Data Analytics Interview Questions!

Data analytics interviews can be a challenging task, but with the right preparation, you can increase your chances of placement. Brush up your skills and build a strong fundamental to crack the interview. Learn about Data analysis processes like Data cleaning, Data analyses, Data Visualization, Data transformation, and about final reports. Research the industry or company you are interviewing with and understand the data analytics challenges they may face.

Here are some interview questions of Data analytics to prepare yourself for upcoming interviews-?

Q1: What are the key differences between Data Analysis and Data Mining?

Ans- Here are some key differences between Data analysis & Data mining-

Data analysis is a process of data collection, cleaning, transformation, modeling, and visualization to extract useful & essential data to take profitable decisions for an organization's growth.

Another hand, Data mining is a part of data analysis to get knowledge about hidden patterns and rules to extract valuable information from datasets.

Q2:?What about Data cleaning & what tools do we use for data cleaning?

Ans- Data cleaning is a process of removing incorrect, duplicate, incomplete, irrelevant & unused data from datasets together with useful data for an organization.?

Some tools we use for the Data cleaning process-

-Excel

-Power query editor

-Tableau Prep

-Open refine

-Tibco

-Winpure

Q3: What is the process a data analyst goes through?

Ans- Data analysts go through some steps to analyze the data-

1- Understanding the requirements?

2- Collect the data from different sources

3-??Data transformation

4- Clean the datasets

5-??Data modeling

6- Explore/analyze the data

7- Visualize the data

8- Present the results (Data reporting)

Q4: What about Outliers? How to detect Outliers?

Ans- Outliers are data points that are significantly different from other values in a dataset. Outliers detection is very important because of its negative effect on the result of the analysis.

Here are some methods to detect Outliers-

1- Visual Inspection

2- Z-score

3- IQR

4- DBSCAN

5- Isolation Forest

Q5- What is the importance of Excel in Data analytics?

Ans- Excel is a powerful tool for data analytics because in Excel we can handle large datasets and?We can calculate a wide range of data and visualizations.?Here are some key points to describe Excel is important in data analysis:

1-?Excel provides a flexible and user-friendly platform for organizing and managing data.

2- Excel provides different types of powerful functions and tools that allow us to perform complex calculations, create pivot tables, and generate charts and graphs.?

3- Excel has various options for charts and graphs that make it easy to create visually appealing and informative data visualizations.

4- Excel provides an opportunity for teams to collaborate and share data.

Q6- What is the difference between quantitive & Qualitative business analytics?

Ans- Difference between Quantitive & Qualitative analytics-

Quantitive analytics- Quantitive analytics have numerical data in the statistical method. It uses for identifying trends and patterns between mathematical and statistical data. Quantitive analytics uses statistics and mathematical formulas for analyzing data.

Qualitative analytics- Qualitative analytics have non-numerical data such as text, images, and videos. Its uses are for understanding the meaning and context of data. Qualitative analytics often uses unstructured data collection methods.

Q7- What is predictive analytics, and how is it used in business?

Ans- Ans- It is a technique followed in advanced analytics which basically makes predictions for possible outcomes which might happen in the future. It uses the data history along with statistical modeling or formatting of data. It also consists of machine learning and data mining techniques. It is used in various fields like marketing, retail, finance, etc.

Q8: What are the responsibilities of a data analyst?

Ans-?Here are some responsibilities of a data analyst-

1- Data collection and processing

2- Data analysis and visualization

3- Data cleaning and checking data quality

4- Maintaining the data sets

5- Effective communication skill

6- Up to date with industry trends

7- Effective Collaboration with the team

Q9- What are DAX queries?

Ans- DAX is (Data Analysis Expressions) a formula expression library, that basically used for Power BI, Power Pivot, and Analysis Services. DAX also includes functions, operations, advanced calculations, and also for queries related to tables and columns in tabular data models.

Q10- What are Joins in SQL?

Ans- In SQL,?joins are the method of combining data from two or more tables in a relational database based on a common column or key. The primary purpose of a join is to combine related data from different tables into a single result set.?

Here are some different types of Joins-

1- Inner Join

2- Left Join

3- Right Join

4- Full Outer Join

Q11- What are the different subsets of SQL?

Ans- SQL (Structured Query Language) is a standard language used to manage and manipulate relational databases.?

Different Subsets of SQL-

1- Data Definition Language (DDL)

2- Data Manipulation Language (DML)

3- Data Control Language (DCL)

4- Transaction Control Language (TCL)

5- Data Query Language (DQL)

6- Data Definition Extension (DDE)

Q12- What is a unique Key?

Ans- In data analytics, a unique key is a column or set of columns that shows each row in a table. The unique key is used to ensure that each row in a table can be identified and accessed easily and efficiently.