Here is a list of Important interview questions

SQL INTERVIEW QUESTIONS WITH IMPORTANT TOPICS
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https://news.1rj.ru/str/sqlspecialist/426

Data Analyst Interview Questions
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https://news.1rj.ru/str/DataAnalystInterview/69

Python Interview Questions and Answers
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https://news.1rj.ru/str/dsabooks/96

Data Science Interview Questions
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https://news.1rj.ru/str/datasciencefun/1058

Advanced Power BI Interview Questions
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https://news.1rj.ru/str/sqlspecialist/422

DSA INTERVIEW QUESTIONS
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https://news.1rj.ru/str/crackingthecodinginterview/77

Use Chat GPT to prepare for your next INTERVIEW
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https://news.1rj.ru/str/getjobss/1483

ENJOY LEARNING 👍👍

Some tips to Sharpen Your analytical Thinking: 🤔💭

1. Use the 80/20 Rule: Identify the 20% of activities that lead to 80% of your results.

2. Master learning with the Feynman Technique: Teach others, identify gaps, & simplify.

3. "You must not fool yourself; you are the easiest person to fool." -Richard Feynman

Data Analyst Starter Kit

Data structure Cheatsheet

Different Types of Data Analyst Interview Questions
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Technical Skills: These questions assess your proficiency with data analysis tools, programming languages (e.g., SQL, Python, R), and statistical methods.

Case Studies: You might be presented with real-world scenarios and asked how you would approach and solve them using data analysis.

Behavioral Questions: These questions aim to understand your problem-solving abilities, teamwork, communication skills, and how you handle challenges.

Statistical Questions: Expect questions related to denoscriptive and inferential statistics, hypothesis testing, regression analysis, and other quantitative techniques.

Domain Knowledge: Some interviews might delve into your understanding of the specific industry or domain the company operates in.

Machine Learning Concepts: Depending on the role, you might be asked about your understanding of machine learning algorithms and their applications.

Coding Challenges: These can assess your programming skills and your ability to translate algorithms into code.

Communication: You might need to explain technical concepts to non-technical stakeholders or present your findings effectively.

Problem-Solving: Expect questions that test your ability to approach complex problems logically and analytically.

Remember, the exact questions can vary widely based on the company and the role you're applying for. It's a good idea to review the job denoscription and the company's background to tailor your preparation.

Data Analyst INTERVIEW QUESTIONS AND ANSWERS
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1.Can you name the wildcards in Excel?

Ans: There are 3 wildcards in Excel that can ve used in formulas.

Asterisk (*) – 0 or more characters. For example, Ex* could mean Excel, Extra, Expertise, etc.

Question mark (?) – Represents any 1 character. For example, R?ain may mean Rain or Ruin.

Tilde (~) – Used to identify a wildcard character (~, *, ?). For example, If you need to find the exact phrase India* in a list. If you use India* as the search string, you may get any word with India at the beginning followed by different characters (such as Indian, Indiana). If you have to look for India” exclusively, use ~.

Hence, the search string will be india~*. ~ is used to ensure that the spreadsheet reads the following character as is, and not as a wildcard.


2.What is cascading filter in tableau?

Ans: Cascading filters can also be understood as giving preference to a particular filter and then applying other filters on previously filtered data source. Right-click on the filter you want to use as a main filter and make sure it is set as all values in dashboard then select the subsequent filter and select only relevant values to cascade the filters. This will improve the performance of the dashboard as you have decreased the time wasted in running all the filters over complete data source.


3.What is the difference between .twb and .twbx extension?

Ans:
A .twb file contains information on all the sheets, dashboards and stories, but it won’t contain any information regarding data source. Whereas .twbx file contains all the sheets, dashboards, stories and also compressed data sources. For saving a .twbx extract needs to be performed on the data source. If we forward .twb file to someone else than they will be able to see the worksheets and dashboards but won’t be able to look into the dataset.


4.What are the various Power BI versions?

Power BI Premium capacity-based license, for example, allows users with a free license to act on content in workspaces with Premium capacity. A user with a free license can only use the Power BI service to connect to data and produce reports and dashboards in My Workspace outside of Premium capacity. They are unable to exchange material or publish it in other workspaces. To process material, a Power BI license with a free or Pro per-user license only uses a shared and restricted capacity. Users with a Power BI Pro license can only work with other Power BI Pro users if the material is stored in that shared capacity. They may consume user-generated information, post material to app workspaces, share dashboards, and subscribe to dashboards and reports. Pro users can share material with users who don’t have a Power BI Pro subnoscription while workspaces are at Premium capacity.

ENJOY LEARNING 👍👍

Data Analyst Interview Topics

Here are some free courses and projects to become a data analyst

Free courses:
🔥 Data Analytics Full Course 2023 | Learn Data Analytics In 11 Hours | Simplilearn by Simplilearn

Data Analyst | Data Analyst Course | Data Analytics | Data Analytics Full Course 2022 | Simplilearn by Simplilearn

Become Data Analyst by learning 1hr per day - Salary min 6 LPA 📈💻📊💰 by Learn With Lokesh Lalwani

Data Analytics Full Course 2022 | Data Analytics For Beginners | Data Analytics Course | Simplilearn by Simplilearn

Projects:

Top 5 Data Analytics Projects with Resources to Get a JOB | Projects for Beginners by Rishabh Mishra

10 PROJECTS TO ADD TO YOUR DATA PORTFOLIO by Data With Mo

The ONLY Data Analytics Portfolio You Need (GUARANTEED Job) by Learn with Lukas

SQL Data Analytics Project (PART 1) | Data Analyst Portfolio Project by techTFQ

End to End Data Analysis Project | HR Analytics Power BI Project 🚀 by codebasics

Hope it helps :)

Python Command Cheatsheet

Complete Roadmap to learn Excel in 2025 👇👇

1. Basic Excel Skills:
   - Familiarize yourself with Excel's interface and navigation.
   - Learn basic formulas (SUM, AVERAGE, COUNT, etc.).
   - Understand cell referencing (absolute vs. relative).

2. Data Entry and Formatting:
   - Practice entering and formatting data efficiently.
   - Explore cell formatting options for a clean and organized dataset.

3. Advanced Formulas:
   - Master more advanced formulas like VLOOKUP, HLOOKUP, INDEX-MATCH.
   - Learn logical functions (IF, AND, OR).
   - Understand array formulas for complex calculations.

4. Pivot Tables:
   - Gain proficiency in creating Pivot Tables for data summarization.
   - Learn to customize and format Pivot Tables effectively.

5. Data Cleaning:
   - Acquire skills in cleaning and transforming data.
   - Explore text-to-columns, remove duplicates, and data validation.

6. Charts and Graphs:
   - Learn to create various charts (bar, line, pie) for data visualization.
   - Understand chart formatting and customization.

7. Dashboard Creation:
   - Combine charts and tables to build basic dashboards.
   - Explore dynamic dashboards using Excel features.

8. Macros and VBA:
   - Dive into basic automation using Excel macros.
   - Learn Visual Basic for Applications (VBA) for more advanced automation.

9. Power Query:
   - Introduce yourself to Power Query for enhanced data manipulation.
   - Learn to import, transform, and load data efficiently.

10. Advanced Excel Techniques:
   - Explore advanced features like Goal Seek, Solver, and Scenario Manager.
   - Master the use of data tables for sensitivity analysis.

11. Real-world Projects:
   - Apply your skills to real-world projects or datasets.
   - Practice solving analytical problems using Excel.
Remember to practice consistently, as hands-on experience is crucial for mastering Excel. This roadmap will provide a solid foundation for your journey into data analysis using Excel.

5️⃣ Free resources to practice Excel

https://www.w3schools.com/EXCEL/index.php

https://bit.ly/3PSorPT

http://learn.microsoft.com/en-gb/training/paths/modern-analytics/

https://news.1rj.ru/str/excel_analyst/52

https://excel-practice-online.com/

Join for more: https://news.1rj.ru/str/free4unow_backup

ENJOY LEARNING 👍👍

SQL Interview Questions

✅ Basic Level (Focuses on fundamental concepts and operations in SQL, including syntax, basic commands, and the definitions of key terms.)

1. Explain the difference between drop and truncate.
2. What are Constraints in SQL?
3. Describe the use of the SELECT statement in SQL.
4. What is a primary key in SQL?
5. Explain the difference between CHAR and VARCHAR data types in SQL.
6. What is a foreign key in SQL?
7. How do you use the GROUP BY statement in SQL?
8. What is a JOIN in SQL, and can you describe a scenario where you would use it?
9. How does the WHERE clause work in SQL?
10. Explain the use of the INSERT statement in SQL.

✅Intermediate Level ( Involves more complex queries, including the use of sub-queries, joins, and functions. It requires a deeper understanding of SQL for data manipulation and analysis.)

1. Describe the Difference Between Window Functions and Aggregate Functions in SQL.
2. Write a SQL query to find the top three products with the highest revenue in the last quarter from a sales database.
3. What do you understand by sub-queries in SQL?
4. What is CTE in SQL?
5. Explain the use of the HAVING clause in SQL.
6. How do you implement pagination in SQL queries?
7. Describe the differences between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.
8. Explain the concept of indexing in SQL and its benefits.
9. How can you prevent SQL injection in your queries?
10. Write a SQL query to find the second highest salary in a given table.

✅ Advanced Level (Covers topics related to database optimization, advanced data manipulation techniques, and understanding SQL's impact on database performance and design.)

1. Describe a SQL query challenge you faced related to optimizing database performance.
2. What is a Recursive Stored Procedure in SQL?
3. What are the subsets of SQL?
4. How do you use window functions for running totals and moving averages?
5. Explain the process and considerations for denormalizing a database.
6. Discuss the implications and solutions for dealing with NULL values in SQL operations.
7. How do you handle large datasets and optimize queries for big data in SQL?
8. Describe how to implement transaction control in SQL and its importance.
9. Explain the concept of materialized views in SQL and their use cases.
10. Discuss strategies for database sharding and partitioning in SQL and their impact on performance.

Can you use Chat GPT as a data analyst?

The answer to this question is yes, but you need to be cautious about using Chat GPT on the job (and even while learning analytics) for the following reasons.

1. Chat GPT gets things wrong. A lot.

If you use Chat GPT to write code, you better know that coding language extremely well, because you gotta be able to fact check and alter the response you get from Chat GPT.

For this reason, I would recommend staying away from Chat GPT when you’re learning SQL, Python, etc so you thoroughly learn the code without becoming dependent on AI.

2. You absolutely CANNOT paste company data into Chat GPT

As data analysts we work with highly confidential data that we must exercise great caution to protect.

For this reason, no matter how secure Chat GPT says it is, you must never paste company data into the application.

3. Some companies and bosses may not allow the use of Chat GPT

This is a reality in the world of tech and data since the avalanche of AI tools and features over the last couple years.

I’ve heard of some companies that block Chat GPT altogether, and some managers who advise against using it out of fears for security and other reasons.

Given all three of these reasons, feel free to play around with Chat GPT and AI and learn about them, but don’t become overly dependent on these tools.

Data Storytelling

Essential Python and SQL topics for data analysts 😄👇

Python Topics:

Python Resources - @pythonanalyst

1. Data Structures
   - Lists, Tuples, and Dictionaries
   - NumPy Arrays for numerical data

2. Data Manipulation
   - Pandas DataFrames for structured data
   - Data Cleaning and Preprocessing techniques
   - Data Transformation and Reshaping

3. Data Visualization
   - Matplotlib for basic plotting
   - Seaborn for statistical visualizations
   - Plotly for interactive charts

4. Statistical Analysis
   - Denoscriptive Statistics
   - Hypothesis Testing
   - Regression Analysis

5. Machine Learning
   - Scikit-Learn for machine learning models
   - Model Building, Training, and Evaluation
   - Feature Engineering and Selection

6. Time Series Analysis
   - Handling Time Series Data
   - Time Series Forecasting
   - Anomaly Detection

7. Python Fundamentals
   - Control Flow (if statements, loops)
   - Functions and Modular Code
   - Exception Handling
   - File

SQL Topics:

SQL Resources - @sqlanalyst

1. SQL Basics
- SQL Syntax
- SELECT Queries
- Filters

2. Data Retrieval
- Aggregation Functions (SUM, AVG, COUNT)
- GROUP BY

3. Data Filtering
- WHERE Clause
- ORDER BY

4. Data Joins
- JOIN Operations
- Subqueries

5. Advanced SQL
- Window Functions
- Indexing
- Performance Optimization

6. Database Management
- Connecting to Databases
- SQLAlchemy

7. Database Design
- Data Types
- Normalization

Remember, it's highly likely that you won't know all these concepts from the start. Data analysis is a journey where the more you learn, the more you grow. Embrace the learning process, and your skills will continually evolve and expand. Keep up the great work!

Share with credits: https://news.1rj.ru/str/sqlspecialist

Hope it helps :)