uk
Feedback
Data Analytics

Data Analytics

Відкрити в Telegram

Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data

Показати більше

📈 Аналітичний огляд Telegram-каналу Data Analytics

Канал Data Analytics (@sqlspecialist) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 109 882 підписників, посідаючи 1 111 місце в категорії Технології та додатки та 2 327 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 109 882 підписників.

За останніми даними від 01 липня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 644, а за останні 24 години на 53, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 2.53%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.75% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 2 775 переглядів. Протягом першої доби публікація в середньому набирає 1 919 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 8.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як row, sql, analytic, analyst, visualization.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data

Завдяки високій частоті оновлень (останні дані отримано 02 липня, 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 Технології та додатки.

109 882
Підписники
+5324 години
+1937 днів
+64430 день
Архів дописів
Q. Explain the data preprocessing steps in data analysis. Ans. Data preprocessing transforms the data into a format that is more easily and effectively processed in data mining, machine learning and other data science tasks. 1. Data profiling. 2. Data cleansing. 3. Data reduction. 4. Data transformation. 5. Data enrichment. 6. Data validation. Q. What Are the Three Stages of Building a Model in Machine Learning? Ans. The three stages of building a machine learning model are: Model Building: Choosing a suitable algorithm for the model and train it according to the requirement Model Testing: Checking the accuracy of the model through the test data Applying the Model: Making the required changes after testing and use the final model for real-time projects Q. What are the subsets of SQL? Ans. The following are the four significant subsets of the SQL: Data definition language (DDL): It defines the data structure that consists of commands like CREATE, ALTER, DROP, etc. Data manipulation language (DML): It is used to manipulate existing data in the database. The commands in this category are SELECT, UPDATE, INSERT, etc. Data control language (DCL): It controls access to the data stored in the database. The commands in this category include GRANT and REVOKE. Transaction Control Language (TCL): It is used to deal with the transaction operations in the database. The commands in this category are COMMIT, ROLLBACK, SET TRANSACTION, SAVEPOINT, etc. Q. What is a Parameter in Tableau? Give an Example. Ans. A parameter is a dynamic value that a customer could select, and you can use it to replace constant values in calculations, filters, and reference lines. For example, when creating a filter to show the top 10 products based on total profit instead of the fixed value, you can update the filter to show the top 10, 20, or 30 products using a parameter.

When should you use histogram?
Anonymous voting

Which chart type is perfect for showing Project timeline?
Anonymous voting

Which chart type is better choice for Viewing trends in data over time?
Anonymous voting

data-visualization-in-python-preview.pdf2.44 MB

Which chart type is perfect for Investigating the relationship between different variables.
Anonymous voting

Which of the following statement is true about KPIs and metrics?
Anonymous voting

Full form of KPIs in analytics domain?
Anonymous voting

Which situation is perfect to use bar chart?
Anonymous voting

Dashboards cannot be used to show which of the following?
Anonymous voting

Which data source is supported by Tableau and Power BI?
Anonymous voting

MySQL In a Nutshell Russell J.T. Dyer, 2008

Automated Machine Learning on AWS Trenton Potgieter, 2022

Learning Predictive Analytics with Python

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.

1.What is quick filter in tableau? Whenever using a filter in Tableau, it comes with some options to change the functionality of filter very easily, such as using it as a single value drop down or single value list or multiple value list or multiple value drop down and various other options. After we set a filter to a sheet just right click on the sheet and there you can see all the quick filter options. Changes made to these options will also change the aesthetics of filter shown on the sheet. 2.How to calculate percentage in tableau? To calculate the percentage of data on your worksheet. Go to Analysis pane and select Percentages of, there you will see a lot percentage options such as percentage of table, column, row, pane, row in pane, column in pane and cell. Select any of the above options then define the total value o which percentage is to be calculated. The option you choose will be uniform to all the rows and columns and there is no way to specify different options to rows and columns. 3. What is Power Pivot? The Power Pivot is an in-memory data modeling component. It provides highly compressed data storage with fast calculation. It helps you build a data model, relationships, creating formulas, calculated columns, Pivot Tables, and Pivot Charts from multiple resources. 4. What is x-velocity in Power Pivot? X-Velocity is the in-memory analytics engine behind Power Pivot that loads and handles huge data in Power BI. It stores data in columnar storage that results in faster processing.

Python Deep Learning Second Edition 👇 book
Python Deep Learning Second Edition 👇 book

Now that you have gained all the right skills, you need to showcase your skills and stand out from others to land a job. Projects and Portfolios will do that for you, so invest an ample amount of time in preparing these. You can find enough and more datasets in Kaggle for doing projects. Do a bit research and start working on it. Once its done, prepare an insightful resume and start applying for jobs and internships.

Free Resources for Numpy and Pandas: Codebasics Numpy playlist:  https://www.youtube.com/playlist?list=PLeo1K3hjS3uset9zIVzJWqplaWBiacTEU Codebasics pandas playlist (first 9):  https://www.youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy Freecodecamp matplotlib playlist:  https://youtu.be/3Xc3CA655Y4 Seaborn tutorials:  https://youtu.be/GcXcSZ0gQps Pandas for beginners https://t.me/datasciencefun/660 Numpy for beginners https://t.me/datasciencefree/156