What’s the Difference Between a Data Analyst, a Data Engineer, and a Data Scientist

Data, data, data…. there’s so much being generated daily in our modern world. Not just in the form of posts, stories, and links on the Internet, but also all those fancy, new job titles. Data Engineer. Data Analyst. Data Scientist. What’s the difference? Does one lead to another? What kind of skills, education, and experience do you need for each one of them?

Definitions

Before we get into the differences, one good start is to understand the words data and database because these words are at the heart of each of these jobs.

According to Merriam-Webster, one definition of data is factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation. This same dictionary also tells us that database is defined as: a usually large collection of data organized especially for rapid search and retrieval (as by a computer). These two words are at the center of all of these jobs.

Data Analysts

Data Analysts request information from an existing database or query the data. They study this data for patterns and trends. Often times, they will present it in a visual format that will make it more easily understandable for a broad audience. Necessary skills include Excel, SQL, Python, R, and HTML.

Data Engineers

Data engineers are those who focus on the development of the database architecture. Rather than querying the data, they are actually building the receptacle for the data. Strong computer programming knowledge is required at this level.  Necessary skills include Java, Scala, or Python.

Data Scientists

Data Scientists use a broader skillset of knowledge than either Data Analysts or Data Engineers including advanced math, statistics, computer programming, and machine learning. This is the level where algorithms come into play in data analysis. Traditionally, a data scientist has a mathematical/statistics background, but augment this knowledge with programming to better analyze the data. Necessary skills include math, statistics, and programming.

The job progression isn’t necessarily from one to the next as each of these jobs involves its own unique skillset, but a course in Data Science can augment your existing skills to prepare you for one of these jobs. To find upcoming Data Science courses in the Seattle/Bellevue area, check out Skillspire.

 

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