Data Science
Kanalga Telegram’da o‘tish
Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases
Ko'proq ko'rsatish📈 Telegram kanali Data Science analitikasi
Data Science (@sql_databases) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 70 803 obunachidan iborat bo'lib, Taʼlim toifasida 2 261-o'rinni va Hindiston mintaqasida 4 562-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 70 803 obunachiga ega bo‘ldi.
26 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -310 ga, so‘nggi 24 soatda esa -15 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 11.21% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.74% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 7 934 marta ko‘riladi; birinchi sutkada odatda 1 943 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 0 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent database, learning, linkedin, udemy, 029k| kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn how to analyze data effectively and manage databases with ease.
Buy ads: https://telega.io/c/sql_databases”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 27 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
70 803
Obunachilar
-1524 soatlar
-1277 kunlar
-31030 kunlar
Postlar arxiv
70 803
🔅 Learning Apache Airflow
📝 Get an introduction to Apache Airflow—its uses, structure, how to get it up and running, and how to create and execute workflows.
🌐 Author: Janani Ravi
🔰 Level: Advanced
⏰ Duration: 2h 10m
📋 Topics: Apache Airflow, IT Automation
🔗 Join Data Analysis for more courses
70 803
+3
Here’s a practical, code-first playbook for exploring numerical data 👇
How we approach EDA (with Python code + outputs):
- Basics: shape, dtypes, and missing values.
- Descriptives: mean/median, variance, and percentiles for quick sanity checks.
- Distributions: histograms, boxplots, density to spot skew and spread.
- Relationships: scatter plots and a correlation heatmap to find signals.
- Outliers: z-scores/IQR to flag anomalies worth investigating.
- Scaling: MinMax vs Z-score depending on the model and metric.
- Segments: groupby comparisons to surface patterns you miss in globals.
- Decisions: tie insights back to the question and next steps.
What this really means is: you get a repeatable workflow that turns raw numbers into clear hypotheses fast.
70 803
📁 Master Excel like a pro
Here's your ultimate Excel Cheat Sheet tailored for Data Analysts. Save it, share it, and boost your productivity!
70 803
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🔅 SQL Practice: Intermediate Queries
📝 Practice writing immediate queries in SQL in this hands-on, interactive course with coding challenges in CoderPad.
🌐 Author: Scott Simpson
🔰 Level: Intermediate
⏰ Duration: 11m
📋 Topics: SQL, Database Queries
🔗 Join Data Analysis for more courses
70 803
🔰 PostgreSQL 101: The Everything Database
Built using C language, PostgreSQL is the most popular choice of database from small web apps to enterprise systems. It runs as a multi-process system and follows ACID principles.📋 The key points about PostgreSQL’s Architecture are as follows: 1 - PostgreSQL supports concurrent client connections independently. Each client connection to PostgreSQL creates a dedicated server process. 2 - The Postmaster Process is the main supervisor that manages all other PostgreSQL processes. It controls the entire database instance. 3 - Background workers run parallel processes when needed to handle specialized tasks. 4 - PostgreSQL shared memory is a central memory area containing multiple buffers such as Shared, WAL, Clog, and Temporary buffers. All components communicate through this shared memory. 5 - PostgreSQL also has several auxiliary processes such as: - BG Writer: Manages background writing - WAL Writer: Handles write-ahead logging - Auto Vacuum: Maintains database cleanliness - Checkpointer: Ensures data consistency - Stats Collector: Gathers statistics - System Logger: Manages Logging - Archiver: Handles archiving - Replication launcher: Manages replication 6 - PostgreSQL has different types of physical files for varied needs such as: - Data Files: Stores actual database data - WAL Files: Write-ahead log storage - Archive Files: Backup and recovery data - Log Files: System and error logs
70 803
📂 Full description
Observable is one of the most exciting (and constantly expanding) platforms to use for data analytics, visualization, storytelling, and collaboration. Its blend of easy-to-use click and drag features and customization makes it extremely popular for users across a wide range of skillsets. In this course, data analytics and visualization expert Bill Shander gives you an overview of the Observable platform, introducing the key features and functionalities with practical and tangible examples. Bill shows you how to get data into Observable, manipulate that data, and make visuals and reports with it. He demonstrates how to add interactivity to the reports, and how to make visuals in a variety of ways—some of which are one-click and others that offer more customizability with coding. By the end of the course, you will be able to spin up a new notebook, add data to it, and create a fully interactive data report.
70 803
🔅 Data Analytics with Observable
🌐 Author: Bill Shander
🔰 Level: Intermediate
⏰ Duration: 2h 9m
🌀 Get an overview of the Observable platform and build real skills fast.📗 Topics: Data Visualization, Data Analytics 📤 Join Data Analysis for more courses
70 803
𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗕𝗮𝘀𝗶𝗰 𝗦𝗤𝗟 𝗖𝗼𝗺𝗺𝗮𝗻𝗱𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀! 🧠
Are you looking to build or refine your SQL skills? Whether you're a beginner or want to solidify the fundamentals, mastering these basic SQL commands is a great starting point. Here's a quick rundown of the most commonly used SQL commands
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🔰 2hrs on top & 8hrs in channel!
