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Difference between Data Scientist and Data Analyst

Data Scientist and Data Analyst are the perfect jobs for you if you love playing with data. This job won't just suit your interest but will also place you in the great firms with decent packages. But many of us are not able to guess the difference between these two. Most of us have misconception in our minds that data scientist and data analyst is the same person but this is not true.

Both data scientist and analyst works with data but the key difference between two is what they do with the data. Data scientists are pros at interpreting data, but also tend to have coding and mathematical modeling expertise. Most data scientists hold an advanced degree, and many actually went from data analyst to data scientist. They can do the work of a data analyst, but are also hands-on in machine learning, skilled with advanced programming, and can create new processes for data modeling. They can work with algorithms, predictive models, and more. Now coming to the role of Data Analyst, Data analysts sift through data and seek to identify trends. What stories do the numbers tell? What business decisions can be made based on these insights? They may also create visual representations, such as charts and graphs to better showcase what the data reveals.

Now the next query could be how data scientist and data analyst are related. Data analysts sift through data and provide reports and visualizations to explain what insights the data is hiding. When somebody helps people from across the company understand specific queries with charts, they are filling the data analyst role. In some ways, you can think of them as junior data scientists, or the first step on the way to a data science job. At its core, a data scientist's job is to collect and analyze data, garner actionable insights, and share those insights with their company.

Now the most important question is difference between their educational qualifications. To begin with data analyst, it requires degree in mathematics, statistics, or business, with an analytics focus, experience working with languages such as SQL/CQL, R, Python, a strong combination of analytical skills, intellectual curiosity, and reporting acumen, a solid understanding of data mining techniques, emerging technologies and a proactive approach, with an ability to manage multiple priorities simultaneously as well as some sort of familiarity with agile development methodology, and the most important which is a must for every job is strong written and verbal communication skills.