Data Analyst to Data Scientist – Know the Difference between the Two and What’s Right for You

When you are looking to establish your marketing strategy for your business, you will want to reap the benefits of a data analyst or data scientist or both. The issue comes when you are trying to establish exactly what you need and exactly what each one offers. The internet is full of different descriptions and explanations of each role. In this piece, we will explore the difference between the two and which role will benefit your business. This allows you to hire the right expert to share their skills and knowledge so your business can successfully grow and develop.

While it is difficult to nail down exactly what each role does, here is a common misconception that needs to be addressed first. A data scientist is not just a fancy name for a data analyst. They have different roles, skills, salaries and expertise. This means that you will need to know who does what to get the right person for your business. 

What is a Data Analyst?

A data analyst’s role is essential to analyze data and answer questions that the business may have regarding their data. A data analyst will typically use one source for their data such as a CRM system. 

Data Analysts are experts in SQL and use regular expressions to sort through data. They can use this data to paint a picture or tell a story about your business or your clientele. A data analyst will also be skilled when it comes to the topics of maths and statistics. They will also know how to program and are experts when it comes to spreadsheets. They are able to scan through large quantities of data to find results and answers so you can learn more about your company.

Learn how to become a data analyst in our extensive guide here.

What is a Data Scientist?

Now that we have established the role and skill of a data analyst, it’s time to outline the role of a data scientist. A data scientist’s role is to use existing data to make predictions and to ask questions to the business. When these questions are answered correctly, the business will prosper. Data scientists have much of the same skills as data analysts. They are proficient at math, statistics and programming. A data scientist’s job is more centered around the future. They make predictions and use data to estimate where the business is going and what will be needed in the coming months or years.

Read our comprehensive guide on how to become a data scientist is here.

What’re the Major Differences Between the Two?

After we’ve covered what the role of each one is, it’s time to establish what the key differences are between the two. See below for some key differences from data analyst to data scientist.

  • Business Acumen. This is a key difference between a data analyst and a data scientist. Data scientists possess a lot of business acumen while data analysts are not expected to possess this skill. 
  • Data scientists will explore data from a plethora of sources. They will use whatever is available and useful. A data analyst on the other hand will usually only use one source for their work. 
  • A data analyst’s role is to find solutions to questions posed by a business. While a data scientist will ask questions to a business that if answered will likely be beneficial to the company. 
  • A data analyst is not expected to build statistical models or to have hands-on experience with machine working. A data scientist’s role is to build statistical models and they are expected to have plenty of hands-on experience. 

While the two skills have some crossover, there are clear differences between the two outlined above. A data scientist will possess the skills of a data analyst but they will have a little extra. They have business acumen and they mostly deal with predicting issues or avenues from data. A data scientist will also have more skills and experience with hands-on machinery. 

What Does My Business Need?

Now that we have established the differences between a data analyst and a data scientist, it is time to figure out which one can benefit your business the most. The first that you must consider when you are going to hire a data analyst or a data scientist is cost. On average a data scientist’s salary will be close to double that of a data analyst. This means that if you are on a budget, you may not be able to afford the services of an experienced data scientist. 

While the data scientist may appear to be more expensive, it can be more cost-effective to hire a good data scientist. They can pose questions to your business that will help you to grow and develop. This can lead to financial gains larger than the data scientists salary. 

If you don’t need the expertise of a data scientist, you should then hire a data analyst. They will be able to provide you with key information about your business, your products and your customers. This is important information and it can be quite valuable. 

To answer the question of what does my business need? The answer is both. They both depend on each other to work and they both need each other to function effectively. Depending on what you need to do in your business, you could hire either a data analyst or data scientist to assist you.

While both jobs are very similar the differences are clear. Data scientists possess skills that data analysts do not. They have more responsibilities and they earn more money per year. A data analyst can learn the skills needed to go from data analyst to data scientist which can then allow them to develop their career. This will provide them with more skills and insights that are incredibly valuable to businesses. This makes investing in an experienced data analyst or data scientist a smart business move. They are skilled workers who can give you insights into your own company as well as help you to progress and enhance your business.

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