Data Analyst Interview Questions And Answers | Data Analytics Interview Questions | Simplilearn

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This video on Data Analyst Interview Questions And Answers by Simplilearn, will take you through the most frequently asked data analyst interview questions and answers. Data analysis is one of the trending jobs of the 21st century. This video covers all the important questions that would help you crack a data analyst interview. It has a set of basic questions related to the data analytics field. It also has a collection of beginner, intermediate and advanced-level questions based on MS Excel, SQL, Tableau, and Python. It would enrich your theoretical and practical knowledge of data analytics. What you will learn

0:00 Data Analyst Interview Questions And Answers
00:34 What is the difference between Data Mining and Data Profiling?
01:38 Define the term Data Wrangling
02:40 What are the common problems that data analysts encounter during analysis?
03:09 What are the various steps involved in any analytics project?
04:03 Which technical tools have you used for analysis and presentation purposes?
04:50 What are the best practices for data cleaning?
05:34 How can you handle missing values in a dataset?
06:54 Define normal Distribution
07:39 What is Time Series analysis?
08:31 How is joining different from blending in Tableau?
09:16 How is overfitting different from underfitting?
10:01 In MS Excel, A numeric Value can be treated as text value if it precedes with
10:29 What is the difference between COUNT, COUNTA, COUNTBLANK and COUNTIF in Excel?
11:29 Explain how VLOOKUP works in Excel?
13:21 How do you subset or filter data in SQL?
15:39 What is the difference between WHERE and HAVING clause in SQL?
17:58 Write the Python code to create an employees dataframe and display the head and summary of it.
18:46 How will you select the Department and Age columns from an Employees dataframe?
19:22 What is the criteria to say whether a developed data model is good or not?
20:08 What is the significance of Exploratory data analysis?
21:09 Explain descriptive, predictive, and prescriptive analytics.
23:01 What are the different types of sampling techniques used by data analysts?
24:45 What are the different types of Hypothesis testing?
25:42 Describe univariate, bivariate, and multivariate analysis.
29:56 write a SQL query to find the record with fourth highest market price
33:36 Create a dual axis chart in Tableau to present Sales
34:36 Design a view in Tableau to show State wise Sales
40:39 How do you write a stored procedure in SQL?
43:01 What is the difference between Tree maps and Heat maps in Tableau

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The Caltech Data Analytics Bootcamp is ideal for working professionals from all backgrounds. Develop core skills such as mastering Excel, creating data-driven presentations, data manipulation with SQL, analyzing data with Python, and data visualization with Tableau. Learn data analysis with tools such as AWS.

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- Statistical Analysis using Excel
- Data Analytics using Python
- Data Visualization with Tableau
- Linear and Logistic Regression
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