Data science and data analysis are two different fields. There are various differences between them. On the other hand, there are various similarities between these two as well.
As a result, in this blog, we will go over everything there is to know about data science and data analysis.
What is Data Analytics
Data analytics has been around for more than 30 years, which may or may not surprise you. It all started with the launch of Microsoft Excel. Before this launch, data analytics was all about manual exercises. All analytics-related work was done using calculators and the trial-and-error method. As a result, it is not incorrect to say that the release of Microsoft Excel was a catalyst for the field of data analytics.
What is Data Science
It is very clear from the above paragraph that MS Excel kicked off the business analytics field. Similarly, there were two major trends that contributed to the start of data science. The first was technology in general. And second was the Internet, in particular. Both of these trends led to an unpredictable data science boom.
No doubt, innovation in new technologies has made it very easy to analyze and interpret vast amounts of data. Due to this, companies are now able to make many impactful and meaningful decisions.
The Internet, on the other hand, has provided endless amounts of information to companies. The Internet has undoubtedly contributed to helping companies make massive decisions by using exponential information.
Differences between a Data Scientist and a Data Analyst
| Basis | Data Scientist | Data Analyst |
| Definition | A professional who designs various data modelling processes for creating algorithms and predictive models is known as a “data scientist.” He then conducts a custom analysis. | A professional who manipulates large data sets and uses them to identify trends is known as a “data analyst.” He then draws meaningful conclusions to guide strategic business decisions. |
| Skills Possessed | A data scientist should possess various technical skills, like machine learning, and statistical analysis. | A data analyst should possess a combination of various technical skills, including knowledge of database languages like SQL, spreadsheet tools like Excel, and data visualization software Power BI and Tableau. |
| Job Responsibilities |
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| Average salary in India | In India, the average salary of a data scientist is around rupees 75,000 per month, which is rupees 9,00,000 per annum. | In India, the average salary of a data analyst is around rupees 50,000 per month which is rupees 6,00,000 per annum. |
| Average salary in the US | In the United States, the average salary of a data scientist is around $8500 per month, which is $1,00,000 per annum. | In the United States, the average salary of a data analyst is about $6000 per month, which is $72,000 per annum. |
Similarities between a Data Scientist and a Data Analyst
| Basis | Similarity |
| Basic Responsibilities | Both data scientists and data analysts are subjected to gathering and analyzing data and converting it into actionable insights. However, the purpose behind this is different. |
| Educational Qualification | One does not need any particular qualification to become a data scientist or even a data analyst. Anyone with a degree in a relevant field related to data science or data analysis can work in either of these fields. For example, a person with a degree in engineering in computer science, information technology, or mechanical or electrical engineering can pursue the job of a data scientist or a data analyst. |
| Soft Skills | Both data scientists and data analysts should possess various soft skills, including the following ones:
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This was all about data analytics and data science. Despite having two different job titles, they share many similarities as well.
