Data Science
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Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases
Mostrar más📈 Análisis del canal de Telegram Data Science
El canal Data Science (@sql_databases) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 70 803 suscriptores, ocupando la posición 2 261 en la categoría Educación y el puesto 4 562 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 70 803 suscriptores.
Según los últimos datos del 26 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -310, y en las últimas 24 horas de -15, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 11.21%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.74% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 7 934 visualizaciones. En el primer día suele acumular 1 943 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
- Intereses temáticos: El contenido se centra en temas clave como database, learning, linkedin, udemy, 029k|.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn how to analyze data effectively and manage databases with ease.
Buy ads: https://telega.io/c/sql_databases”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 27 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
70 803
Suscriptores
-1524 horas
-1277 días
-31030 días
Archivo de publicaciones
70 803
🔅 Python in Excel: Getting Started with Data Analysis
📝 Explore the core concepts and fundamental skills of working with data using Python in Microsoft Excel.
🌐 Author: Joe Marini
🔰 Level: Intermediate
⏰ Duration: 1h 40m
📋 Topics: Data Analysis, Microsoft Excel, Python
🔗 Join Data Analysis for more courses
70 803
📊 Your Data Analyst journey doesn’t start with tools — it starts with a roadmap.
From mastering Excel & SQL ➝ understanding statistics ➝ working with Python & visualization tools ➝ building real-world projects — a clear Data Analyst roadmap can save you months of confusion and wrong learning choices.
If you’re serious about breaking into analytics in 2026, you don’t need random tutorials. You need structured learning, hands-on practice, and industry-relevant skills.
70 803
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+1
80% of data problems can be solved with just 16 SQL functions.
I’ve been working with data for years and this truth keeps proving itself:
You don’t need fancy tools.
You need to master the fundamentals.
For data analysts, data scientists, and data engineers:
SQL isn’t optional.
Because data lives in databases.
And databases speak SQL-ish.
Most problems fall into 2 categories:
Aggregate functions (summarise data):
SUM() - Total revenue
COUNT() - Total orders
AVG() - Average purchase value
MIN() - Smallest sale
MAX() - Biggest transaction
STRING_AGG() - Combine text values
Window functions (compare rows):
ROW_NUMBER() - Pagination
RANK() - Leaderboards with ties
DENSE_RANK() - Performance tiers
NTILE() - Split into quartiles
LEAD() - Compare current vs next
LAG() - Compare current vs previous
FIRST_VALUE() - Highest value per group
LAST_VALUE() - Lowest value per group
SUM() OVER() - Running totals
AVG() OVER() - Moving averages
Aggregates collapse rows → one summary result
Window functions keep all rows → add calculations across them
70 803
🔅 MySQL Installation and Configuration
📝 Learn how to install and configure MySQL on various platforms, including Mac and Windows.
🌐 Author: Bill Weinman
🔰 Level: Intermediate
⏰ Duration: 1h 20m
📋 Topics: MySQL, Database Administration
🔗 Join Data Analysis for more courses
70 803
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If you’re thinking of starting a career in data science but not sure where to begin, 🤔 don’t worry—I’ve got you covered! 🙌
Here’s a list of platforms that can help you learn 📚, practice 💻, and ace your interviews.
Whether you’re diving into online courses 🧑🏫, looking for datasets 📊 to build your projects, or sharpening your coding skills 💡 for interviews, these resources are perfect for you.
70 803
🔅 Hands-On Advanced Python: Data Engineering Basics
📝 Practice applying advanced concepts and coding moves in Python in this hands-on, interactive course with coding challenges in CoderPad.
🌐 Author: Joe Marini
🔰 Level: Advanced
⏰ Duration: 1h 56m
📋 Topics: Python
🔗 Join Data Analysis for more courses
