Data Analyst vs. Data Scientist: Do you know the difference?

Harvard Business Review described the role of a data scientist as “the sexiest job of the 21st century.” Ever since the field has gotten so much buzz and recognition, which has increased the need for data skills. Although similar, Data Analysts and Data Scientists carry out different tasks that require different skills and tools. 

  • Data Analyst: A data analyst typically gathers, interprets, and identifies trends in data in order to solve a problem(s). A data analyst typically uses tools like Excel, SQL, Tableau, or Power BI. They also have basic fluency in Python or R.
  • Data Scientist: Data scientists use more advanced data techniques to make predictions about the future. They might automate their own machine learning algorithms or design predictive modeling processes that can handle both structured and unstructured data. Data Scientists usually have one or more of these skills up their sleeves:  Python, R, Java, SQL, Matlab, and Big Data Frameworks like Hadoop, Spark, and MapReduce)