Python Interview Questions for Data/Business Analysts:

Question 1:
Given a dataset in a CSV file, how would you read it into a Pandas DataFrame? And how would you handle missing values?

Question 2:
Describe the difference between a list, a tuple, and a dictionary in Python. Provide an example for each.

Question 3:
Imagine you are provided with two datasets, 'sales_data' and 'product_data', both in the form of Pandas DataFrames. How would you merge these datasets on a common column named 'ProductID'?

Question 4:
How would you handle duplicate rows in a Pandas DataFrame? Write a Python code snippet to demonstrate.

Question 5:
Describe the difference between '.iloc[] and '.loc[]' in the context of Pandas.

Question 6:
In Python's Matplotlib library, how would you plot a line chart to visualize monthly sales? Assume you have a list of months and a list of corresponding sales numbers.

Question 7:
How would you use Python to connect to a SQL database and fetch data into a Pandas DataFrame?

Question 8:
Explain the concept of list comprehensions in Python. Can you provide an example where it's useful for data analysis?

Question 9:
How would you reshape a long-format DataFrame to a wide format using Pandas? Explain with an example.

Question 10:
What are lambda functions in Python? How are they beneficial in data wrangling tasks?

Question 11:
Describe a scenario where you would use the 'groupby()' method in Pandas. How would you aggregate data after grouping?

Question 12:
You are provided with a Pandas DataFrame that contains a column with date strings. How would you convert this column to a datetime format? Additionally, how would you extract the month and year from these datetime objects?

Question 13:
Explain the purpose of the 'pivot_table' method in Pandas and describe a business scenario where it might be useful.

Question 14:
How would you handle large datasets that don't fit into memory? Are you familiar with Dask or any similar libraries?

Python Interview Q&A: https://topmate.io/coding/898340

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Business Analyst → Bridge Between Strategy and Data
Aligns business goals with insights
Uses Excel, SQL, Tableau, and domain knowledge
Answers “Why did this happen?”

Example: Analyzing customer churn and recommending solutions.

Data Scientist → Predicts Future Trends
Uses machine learning and analytics
Works with Python, R, and AI models
Answers “What’s next?”

Example: Forecasting sales based on past data.

Gamecrio Studios is hiring Business Analyst 🚀

Qualification : Bachelor's degree
Experience : 0-2 Years
Location : Ahmedabad

Apply link : Check out this job at Gamecrio Studios Pvt Ltd.: https://www.linkedin.com/jobs/view/4162966294

Business Analytics vs Data Analytics

STEM is hiring Junior Business Analyst 🚀

Qualification : Bachelor's degree
Experience : Freshers / Experienced
Location : Gurugram

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SQL Questions

Business Analyst vs Data Analyst

Majority of top companies hiring for analytic roles (Data Analyst/Business Analyst) focus heavily on SQL understanding as a selection criteria, which according to me, should be the first thing you start your preparation with.

I have divided this SQL roadmap into 3 steps (Basics, Level Up & Practice), and it should take around 1 month to complete.

Step 1 - Basics 🔢 :

➡What is a Relational Database / RDBMS?
➡SQL Data Types - Varchar, text, int, number, date, float, boolean.
➡SQL commands - select, where, like, distinct, between, group by, having, order by, insert into, case when, update, truncate, delete, commit, rollback (basically all the DDL, DML, DCL, TCL commands in SQL).
➡Integrity Constraints - Primary key, foreign key, not null, unique.
➡Operators arithmetic, logical, and comparison operations.
➡Use of distinct, order by, limit, and top.
➡Use of union and union all.
➡Joins in SQL inner, left, right, outer, self, full outer, cross join.


Step 2 - Level up ⬆⬆ :

➡Normalization in SQL
➡Aggregate, date, and string functions
➡Sub-Queries
➡CTE table / with clause
➡In-built SQL functions
➡Window functions
➡Views


Step 3 - Practice SQL Questions on leetcode & hackerrank ✅

Hope it helps :)

Microsoft Excel is used by 99% of the World’s businesses.

But the truth is most people don't know how to use it.

10 must-have Excel skills to accelerate your career:

1. Wildcards
2. XLookup
3. Sparklines
4. Remove duplicates
5. Flash Fill
6. Transpose
7. Trim
8. Pivot tables
9. Upper, lower, proper case
10. Stock market data

Most people suck at using Microsoft Excel.

I'm not talking about formatting data/reports or writing formulas.

I'm talking about using Excel to analyze data and make an impact.

Here are 7 ways to stand out from the crowd:

1) Don't make PivotTables your hammer and every problem a nail.

PivotTables are like any other data analysis technique.

They have pros and cons.

Tables are good primarily at two things:

Looking up exact values
Comparing exact values

This alone is not enough for most analyses.

2) Use more charts.

Humans are visual creatures, and we can use this to analyze data.

The best use of PivotTables is to create PivotCharts.

For example, bar charts that use three or more columns of data.

It's way more powerful than a PivotTable.

3) Use line charts.

I can't stress this one enough.

The single most valuable data visualization in business analytics is a line chart.

Line charts allow you to see:

Trends
Variability
Cycles
Rate of change
Exceptions

Oh, and make sure to use line charts in your dashboards!

4) Learn data analysis fundamentals.

Microsoft Excel can be a potent tool - if you know how to analyze data.

Here are two fundamentals that 99% of Excel users don't know:

Distribution analysis
Correlation analysis

While this sounds scary, it isn't.

No fancy math is required.

5) Time to step up to PowerQuery.

It's a crying shame PowerQuery isn't more popular.

It's exceedingly powerful (pun intended) and allows you to automate many steps in your data analyses.

In 2025, however, PowerQuery is more critical than ever because of the following three words.

6) Python in Excel

Shortly, there will be two kinds of Excel users:

Those who use Python in Excel to have an impact at work using DIY data science.

Those that do not.

BTW - If you're the first kind of Excel user, you can make the most of AI by...

7) Use Copilot in Excel with Python

I'm going to be honest.

Vanilla Copilot in Excel isn't very impressive.

However, using the Copilot AI to generate Python code for DIY data science is a different story.

But you must have DIY data science skills to use Copliot, or you're playing with 🔥.

Free Excel Resources: https://news.1rj.ru/str/excel_data

📊 Decoding Business Metrics: Median vs. Average! 🧐

Ever wondered whether to use the average (mean) or the median when presenting your business data? 🤔

While the average is a common go-to (add everything up and divide by the count 🔢), it can sometimes paint a misleading picture, especially when your data has some serious outliers! 😬

Think about it: Imagine a company's sales team where a few top performers have HUGE numbers, while the majority have more moderate results. The average might be inflated by those high-flyers, not truly reflecting the typical sales performance. 📈

➡️ That's where the median shines! ✨ The median is the middle value when your data is ordered. It's not affected by extreme highs or lows, giving you a more accurate representation of the "typical" data point. 🎯

When might the median be your MVP? 👇
* 💰 Salary distributions: A few executive salaries can heavily skew the average. The median gives a better sense of the typical employee's earnings.
* 🏘️ Real estate prices: One or two ultra-luxury homes won't drastically impact the median price in an area.
* 🛒 Customer spending: A few very large purchases might inflate the average order value, while the median shows the more common spending amount.

So, next time you're presenting business metrics, take a moment to consider your data's distribution. If you suspect skewness, the median might be your secret weapon for a more truthful and insightful representation! 💡

#businessanalysts

Excel interview questions for both data analysts and business analysts

1) What are the basic functions of Microsoft Excel?
2) Explain the difference between a workbook and a worksheet.
3) How would you freeze panes in Excel?
4) Can you name some common keyboard shortcuts in Excel?
5) What is the purpose of VLOOKUP and HLOOKUP?
7) How do you remove duplicate values in Excel?
8) Explain the steps to filter data in Excel.
9) What is the significance of the "IF" function in Excel, and can you provide an example of its use?
10) How would you create a pivot table in Excel?
11) Explain the use of the CONCATENATE function in Excel.
12) How do you create a chart in Excel?
13) Explain the difference between a line chart and a scatter plot.
14) What is conditional formatting, and how can it be applied in Excel?
15) How would you create a dynamic chart that updates with new data?
16) What is the INDEX-MATCH function, and how is it different from VLOOKUP?
17) Can you explain the concept of "PivotTables" and when you would use them?
18) How do you use the "COUNTIF" and "SUMIF" functions in Excel?
19) Explain the purpose of the "What-If Analysis" tools in Excel.
20) What are array formulas, and can you provide an example of their use?

Business Analysis Specific:

1) How would you analyze a set of sales data to identify trends and insights?
2) Explain how you might use Excel to perform financial modeling.
3) What Excel features would you use for forecasting and budgeting?
4) How do you handle large datasets in Excel, and what tools or techniques do you use for optimization?
5) What are some common techniques for cleaning and validating data in Excel?
6) How do you identify and handle errors in a dataset using Excel?

Scenario-based Questions:

1) Imagine you have a dataset with missing values. How would you approach this problem in Excel?
2) You are given a dataset with multiple sheets. How would you consolidate the data for analysis?

I have curated top-notch Data Analytics Resources 👇👇
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Business Analyst Interview Questions and Answers
👇👇

1. What is analysis in tableau?

Ans: Tableau comes with inbuilt features to analyze the data plotted on a chart. We have various tools such as adding an average line to the chart which tableau calculates itself after we drop the tool on the chart. Some other features include clustering, percentages, forming bands of a particular range and various other tools to explore and inspect data. All these tools are available in analyze tab on each sheet used to create any chart. The features become visible only when they are applicable to the worksheet.


2.How to create sets in tableau?

Ans: Sets are custom fields used to compare and ask questions about a subset of data. For creating a set on dimension, right-click on a dimension in data pane and select create -> set. In general tab select the fields that will be considered for computing the set. Specify the conditions to create set in conditions tab and you also have the option to select top N members in dataset based on any field in the top tab. When a set is created it divides the measure into two parts namely in and out of the set based on the conditions applied by the user.


3.Why and how would you use a custom visual file?

A custom visual file is used when none of the pre existing visuals fit the business needs. Custom visual files are generally created by Developers which can be used in the same way as prepackaged files.


4. What are the various type of users who can use Power BI?

Ans: PowerBI can be used by anyone for their requirements but there is a particular group of users who are more likely to use it:

Report Consumers: They consume the reports based on a specific information they need

Report Analyst: Report Analysts need detailed data for their analysis from the reports

Self Service Data Analyst: They are more experienced business data users. They have an in-depth understanding of the data to work with.

Basic Data Analyst: They can build their own datasets and are experienced in PowerBI Service

Advanced Data Analyst: They know how to write SQL Queries and have hands-on experience on PowerBI. They have experience in Advanced PowerBI with DAX training and data modelling.

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Majority of top companies hiring for analytic roles (Data Analyst/Business Analyst) focus heavily on SQL understanding as a selection criteria, which according to me, should be the first thing you start your preparation with.

I have divided this SQL roadmap into 3 steps (Basics, Level Up & Practice), and it should take around 1 month to complete.

Step 1 - Basics 🔢 :

➡What is a Relational Database / RDBMS?
➡SQL Data Types - Varchar, text, int, number, date, float, boolean.
➡SQL commands - select, where, like, distinct, between, group by, having, order by, insert into, case when, update, truncate, delete, commit, rollback (basically all the DDL, DML, DCL, TCL commands in SQL).
➡Integrity Constraints - Primary key, foreign key, not null, unique.
➡Operators arithmetic, logical, and comparison operations.
➡Use of distinct, order by, limit, and top.
➡Use of union and union all.
➡Joins in SQL inner, left, right, outer, self, full outer, cross join.


Step 2 - Level up ⬆⬆ :

➡Normalization in SQL
➡Aggregate, date, and string functions
➡Sub-Queries
➡CTE table / with clause
➡In-built SQL functions
➡Window functions
➡Views


Step 3 - Practice SQL Questions on leetcode & hackerrank ✅

Hope it helps :)

Business Analyst vs Data Analyst

Business Analyst Interview Questions and Answers
👇👇

1. What is analysis in tableau?

Ans: Tableau comes with inbuilt features to analyze the data plotted on a chart. We have various tools such as adding an average line to the chart which tableau calculates itself after we drop the tool on the chart. Some other features include clustering, percentages, forming bands of a particular range and various other tools to explore and inspect data. All these tools are available in analyze tab on each sheet used to create any chart. The features become visible only when they are applicable to the worksheet.


2.How to create sets in tableau?

Ans: Sets are custom fields used to compare and ask questions about a subset of data. For creating a set on dimension, right-click on a dimension in data pane and select create -> set. In general tab select the fields that will be considered for computing the set. Specify the conditions to create set in conditions tab and you also have the option to select top N members in dataset based on any field in the top tab. When a set is created it divides the measure into two parts namely in and out of the set based on the conditions applied by the user.


3.Why and how would you use a custom visual file?

A custom visual file is used when none of the pre existing visuals fit the business needs. Custom visual files are generally created by Developers which can be used in the same way as prepackaged files.


4. What are the various type of users who can use Power BI?

Ans: PowerBI can be used by anyone for their requirements but there is a particular group of users who are more likely to use it:

Report Consumers: They consume the reports based on a specific information they need

Report Analyst: Report Analysts need detailed data for their analysis from the reports

Self Service Data Analyst: They are more experienced business data users. They have an in-depth understanding of the data to work with.

Basic Data Analyst: They can build their own datasets and are experienced in PowerBI Service

Advanced Data Analyst: They know how to write SQL Queries and have hands-on experience on PowerBI. They have experience in Advanced PowerBI with DAX training and data modelling.

McKinsey hiring Business Analyst

Apply link: https://www.mckinsey.com/careers/search-jobs/jobs/businessanalyst-15136

👉WhatsApp Channel: https://whatsapp.com/channel/0029Vaxjq5a4dTnKNrdeiZ0J

👉Telegram Link: https://news.1rj.ru/str/addlist/4q2PYC0pH_VjZDk5

All the best 👍👍

Must important topics to look before any excel interview for Data/Business Analyst role :-

Data Handling: Cell formatting, rows/columns, basic functions (SUM, AVERAGE, COUNT etc).

Data Management Mastery: Sorting, filtering, data validation, diverse cell references. Function Proficiency: Explore SUMIF, (V & X)LOOKUP, INDEX, MATCH, IF, and advanced function nesting.

Advanced Analytics: Master PivotTables for dynamic data analysis and various chart creation.

Advanced Analysis Techniques: Conditional formatting, goal-seeking, in-depth what-if analysis.

Advanced Functions: COUNTIF/IFS, SUMIFS, AVERAGEIF/IFS, CONCATENATE, date/time functions.

These are the most important one's which I tried to summarise in the best possible way, please let me know in the comments if I have missed something important.