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Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

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Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun

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๐Ÿ“ˆ Analytical overview of Telegram channel Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

Channel Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) in the English language segment is an active participant. Currently, the community unites 51 852 subscribers, ranking 3 362 in the Education category and 7 262 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 51 852 subscribers.

According to the latest data from 14 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 525 over the last 30 days and by 20 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.70%. Within the first 24 hours after publication, content typically collects 1.28% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 3 991 views. Within the first day, a publication typically gains 665 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
  • Thematic interests: Content is focused on key topics such as analyst, |--, excel, visualization, analytic.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œData Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfunโ€

Thanks to the high frequency of updates (latest data received on 15 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

51 852
Subscribers
+2024 hours
+1377 days
+52530 days
Posts Archive
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๐—™๐—ฅ๐—˜๐—˜ ๐—ฅ๐—ฒ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ๐˜€ ๐˜๐—ผ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€! ๐Ÿ“Š๐Ÿš€ Want to master data analytics? Here are top free courses, books, and certifications to help you get started with Power BI, Tableau, Python, and Excel. ๐‹๐ข๐ง๐ค๐Ÿ‘‡ https://pdlink.in/41Fx3PW All The Best ๐Ÿ’ฅ

Goldman Sachs senior data analyst interview asked questions SQL 1 find avg of salaries department wise from table 2 Write a SQL query to see employee name and manager name using a self-join on 'employees' table with columns 'emp_id', 'name', and 'manager_id'. 3 newest joinee for every department (solved using lead lag) POWER BI 1. What does Filter context in DAX mean? 2. Explain how to implement Row-Level Security (RLS) in Power BI. 3. Describe different types of filters in Power BI. 4. Explain the difference between 'ALL' and 'ALLSELECTED' in DAX. 5. How do you calculate the total sales for a specific product using DAX? PYTHON 1. Create a dictionary, add elements to it, modify an element, and then print the dictionary in alphabetical order of keys. 2. Find unique values in a list of assorted numbers and print the count of how many times each value is repeated. 3. Find and print duplicate values in a list of assorted numbers, along with the number of times each value is repeated. I have curated best 80+ top-notch Data Analytics Resources ๐Ÿ‘‡๐Ÿ‘‡ https://t.me/DataSimplifier Hope this helps you ๐Ÿ˜Š

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Essential Topics to Master Data Science Interviews: ๐Ÿš€ SQL: 1. Foundations - Craft SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING - Embrace Basic JOINS (INNER, LEFT, RIGHT, FULL) - Navigate through simple databases and tables 2. Intermediate SQL - Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN) - Embrace Subqueries and nested queries - Master Common Table Expressions (WITH clause) - Implement CASE statements for logical queries 3. Advanced SQL - Explore Advanced JOIN techniques (self-join, non-equi join) - Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag) - Optimize queries with indexing - Execute Data manipulation (INSERT, UPDATE, DELETE) Python: 1. Python Basics - Grasp Syntax, variables, and data types - Command Control structures (if-else, for and while loops) - Understand Basic data structures (lists, dictionaries, sets, tuples) - Master Functions, lambda functions, and error handling (try-except) - Explore Modules and packages 2. Pandas & Numpy - Create and manipulate DataFrames and Series - Perfect Indexing, selecting, and filtering data - Handle missing data (fillna, dropna) - Aggregate data with groupby, summarizing data - Merge, join, and concatenate datasets 3. Data Visualization with Python - Plot with Matplotlib (line plots, bar plots, histograms) - Visualize with Seaborn (scatter plots, box plots, pair plots) - Customize plots (sizes, labels, legends, color palettes) - Introduction to interactive visualizations (e.g., Plotly) Excel: 1. Excel Essentials - Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.) - Dive into charts and basic data visualization - Sort and filter data, use Conditional formatting 2. Intermediate Excel - Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF) - Leverage PivotTables and PivotCharts for summarizing data - Utilize data validation tools - Employ What-if analysis tools (Data Tables, Goal Seek) 3. Advanced Excel - Harness Array formulas and advanced functions - Dive into Data Model & Power Pivot - Explore Advanced Filter, Slicers, and Timelines in Pivot Tables - Create dynamic charts and interactive dashboards Power BI: 1. Data Modeling in Power BI - Import data from various sources - Establish and manage relationships between datasets - Grasp Data modeling basics (star schema, snowflake schema) 2. Data Transformation in Power BI - Use Power Query for data cleaning and transformation - Apply advanced data shaping techniques - Create Calculated columns and measures using DAX 3. Data Visualization and Reporting in Power BI - Craft interactive reports and dashboards - Utilize Visualizations (bar, line, pie charts, maps) - Publish and share reports, schedule data refreshes Statistics Fundamentals: - Mean, Median, Mode - Standard Deviation, Variance - Probability Distributions, Hypothesis Testing - P-values, Confidence Intervals - Correlation, Simple Linear Regression - Normal Distribution, Binomial Distribution, Poisson Distribution. Show some โค๏ธ if you're ready to elevate your data science journey! ๐Ÿ“Š ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

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โœ… ๐‡๐จ๐ฐ ๐ญ๐จ ๐๐ฎ๐ข๐ฅ๐ ๐š ๐‚๐š๐ซ๐ž๐ž๐ซ ๐š๐ฌ ๐š ๐ƒ๐š๐ญ๐š ๐€๐ง๐š๐ฅ๐ฒ๐ฌ๐ญ ๐ข๐ง ๐Ÿ๐ŸŽ๐Ÿ๐Ÿ“ ๐Ÿง‘โ€๐Ÿ’ป If you are thinking about becoming a data analyst, 2025 is the perfect year to start. Companies need people who can understand data and turn it into useful insights. Hereโ€™s a simple step-by-step guide to help you start your journey. ๐Ÿ. ๐ƒ๐š๐ญ๐š ๐€๐ง๐š๐ฅ๐ฒ๐ฌ๐ญ ๐‘๐จ๐ฅ๐ž A data analyst collects and studies data to help companies make better decisions. They find trends, create reports, and suggest solutions to business problems. ๐Ÿ. ๐‹๐ž๐š๐ซ๐ง ๐๐ž๐œ๐ž๐ฌ๐ฌ๐š๐ซ๐ฒ ๐’๐ค๐ข๐ฅ๐ฅ๐ฌ ๐„๐ฑ๐œ๐ž๐ฅ: Start with PivotTables, VLOOKUP, and creating dashboards. ๐’๐๐‹: Master queries to extract and manipulate data. ๐ƒ๐š๐ญ๐š ๐•๐ข๐ฌ๐ฎ๐š๐ฅ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง ๐“๐จ๐จ๐ฅ๐ฌ: Learn Power BI and Tableau to present insights effectively. ๐๐ฒ๐ญ๐ก๐จ๐ง: Focus on libraries like Pandas, NumPy, Matplotlib, and Seaborn. ๐’๐ญ๐š๐ญ๐ข๐ฌ๐ญ๐ข๐œ๐ฌ: Basic concepts- mean, median, mode, standard deviation, regression. ๐Ÿ‘. ๐–๐จ๐ซ๐ค ๐จ๐ง ๐๐ซ๐จ๐ฃ๐ž๐œ๐ญ๐ฌ https://t.me/sqlproject https://t.me/pythonspecialist ๐Ÿ’. ๐†๐š๐ข๐ง ๐‚๐ž๐ซ๐ญ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง Certifications add credibility to your resume. Some popular ones include: Google Data Analytics Professional Certificate Microsoft Certified: Data Analyst Associate Tableau Desktop Specialist Certification ๐Ÿ“. ๐‚๐ซ๐ž๐š๐ญ๐ž ๐๐จ๐ซ๐ญ๐Ÿ๐จ๐ฅ๐ข๐จ ๐‹๐ข๐ง๐ค๐ž๐๐ˆ๐ง: Treat your LinkedIn profile as your portfolio. Update it with skills, certifications, and projects. ๐†๐ข๐ญ๐‡๐ฎ๐›: Add links to your GitHub repositories with coding projects and Power BI/Tableau dashboards. ๐Ÿ”. ๐†๐š๐ข๐ง ๐๐ซ๐š๐œ๐ญ๐ข๐œ๐š๐ฅ ๐„๐ฑ๐ฉ๐ž๐ซ๐ข๐ž๐ง๐œ๐ž (๐…๐จ๐ซ ๐…๐ซ๐ž๐ฌ๐ก๐ž๐ซ๐ฌ) If you're a fresher, here are some ideas to gain experience: ๐ˆ๐ง๐ญ๐ž๐ซ๐ง๐ฌ๐ก๐ข๐ฉ๐ฌ: Apply for internships at companies where you can work on real data problems. ๐…๐ซ๐ž๐ž๐ฅ๐š๐ง๐œ๐ข๐ง๐ : Offer data analysis services on platforms like Upwork, Fiverr, or Freelancer. ๐๐ž๐ซ๐ฌ๐จ๐ง๐š๐ฅ ๐๐ซ๐จ๐ฃ๐ž๐œ๐ญ๐ฌ: Build your own projects, such as analyzing public datasets (e.g., from Kaggle), and share them on GitHub. ๐Ž๐ง๐ฅ๐ข๐ง๐ž ๐‚๐จ๐ฆ๐ฉ๐ž๐ญ๐ข๐ญ๐ข๐จ๐ง๐ฌ: Participate in data analysis competitions on Kaggle or DrivenData to build your skills and gain recognition. ๐Ž๐ฉ๐ž๐ง-๐’๐จ๐ฎ๐ซ๐œ๐ž: Contribute to open-source data analysis projects on GitHub. ๐Ÿ•. ๐’๐ญ๐š๐ซ๐ญ ๐€๐ฉ๐ฉ๐ฅ๐ฒ๐ข๐ง๐  ๐Ÿ๐จ๐ซ ๐‰๐จ๐›๐ฌ Tailor your resume and portfolio for each role. Highlight projects and key skills. Consider entry-level roles like: Junior Data Analyst, Business Analyst, Reporting Analyst Use platforms like LinkedIn & Naukri to apply for jobs.

๐Ÿฐ ๐— ๐˜‚๐˜€๐˜-๐——๐—ผ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฏ๐˜† ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜!๐Ÿ˜ Want to stand out in Data
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