Data Analyst vs. Data Scientist. How similarly do they differ

Data analytics seems to be the buzzword lately. Expected to experience a colossal boom, data analytics presents an opportunity that companies need to grasp with immediate effect.

The stock pile of data remains redundant unless someone makes a sense of it and extracts insights from it. That someone is either a data analyst or a data scientist. Exclude the word data from both the job profiles and many aspects distinguish them. A lot of confusion regarding the role and responsibilities concerned with the two job profile persist. Companies too define the job profiles based on their requirement.

Let us explore both the job profiles based on the skill set, knowledge, roles and responsibilities attached with each role.

Data Analyst

Data analysts turn numbers, figures and data into insights. They convert huge chunks of data into conclusions and inferences.

In short, reading between the lines wherein the lines depict data. They are responsible for providing the company with valuable inputs that will help it perform to its finest and take relevant decisions that propel business ahead in a speedy and profitable manner.

They initiate change within the organisation by analysing data and providing recommendations. These recommendations may vary from recommending changes to meet consumer satisfaction, adopt practices for maximum utilisation of human resources and physical resources and ways to reduce unnecessary cost.

The skills required for the role of a data analyst are:

A bachelor's degree is needed in a numerical field. Some companies do look our for candidates with Master's degree, again in a numerical field
Analytical bent of mind along with ability to digest large amounts of data and understand the nuances of business
Practical knowledge of statistical packages like - SAS, R, Python, etc
Understanding of relational databases like Teradata, SQL server, etc

Data Scientist

They work closely at the business domain level as well as the IT level. Data is interwoven with stories. Data scientists uncover these stories by interpreting data and drawing inferences to change how business is conducted.

They deploy their statistical and analytical skills to identify solutions to business problems. They are expert in applying statistical techniques in solving complex business problems, which otherwise, are not solved using common data analysis approaches.

The skills required for the role of a data scientist are:

1. Master's or in some cases PHD in a numerical field with specialisation in Mathematics/Statistics

2. Deep understanding of statistical techniques and approaches and how to use them in solving business problems

3. Good understanding of statistical and data analysis packages like - SAS, R, Python, etc.

4. Understanding of relational databases like Teradata, SQL server, etc

So the natural question you’d ask is how much money do they make?

Even as both the job profiles are subsets of the data analytics sphere, the salaries do vary based on educational background, knowledge, experience and skill.

According to glassdoor.com, the average salary of a data analyst in the London area is £32,000, which is £2000 above the national average of £30,000 per annum.

Whereas, the average salary of a data scientist in the London area is £45,000 which is £3000 above the national average of £42,000 per annum.

The future of data analytics is beaming with possibilities. So, pursuing a career in this field will be rewarding not only monetarily but also for a fulfilling career experience.

Data Analyst vs Data Scientist
How similarly do they differ?

September 10, 2017

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Data Analyst vs Data ScientistHow similarly do they differ?