Analytics and growth mindset ️

I was interviewed by The New York Times!☝️

We talked about business on Telegram, especially about growing Telegram channels and making money on them.

You can read the full article here (access it for free from your phone using Telegram’s in-app browser).

I’ve noticed growing activity and interest in the platform among English-speaking audiences every day.

I receive daily questions from people who want:
- Boost their visibility, positioning themselves as an expert in their niche.
- Get an additional source of income.
- Save months of effort and money.

If you also want to turn your Telegram channel into a profitable business, my services are for you: https://tghero.pro/telegram.

10 Best AI Tools for Excel and Spreadsheets in 2025 (Paid + Free) that I've tried

1. Julius AI — 🔥 *

— A computational AI data analyst that provides professional-grade insights quickly.
— Works with data from various sources, including Excel, spreadsheets, images, PDFs, or text files.
— Offers advanced analysis, sleek visualizations, and smart problem-solving, and more.

Pricing: Free + Paid.

* I use it so far (my recommendation).

2. Simple ML for Sheets

— Designed to make machine learning accessible to everyone.
— Developed by the TensorFlow Decision Forests team.
— Streamlines tasks like predicting missing values, training and evaluating models, and forecasting.
— Helps spot abnormalities and uncover patterns directly within your datasets.

Pricing: Free

3. AI Excel Bot ChatGPT

— Ranked #4 in Research & Analysis on ChatGPT, serves as a powerful data analysis assistant.
— Key Capabilities: Code Interpreter & Data Analysis, DALL·E Image Generation, Web Search Integration.

Pricing: Free + Paid (for GPT Premium)

4. ChatGPT 4.0

— Helps you save time by quickly writing scripts, SQL queries, or creating visualizations.
— Can explain complex data, suggest ways to analyze it, and make your work easier.

Pricing: Free + Paid (for GPT Premium)

5. Coefficient.io

— A powerful tool that integrates with Google Sheets to connect live data from business apps, automate reporting, and provide real-time analytics.
— Simplifies workflows by syncing data directly into spreadsheets, enabling users to create dynamic dashboards and perform advanced analysis without coding.

Pricing: Free + Paid

6. AI for Sheets™ Gemini

— A popular Google Sheets add-on with over 1 million downloads and a high rating of 4.5+.
— Leverages AI to simplify data processing, automate tasks, and enhance productivity directly within Google Sheets, making it a favorite for both casual and professional users.

Pricing: Free + Paid

7. GPT Workspace

— An AI assistant for Google Sheets™, Docs™, and Slides™, Drive™ and Gmail™.
— Built on top OpenAI GPT-4o and Google Gemini™ models
— Can be used for all sorts of tasks on text and data analysis: writing, editing, extracting, cleaning, translating, summarizing, outlining, explaining, etc.

Pricing: Free

8. Ajelix.com

— Includes over 15 productivity tools for your spreadsheets: more than 10 ai excel tools, spreadsheet formula generator, vba & google apps code creator, excel template builder, file translator, excel & google sheets add-on, ai spreadsheet assistant, ai graph generator, sql generator.

Pricing: Free + Paid

9. Microsoft Copilot Pro in Excel

— An AI-powered feature integrated into Microsoft 365 that enhances productivity by using advanced AI models to assist with tasks directly within Excel.
— Key Capabilities: natural language queries, automated data analysis, formula generation, data visualization, scenario analysis and forecasting, data cleaning and transformation, insights summarization, integration with Python, and more.

Pricing: Paid

10. Data Analyst by ChatGPT

— A versatile AI assistant designed for tasks such as data analysis, problem-solving, and providing insights.
— Can analyze datasets, create visualizations, address complex questions, and assist with a variety of tasks, including calculations, content creation, and brainstorming.

Pricing: Free + Paid (for GPT Premium)


What tools do you use? Let me know in the comments!👇🏻

YouTube changed my life, even with small channels (9,500 & 1,269 subs).

Here's what I’ve learned, what works, and my 2025 strategy 👉 https://youtu.be/6Jh4bMWV1cA

🔥18 Company Blogs About Data and Technology You Should Read

Many companies like LinkedIn, Canva, and Uber openly share their experiences in blogs, explaining how they solve complex problems in analytics and machine learning.

For example:

— How Spotify runs experiments
— How Canva collects 25 billion events per day
— What tools Duolingo uses for data analysis

Why is it useful to read these?

— Learning: You can discover best practices that you can adapt to your own work.
— Inspiration: Real-life case studies can give you new ideas and fresh perspectives on your own tasks.
— Trends: Stay updated on the latest technologies and methods shaping the future of the industry.

Top blogs about data and technology:

1. Canva
2. Netflix
3. Uber
4. LinkedIn
5. Airbnb
6. Spotify
7. Duolingo
8. New York Times
9. Dropbox
10. Skyscanner
11. Lyft
12. Disney
13. Pinterest
14. X (Twitter)
15. Notion
16. Swiggy
17. Google
18. Stripe


If you'd like more posts like this, hit 🔥!

How Much YouTube Pays Me as a Small YouTuber (with 9.3K Subscribers)


Hey everyone! Today, I'm sharing the inside details about how much money I actually earn from YouTube, even though my channel isn't very big.

I also share some tips on YouTube monetization.


Watch the video to find out!🟥


I'd really appreciate your like and comment!❤

📱 How did Spotify achieve success in the market, and how does analytics help its growth?


Spotify is the #1 music streaming service in terms of monthly active users (MAU). According to the company, over 515 million people use Spotify each month, and 210 million are premium subscribers.

Users can listen to their favorite music and podcasts with a subscription or for free with ads.


What’s behind this success? 📈

1. Experiments. Spotify constantly runs experiments with the app interface, recommendations, and new features to improve the service.

All articles about experiments here

2. Dashboards. In 2023, Spotify created more than 4,900 dashboards in Tableau and Google’s Looker Studio. To ensure quality, they developed a Dashboard Quality Framework — a checklist covering design, usability, insights, and trust.

Article and checklist for dashboard design

3. Data platform. With growing data complexity, Spotify believes a strong data platform is crucial for gaining valuable insights and driving innovation.

About Spotify's data platform - Part 1
About Spotify's data platform - Part 2

4. Machine learning. Spotify heavily uses machine learning to enhance user experience and create personalized music recommendations.

All Spotify articles on machine learning here


Working at Spotify👨‍💻

Spotify has over 9,000 employees worldwide and promotes equality, freedom from judgment and stigmatization, and contributes to addressing climate change.

— More on Spotify’s diversity, equity, and impact
— Current job openings
— How Spotify hires
— Tour of Spotify's office in Milan, Italy


Other⚡

— Spotify’s datasets
— NerdOut@Spotify - a technical podcast by Spotify
— Spotify blog (often posts fresh articles)
— Spotify’s open source projects, including Spotify PostgreSQL Metrics and Chartify.


If you'd like more posts like this, hit 🔥!

🔴 The best free machine learning courses (I've liked the most)


I've explored🔎 many machine learning courses, and here are several free ones that I liked the most.


Watch video🟥

Hey everyone😻! I know many of you are interested in making money on Telegram.

Telegram can be a great source of additional income, or even a main one. Imagine writing posts about things you enjoy and earning money from it!

I've created a video just for you: "How to Make Money on Telegram: Step-by-Step Guide (MY EXPERIENCE AND EXAMPLES)"

Check it out here 👉 WATCH.

🔥How to Find a Job in the Data Industry (PART 1)


Competition in the data industry is tough, and many people, especially beginners, struggle to find a job.

In this series of posts, I’ll share tips to help you find a job faster.


❗The first tip:

Be proactive. Don’t limit yourself to just one job board. If you're not finding enough relevant opportunities on one platform, explore others to discover more suitable job listings.

1. Explore Platforms Specializing in Tech Jobs
 
These sites connect you with employers looking for tech talent, giving you more chances to find the right jobs.

- dice.com
- arc.dev
- builtin.com
- monster.com
- otta.com

2. Explore Platforms Specialized in Data Jobs

They provide job postings and resources specifically for data professionals.

- aijobs.net
- womenindata.co.uk
- datayoshi.com
- careersinaudit.com

3. Explore Startup Job boards

Startups offer unique chances for growth and innovation and let you work on exciting projects.

- lemon.io
- workatastartup.com
- wellfound.com
- startup.jobs

4. Dive into Company Websites 

Check the websites of companies you admire. You can also search online for lists of companies in any industry and visit their sites. This helps you find potential employers you might not have thought of before.

Many companies post jobs only on their own sites, giving you access to opportunities not found on job boards.

- 53 Data Companies to Know About in 2024
- The complete list of surf brands
- List of eLearning Content Providers

5. Try Growth Job

I built this platform to make your job search easier. We gather the best data jobs from over 100,000 sources and send them straight to your inbox. And here's the cool part – we also catch those hidden vacancies that companies don’t always post on regular job boards.

- growthmindset.dev

6. Explore General Job Boards 

These platforms provide a broad range of job listings across various fields, including data.

- linkedin.com
- indeed.com
- glassdoor.com

7. Discover Job Boards for Remote Work

If you’re interested in remote opportunities, specialized remote job boards are a must.

- Remote.co
- flexjobs.com
- remoteok.com
- weworkremotely.com

P.S. In the video, I explore India🇮🇳.

🔥 7 best ways to find job in data (FROM BEGINNER TO SENIOR LEVEL)

➡️➡️➡️ WATCH THE NEW VIDEO

👋 How Duolingo Succeeded in the Market (And How Analytics Helped)


Duolingo is one of the most popular language learning apps (ranked #1 in app stores). Instead of boring lessons, it feels like a game with progress, levels, rewards, mini-game exercises, and more.

According to the company, around 34 million people use Duolingo every day.


But what’s behind this success?

1. "Test Everything" is a key principle at Duolingo. Constant experiments help the company improve learning and find new ways to grow. At any given moment, Duolingo runs hundreds of A/B tests. They experiment with everything—from small UI changes to major features like leaderboards. They've even built their own A/B testing platform.

➡️Learn about Duolingo’s experiments: article

➡️Example of an A/B test to build a daily learning habit: article

➡️Tools Duolingo uses for data analysis: article

2. Duolingo develops its own metrics to help improve the product. One of the most important metrics is "time spent learning well."

➡️How Duolingo develops its metrics: article

3. In 2018, after several years of consistent year-over-year growth, the DAU metric began to stagnate. To address this issue, the Data Science team developed a "Growth Framework," which helped increase DAU fourfold since 2019.

➡️More on this case: article

4. Motivation to use the app and learn a language may work for speakers of one language but not for speakers of another. Duolingo developed the Expurrimenter, which helps conduct A/B tests on in-app messages to ensure that the messages motivate all learners equally and feel natural to them.

➡️How Duolingo adapts in-app messages: article

5. Turning a Free App into a $7.7 Billion Business: video


Working at Duolingo

Duolingo has 700+ employees from 30 countries, with 45% being engineers (including developers and data scientists). Check out their job openings, including internships: careers. Learn about Duolingo’s interview process: article.


If you found this content helpful, hit 🔥!

⭐ 3 Free SQL Games for Learning and Fun


The games are completely free, and you can write SQL queries directly in your browser—no downloads needed.

1. SQL Murder Mystery

This is a murder mystery created by Knight Lab at Northwestern University. You'll need to use your SQL skills to find the killer hiding in SQL City.

🔗Play SQL Murder Mystery

2. SQL Island

In this adventure game, you're stranded on SQL Island after a plane crash and need to use your SQL skills to find a way to escape.

🔗Play SQL Island

3. Lost at SQL

You’re lost in a fantasy world of SQL, and the only way to get home is by solving SQL challenges.

🔗Play Lost at SQL


🎮 Learning through games is a trend in education in recent years. Games make the learning process more fun, helping to keep attention and motivation high. And here’s also a business idea for you: gamify the learning of SQL, Python, etc., and monetize it.


If you like this post, show it some 🔥!

❤️‍🔥 Thank you all, guys, for your answers!

As a data analyst, I know how difficult it is to find a data job as a beginner (or even if you're experienced but looking to enter a new market). And I understand your concerns:

➡️ The lack of practical experience and confidence that often holds people back.
➡️ The emotional burnout from constant learning and job searching.
➡️ The fear of not standing out in a highly competitive job market.

I know many people worry they won’t find a job and that all their hard work learning data analytics will be wasted.

That's why I’ve prepared something to help you get an internship or entry-level job and finally start building your career in data analytics.

🚀I will launch this in approximately 2 weeks, so stay tuned for updates!

👋 The question from the interview for a Data Analyst position at Duolingo (Difficulty: Medium)⤵️


➖➖➖➖

Stories Difficulty

Duolingo is a language learning platform. When a student is learning a new language, Duolingo wants to recommend increasingly difficult stories to read.

How would you measure the difficulty level of a story based on how users interact with it?

The question and answers from data analysts are here.


➖➖➖➖

If you want to know the questions asked at different companies for a Data Analyst position and prepare for an interview:

- Non-coding questions are here (free).
- Coding questions are here (free).