Question 1

Can you explain the role of a Data Analyst in a business setting?

Accepted Answer

Data Analysts interpret historical data, identify trends, and provide actionable insights to support decision-making within a business.

Question 2

What statistical techniques are commonly used in Data Analytics?

Accepted Answer

Data Analysts often employ statistical techniques to analyse historical data, such as regression analysis, hypothesis testing, and correlation analysis.

Question 3

How does Data Science contribute to decision-making in the finance industry?

Accepted Answer

In finance, Data Science can be applied for risk assessment, fraud detection, and portfolio optimization to make informed investment decisions.

Question 4

What distinguishes a Data Scientist from a Data Analyst in terms of skills?

Accepted Answer

Data Scientists typically require advanced skills in machine learning, statistical modelling, and programming, whereas Data Analysts focus on data interpretation, visualisation, and statistical analysis.

Question 5

How does the Data Science process differ from the Data Analytics process?

Accepted Answer

While both involve data exploration and analysis, the Data Science process includes predictive modelling and complex algorithm development, whereas Data Analytics is more focused on historical data analysis.

Question 6

Are there specific industries where Data Analytics is particularly valuable?

Accepted Answer

Data Analytics is valuable in various industries, including marketing, finance, healthcare, and retail, where historical data analysis can inform decision-making.

Question 7

What role does domain expertise play in the skills of a Data Scientist?

Accepted Answer

Domain expertise is crucial for a Data Scientist as it enhances the understanding of business goals, enabling the development of more relevant and effective models.

Question 8

What are some common data analysis tools used by Data Analysts?

Accepted Answer

Data Analysts often use tools like Excel, SQL, and specialised analytics software for data manipulation, statistical analysis, and visualisation.

Question 9

How do salary levels differ between Data Science and Data Analytics roles in India?

Accepted Answer

Generally, Data Science roles command higher salaries than Data Analytics roles due to the additional complexity and skill set required.

Question 10

What are some factors that can influence salary levels in Data Science and Data Analytics?

Accepted Answer

Factors such as experience, location, and industry can significantly impact salary levels in both Data Science and Data Analytics roles.

difference between data science and data analytics with example

Data Science vs Data Analytics: Definition, Process, Role and Skills Required