Data Analyst Interview Resources
前往频道在 Telegram
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显示更多📈 Telegram 频道 Data Analyst Interview Resources 的分析概览
频道 Data Analyst Interview Resources (@dataanalystinterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 52 335 名订阅者,在 教育 类别中位列第 3 325,并在 印度 地区排名第 7 153 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 52 335 名订阅者。
根据 14 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 315,过去 24 小时变化为 16,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 2.27%。内容发布后 24 小时内通常能获得 0.96% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 189 次浏览,首日通常累积 504 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 4。
- 主题关注点: 内容集中在 sql, row, |--, dataset, visualization 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Join our telegram channel to learn how data analysis can reveal fascinating patterns, trends, and stories hidden within the numbers! 📊
For ads & suggestions: @love_data”
凭借高频更新(最新数据采集于 15 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 教育 类别中的关键影响点。
52 335
订阅者
+1624 小时
+1127 天
+31530 天
帖子存档
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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.
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1. What do you understand by the term silhouette coefficient?
The silhouette coefficient is a measure of how well clustered together a data point is with respect to the other points in its cluster. It is a measure of how similar a point is to the points in its own cluster, and how dissimilar it is to the points in other clusters. The silhouette coefficient ranges from -1 to 1, with 1 being the best possible score and -1 being the worst possible score.
2. What is the difference between trend and seasonality in time series?
Trends and seasonality are two characteristics of time series metrics that break many models. Trends are continuous increases or decreases in a metric’s value. Seasonality, on the other hand, reflects periodic (cyclical) patterns that occur in a system, usually rising above a baseline and then decreasing again.
3. What is Bag of Words in NLP?
Bag of Words is a commonly used model that depends on word frequencies or occurrences to train a classifier. This model creates an occurrence matrix for documents or sentences irrespective of its grammatical structure or word order.
4. What is the difference between bagging and boosting?
Bagging is a homogeneous weak learners’ model that learns from each other independently in parallel and combines them for determining the model average. Boosting is also a homogeneous weak learners’ model but works differently from Bagging. In this model, learners learn sequentially and adaptively to improve model predictions of a learning algorithm
5. What do you understand by the F1 score?
The F1 score represents the measurement of a model's performance. It is referred to as a weighted average of the precision and recall of a model. The results tending to 1 are considered as the best, and those tending to 0 are the worst. It could be used in classification tests, where true negatives don't matter much.
6. How to create ATS- friendly Resume?
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Repost from Star Union News
Turkey and the EU. Who needs who?
✔️Turkey has been striving to join the European Union for many years. But the EU is making more and more demands on the country. Ankara has repeatedly asked how long this will last. Asked Turkey and present the entire list of requirements.
" Now Erdogan says that the security of Europe without Turkey is impossible against the background of the weakening of the European Union. The EU is transforming it from a subject of world politics into an object whose future architecture is being worked on by world powers. Turkey is also trying to grab its own piece of the pie in this process."
For a long time, Europe kept Turkey at the door, not allowing it to join the European Union. But in the current circumstances, the situation may change." And if Turkey is still accepted in the EU, it will play a dominant role in the new European subsystem." Players like France, Poland, and many other countries will not want this. But in many ways, the possibility or impossibility of Turkey's accession to the EU (as well as the preservation of the EU itself) depends on the United States.
✔️Turkey remains a non-EU entry country. For the European Union – it is a Muslim country with a large number of inhabitants (mostly poor) and a foreign aggressive culture. The absence of the principle of homogeneity also remains valid. Therefore, Turkey will not be accepted in the EU.
Speaking about joining the EU, Erdogan has other goals. He sees that there is a sharp rise in right-wing sentiment in Europe, and the European supranational ideology is in a deep crisis. Caricature figures from the European Commission imposed an ultra-liberal agenda on Europe, which led to the strengthening of ultra-right forces. And right-wing Europeans are mostly anti-Muslim. Right-wing Europe will be hostile to Erdogan, so he offers protection to Muslim minorities.
✔️He says that if Turkey joins the EU, it could solve the problem of labor shortage, give an economic incentive, etc. With him, the Muslims of Europe will receive strong support, and Erdogan at their expense, since these people are also voters, will have an influence on internal European affairs.
Erdogan makes it clear that he will use the levers of pressure he already has on the EU. This is also the gas issue (Erdogan managed to concentrate a significant part of gas transit flows to Europe).And immigration (ability to open / close floodgates for refugees). And in the very distant future, this influence can be converted into Turkey's membership in the EU.
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Top 10 Excel Interview Questions with Answers 😄👇
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1. Question: What is the difference between CONCATENATE and "&" in Excel?
Answer: CONCATENATE and "&" both combine text, but "&" is more concise. For example,
=A1&B1 achieves the same result as =CONCATENATE(A1, B1).
2. Question: How can you freeze rows and columns simultaneously in Excel?
Answer: Use the "Freeze Panes" option under the "View" tab. Select the cell below and to the right of the rows and columns you want to freeze, and then click on "Freeze Panes."
3. Question: Explain the VLOOKUP function and when would you use it?
Answer: VLOOKUP searches for a value in the first column of a range and returns a corresponding value in the same row from another column. It's useful for looking up information in a table based on a specific criteria.
4. Question: What is the purpose of the IFERROR function?
Answer: IFERROR is used to handle errors in Excel formulas. It returns a specified value if a formula results in an error, and the actual result if there's no error.
5. Question: How do you create a PivotTable, and what is its purpose?
Answer: To create a PivotTable, select your data, go to the "Insert" tab, and choose "PivotTable." It summarizes and analyzes data in a spreadsheet, allowing you to make sense of large datasets.
6. Question: Explain the difference between relative and absolute cell references.
Answer: Relative references change when you copy a formula to another cell, while absolute references stay fixed. Use a $ symbol to make a reference absolute (e.g., $A$1).
7. Question: What is the purpose of the INDEX and MATCH functions?
Answer: INDEX returns a value in a specified range based on the row and column number, while MATCH searches for a value in a range and returns its relative position. Combined, they provide a flexible way to look up data.
8. Question: How can you find and remove duplicate values in Excel?
Answer: Use the "Remove Duplicates" feature under the "Data" tab. Select the range containing duplicates, go to "Data" -> "Remove Duplicates," and choose the columns to check for duplicates.
9. Question: Explain the difference between a workbook and a worksheet.
Answer: A workbook is the entire Excel file, while a worksheet is a single sheet within that file. Workbooks can contain multiple worksheets.
10. Question: What is the purpose of the COUNTIF function?
Answer: COUNTIF counts the number of cells within a range that meet a specified condition. For example, =COUNTIF(A1:A10, ">50") counts the cells in A1 to A10 that are greater than 50.
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Here are some interview questions for both freshers and experienced applying for a data analyst #SQL
Analyst role:
#ForFreshers:
1. What is SQL, and why is it important in data analysis?
2. Explain the difference between a database and a table.
3. What are the basic SQL commands for data retrieval?
4. How do you retrieve all records from a table named "Employees"?
5. What is a primary key, and why is it important in a database?
6. What is a foreign key, and how is it used in SQL?
7. Describe the difference between SQL JOIN and SQL UNION.
8. How do you write a SQL query to find the second-highest salary in a table?
9. What is the purpose of the GROUP BY clause in SQL?
10. Can you explain the concept of normalization in SQL databases?
11. What are the common aggregate functions in SQL, and how are they used?
For ExperiencedCandidates:
1. Describe a scenario where you had to optimize a slow-running SQL query. How did you approach it?
2. Explain the differences between SQL Server, MySQL, and Oracle databases.
3. Can you describe the process of creating an index in a SQL database and its impact on query performance?
4. How do you handle data quality issues when performing data analysis with SQL?
5. What is a subquery, and when would you use it in SQL? Give an example of a complex SQL query you've written to extract specific insights from a database.
6. How do you handle NULL values in SQL, and what are the challenges associated with them?
7. Explain the ACID properties of a database and their importance.
8. What are stored procedures and triggers in SQL, and when would you use them?
9. Describe your experience with ETL (Extract, Transform, Load) processes using SQL.
10. Can you explain the concept of query optimization in SQL, and what techniques have you used for optimization?
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Statistics Interview Questions
Topics to Cover:
• Descriptive statistics
• Probability
• Hypothesis testing
• Regression analysis
Questions and Answers:
1 Q: What is the difference between descriptive and inferential statistics?
A: Descriptive statistics summarize the main features of a dataset (e.g., mean, median, mode), while inferential statistics use samples to make inferences about a larger population.
2 Q: Define p-value in hypothesis testing.
A: The p-value is the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. A low p-value (< 0.05) indicates strong evidence against the null hypothesis.
3 Q: What is the central limit theorem?
A: The central limit theorem states that the distribution of the sample mean approximates a normal distribution as the sample size becomes large, regardless of the population's distribution.
4 Q: Explain the concept of correlation.
A: Correlation measures the strength and direction of the relationship between two variables. It ranges from -1 (perfect negative) to +1 (perfect positive), with 0 indicating no correlation.
5 Q: What is linear regression?
A: Linear regression is a statistical method for modeling the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.
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Data Analytics Interview Preparation Part-2
[Questions with Answers]
How did you get your job?
I was hired after an internship.
To get the internship, I prepared a bunch for general Python questions (LeetCode etc.) and studied the basics of machine learning (several different algorithms, how they work, when they're useful, metrics
to measure their performance, how to train them in practice etc.).
To get the internship I had to pass a technical interview as well as a take-home machine learning (ML) exercise. Then, it was just a question of doing a good job in the internship!
What are your data related responsibilities in your job?
I work on our recommendation system. It’s deep learning based. I work on a lot of features to try and
improve it (reinforcement learning & NLP etc). Since I'm in a start-up, it's also up to our team to put the models we design into production. So, after a phase of research & development and model design, in notebooks, it's time to create a real pipeline, by creating scripts.
This enables us to define, train, replace, compare and check the status of the models in production. It's basically all in Python, using Keras/TensorFlow, Pandas, Scikit-learn and NumPy. We also do a lot of analysis for the business team to help them compute metrics of interest (related to
revenue, acquisition etc.). For that, we use an external utility called Metabase. It is is hooked up to our database where we write SQL queries and visualize the results and create dashboards (using
Tableau/Looker etc).
I would say my role is quite "full-stack" since we are all involved from the phase of R&D to deployment on our cluster.
Was it difficult to get this role?
I got hired after an internship. If you come from a scientific background, it's not that hard to transition into data science. All the math is something you will probably have seen already (especially if you're
doing maths or physics). So, with some preparation and coding practice, you can start applying to internships.
It took me maybe a month or two of preparation to get some basic ideas of the typical Python data stack (Pandas, Keras, SciKit-learn etc) before I started to send out CVs. Then, if you get an internship, try your best to do the best you can and then maybe you'll be hired after!
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Data Analyst interview questions 👇
Excel:
1. Explain the difference between the "COUNT", "COUNTA", "COUNTIF", and "COUNTIFS" functions in Excel. When would you use each of these functions, and provide examples?
2. How do you create a pivot chart in Excel, and what are some advantages of using pivot charts for data visualization?
3. Describe the purpose and usage of Excel's "Solver" tool. Can you provide an example of a problem you could solve using the Solver tool?
4. How would you use Excel's "Data Validation" feature to ensure data integrity in a spreadsheet? Provide examples of different types of data validation rules you might implement.
5. What are Excel tables, and how do they differ from regular data ranges? What advantages do tables offer in terms of data management and analysis?
SQL:
1. Discuss the concept of data aggregation in SQL. How do you use aggregate functions such as SUM, AVG, MIN, and MAX to summarize data in a query?
2. Explain the difference between a primary key and a foreign key in SQL. Why are these constraints important in database design?
3. How do you handle duplicates in a SQL query result? Can you demonstrate how to remove duplicates using the DISTINCT keyword or other techniques?
4. Describe the purpose and benefits of using stored procedures in SQL databases. Provide an example of a scenario where you would use a stored procedure.
5. What is SQL injection, and how can you prevent it in your SQL queries or applications? Discuss best practices for writing secure SQL code.
Power BI:
1. How does Power BI handle data refresh and scheduling for reports and dashboards? What options are available for configuring data refresh settings?
2. Describe the concept of row-level security in Power BI. How can you implement row-level security to restrict access to specific data based on user roles or permissions?
3. What is the Power Query Editor in Power BI, and how do you use it to transform and clean data imported from different sources?
4. Discuss the benefits of using Power BI's Direct Query mode versus Import mode for connecting to data sources. When would you choose one mode over the other?
5. How do you share reports and dashboards with other users in Power BI? What options are available for distributing and collaborating on Power BI content within an organization?
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