average salary at about $79K. Many top employers are willing to pay well over $100K for a good data analyst.
There are several large employers that look for data analysts. With the right skills, you can work for a manufacturing company, hospital, retail stores, or even a fast-food chain. Many businesses need the skills of a data analyst.
While data science and data analytics are similar, they are also very different. When you are trying to make a decision about your career, you want to compare the two before making a decision. One may be a better fit than another for you.