Data scientist vs data analyst: The major difference between the two

economictimes.indiatimes.com:

Today, people looking at a career in the world of data have a common question: how do you differentiate between a data scientist and a data analyst?

The skills for both are similar, says Simplilearn, an online learning platform. While the role of a data analyst has been around for longer, data science started when the data boom led to the use of new technologies to manage, interpret and analyse such large data sets to make better decisions, according to Simplilearn. The work involves understanding business problems, looking at various sources of data to assess patterns, finding the best way to look at insights and then distilling them for outcomes.

The learning platform says data scientists are primarily problem solvers. The kind of tools they need to work on are vast — Tableau, Python, Hive, Impala, PySpark, Excel, Hadoop, etc — to develop and test new algorithms. Data scientists look at both structured and unstructured data, and build AI and machine learning models.

Meanwhile, the responsibilities for data analysts range from gathering data across databases, building complex queries using SQL and other tools, spotting trends and creating reports.

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In terms of qualifications, engineering, information technology, and degrees in maths, statistics and economics are important for both, along with the right domain knowledge.

Where the skills differ

Data Analyst Skills

Data Scientist Skills