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Data Analyst Interview Resources

Data Analyst Interview Resources

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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

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📈 Аналітичний огляд Telegram-каналу Data Analyst Interview Resources

Канал Data Analyst Interview Resources (@dataanalystinterview) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 52 250 підписників, посідаючи 3 377 місце в категорії Освіта та 6 598 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 52 250 підписників.

За останніми даними від 05 листопада, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на -326, а за останні 24 години на -9, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 2.40%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.70% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 1 254 переглядів. Протягом першої доби публікація в середньому набирає 364 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 2.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як sql, row, |--, dataset, visualization.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“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”

Завдяки високій частоті оновлень (останні дані отримано 06 листопада, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

52 250
Підписники
-924 години
-447 днів
-32630 днів
Архів дописів
Top 20 #SQL INTERVIEW QUESTIONS 1️⃣ Explain Order of Execution of SQL query 2️⃣ Provide a use case for each of the functions Rank, Dense_Rank & Row_Number ( 💡 majority struggle ) 3️⃣ Write a query to find the cumulative sum/Running Total 4️⃣ Find the Most selling product by sales/ highest Salary of employees 5️⃣ Write a query to find the 2nd/nth highest Salary of employees 6️⃣ Difference between union vs union all 7️⃣ Identify if there any duplicates in a table 8️⃣ Scenario based Joins question, understanding of Inner, Left and Outer Joins via simple yet tricky question 9️⃣ LAG, write a query to find all those records where the transaction value is greater then previous transaction value 1️⃣ 0️⃣ Rank vs Dense Rank, query to find the 2nd highest Salary of employee ( Ideal soln should handle ties) 1️⃣ 1️⃣ Write a query to find the Running Difference (Ideal sol'n using windows function) 1️⃣ 2️⃣ Write a query to display year on year/month on month growth 1️⃣ 3️⃣ Write a query to find rolling average of daily sign-ups 1️⃣ 4️⃣ Write a query to find the running difference using self join (helps in understanding the logical approach, ideally this question is solved via windows function) 1️⃣ 5️⃣ Write a query to find the cumulative sum using self join (you can use windows function to solve this question) 1️⃣6️⃣ Differentiate between a clustered index and a non-clustered index? 1️⃣7️⃣ What is a Candidate key? 1️⃣8️⃣What is difference between Primary key and Unique key? 1️⃣9️⃣What's the difference between RANK & DENSE_RANK in SQL? 2️⃣0️⃣ Whats the difference between LAG & LEAD in SQL? Access SQL Learning Series for Free: https://t.me/sqlspecialist/523 Hope it helps :)

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Python Tips and Tricks.pdf8.45 MB

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Best YouTube Channels to Learn Data Analytics
Best YouTube Channels to Learn Data Analytics

Today's Interview QnAs Date - 25/01/2024 Company - The Math Company Role- Data Analyst 1.How to create filters in Power BI? Filters are an integral part of Power BI reports. They are used to slice and dice the data as per the dimensions we want. Filters are created in a couple of ways. Using Slicers: A slicer is a visual under Visualization Pane. This can be added to the design view to filter our reports. When a slicer is added to the design view, it requires a field to be added to it. For example- Slicer can be added for Country fields. Then the data can be filtered based on countries. Using Filter Pane: The Power BI team has added a filter pane to the reports, which is a single space where we can add different fields as filters. And these fields can be added depending on whether you want to filter only one visual(Visual level filter), or all the visuals in the report page(Page level filters), or applicable to all the pages of the report(report level filters) 2.How to sort data in Power BI? Sorting is available in multiple formats. In the data view, a common sorting option of alphabetical order is there. Apart from that, we have the option of Sort by column, where one can sort a column based on another column. The sorting option is available in visuals as well. Sort by ascending and descending option by the fields and measure present in the visual is also available. 3.How to convert pdf to excel? Open the PDF document you want to convert in XLSX format in Acrobat DC. Go to the right pane and click on the “Export PDF” option. Choose spreadsheet as the Export format. Select “Microsoft Excel Workbook.” Now click “Export.” Download the converted file or share it. 4. How to enable macros in excel? Click the file tab and then click “Options.” A dialog box will appear. In the “Excel Options” dialog box, click on the “Trust Center” and then “Trust Center Settings.” Go to the “Macro Settings” and select “enable all macros.” Click OK to apply the macro settings.

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𝐇𝐨𝐰 𝐭𝐨 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐞 𝐝𝐚𝐭𝐚 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 𝐚𝐬 𝐚𝐧 𝐚𝐬𝐩𝐢𝐫𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 𝐚𝐧𝐚𝐥𝐲𝐬𝐭? Here's a step-by-step guide for the same: Step 1️⃣ - Download a practice dataset. I'd recommend the Codebasics resume project challenge dataset (as it contains multi-table datasets). Step 2️⃣ - Open your preferred RDBMS tool (SQL server/MySQL). Create a local database to load the dataset. Step 3️⃣ - Import the practice dataset (.xlsx/.csv) into this database by creating the tables (please google if you need help). Step 4️⃣ - Now open Power BI desktop and connect to the local database using the appropriate connector. Step 5️⃣ - Build the dashboard using the questions shared in the resume project challenge. Step 6️⃣ - Now, you can validate the output of your dashboard by writing SQL queries. Step 7️⃣ - Try to write an SQL query for a question asked in the challenge. You need to convert a natural language question into an SQL query. Step 8️⃣ - Compare the query output with the dashboard output and check if the numbers are matching. If they aren't matching, either the query is wrong or the dashboard numbers are wrong. Hence, try to identify the gap. Step 9️⃣ - Repeat the process for every question asked in the challenge. Thus, you will learn and practice both SQL and Power BI simultaneously. 𝐖𝐡𝐲 𝐬𝐡𝐨𝐮𝐥𝐝 𝐲𝐨𝐮 𝐭𝐫𝐲 𝐭𝐡𝐢𝐬 𝐦𝐞𝐭𝐡𝐨𝐝? In real-world scenarios, 𝐝𝐚𝐭𝐚 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 is a very important step in every analytics project. One needs to compare the output of the report/dashboard with the data source and then launch it for usage, to avoid discrepancies. This will help you weed out any mistakes that you have applied in your report/dashboard logic.

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If you have ever given an SQL interview some of the questions would be definitely from below list : 1- How to find duplicates in a table 2- How to delete duplicates from a table 3- Difference between union and union all 4- Difference between rank,row_number and dense_rank 5- Find records in a table which are not present in another table 6- Find second highest salary employees in each department 7- Find employees with salary more than their manager's salary 8- Difference between inner and left join 9- update a table and swap gender values. If not exact at least flavor of these questions are always asked in interviews irrespective of your experience level

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Numerical Methods with Python William Miles, 2023

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4 Types of Data Analytics
4 Types of Data Analytics