Careers in Data are not restricted to pure science. There are plenty of options for Data Scientist and Analyst positions, but they are two very different career paths. Read this article to find out more about the differences between these two Data roles, what they entail, and which might be best for you!
What Is A Career in Data?
A career in Data is a fast-paced, challenging, and exciting way to use your love of mathematics and computer science for the good of all kinds of businesses.
There are lots of different roles available when it comes to careers in Data, which can be split broadly into two categories: data scientist vs data analyst. The difference between these two careers in Data is important to understand, both for what each entails and which may be best suited to you.
What Does a Data Scientist Do?
A data scientist is a more advanced role of a data analyst. They have a deep understanding of computers and how they work, as well as the ability to recognize complex patterns in numbers and draw meaningful conclusions from them.
They are perhaps the most important role within a company in terms of understanding how customers use a product and what they need to improve it. Typical daily tasks for a data scientist might involve:
- Monitoring real-time customer usage data.
- Examining web traffic, social media posts, etc., for any trends or information that can be used to improve the company’s business model.
- Conducting statistical analysis on that data and then presenting it in a way that is easily understood by non-technical employees.
What Does a Data Analyst Do?
Although data analyst positions are often stepping stones towards data scientist positions, they’re their roles. Again, the main purpose of data analysis is to examine real-time data and draw conclusions from it, but the difference is that data analysts aren’t expected to have as much technical knowledge or programming ability. Daily tasks for a data analyst might therefore involve:
- Conducting statistical analysis on that data and then presenting it in a way that is easily understood by non-technical employees.
- Examining the company’s product and its customers’ behavior to determine areas of improvement, including gathering user requirements for new features.
- Using software tools such as JIRA and Trello to help organize projects and tasks.
What Other Roles Are Available?
In addition to those roles related directly to data, there are lots of other jobs available within a company that have a data-related element. These might include:
- Database administration.
- Web design and programming.
- Network engineering, security, etc.
- Business intelligence consulting (helping companies use their data more effectively).
- Data visualization.
Why Data Scientists and Data Analysts Are Important
Although the media might portray Data Scientists and Analysts as super-intelligent, all-knowing gurus of data, these professionals are responsible for some of the most important decisions using strategic thinking within a company.
Good data analysis is vital to helping any organization function more efficiently and therefore compete in their market more effectively. They are also important because of their capacity to empower employees throughout the company by helping them understand how they can improve what they do.
For both careers in data, there are many different tools you will be using. These include Microsoft Excel and Google Sheets, SQL and SQL-like languages such as MySQL and JavaScript, R, Python, MATLAB, Machine learning and neural networks, Software development kits (SDKs), and many more. It’s important to know how to use these tools as a data scientist, as well as how to use them as a data analyst!
What Career Is Right for You?
The difference between the two is subtle but important. For both, you need to have a strong understanding of computers and statistics. However, for data science, you also need to have a strong programming background. That’s not necessarily true for data analysis, although evidence of using SQL or machine learning would also be helpful!
Also, data scientists tend to work with very large sets of highly complex data (think Big Data). Data analysts might deal with smaller (though still pretty big) sets of less complex data. When choosing what kind of data and how much data you’re willing to deal with, it’s important to consider your competency in dealing with these types of data.
Now that you have read about these two careers in Data, it comes down to which career is better for you. A data scientist will require a greater knowledge of programming and statistics, but it also opens up more career opportunities, such as data visualization and consulting. A data analyst is a great choice for someone who wants to work in the realm of Data but doesn’t necessarily feel passionate about it or want to study further.
Remember that if you choose this career in Data, your job will be all about analyzing numbers and drawing conclusions from them – it’s important to enjoy both that and working with numbers. It’s also important that you understand the job position thoroughly before you apply for it so that you understand the job requirements.
Who Employs These Positions?
Both data scientists and data analysts are employed primarily by organizations in the technology, finance, and science industries. These include:
- Finance companies that use customer activity to determine potential investments.
- Banks that need to analyze wire transfer records.
- Companies using social media to target advertising.
- Government agencies with large datasets related to healthcare, crime, and the environment.
- Scientific research institutions that need to analyze experimental results or climate change data.
- Technical companies in IT, networking, etc.
There are options for both Data Scientist and Analyst positions, but they are two very different career paths. A data scientist will require a greater knowledge of programming and statistics, as well as being good at math. However, the job opportunities that open up from this role are numerous.
Data analysts, on the other hand, deal with smaller sets of less complex data. Data analysts also do not need to have a strong background in programming or statistics, although evidence of that would be helpful. Remember that if you choose this career in Data, your job will be all about analyzing numbers and drawing conclusions from them – it’s important to enjoy both that and working with numbers!
