Data Science
前往频道在 Telegram
Learn how to analyze data effectively and manage databases with ease. Buy ads: https://telega.io/c/sql_databases
显示更多📈 Telegram 频道 Data Science 的分析概览
频道 Data Science (@sql_databases) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 71 041 名订阅者,在 教育 类别中位列第 2 273,并在 印度 地区排名第 4 764 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 71 041 名订阅者。
根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 -54,过去 24 小时变化为 6,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 12.21%。内容发布后 24 小时内通常能获得 2.97% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 8 672 次浏览,首日通常累积 2 110 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 0。
- 主题关注点: 内容集中在 database, learning, linkedin, udemy, 029k| 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Learn how to analyze data effectively and manage databases with ease.
Buy ads: https://telega.io/c/sql_databases”
凭借高频更新(最新数据采集于 06 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 教育 类别中的关键影响点。
71 041
订阅者
+624 小时
+237 天
-5430 天
帖子存档
71 041
🔅 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
71 041
🔰 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
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📂 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.
71 041
🔅 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
71 041
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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📂 Full description
Data analysis isnt just for specialists who need to make sense of massive datasets. Decision-makers in every industry can benefit from a basic understanding of the goals and concepts of applied data analysis. In this course, Barton Poulson focuses on the fundamentals of data fluency, or the ability to work with data to extract insights and determine your next steps. Barton shows how exploring data with graphs and describing data with statistics can help you reach your goals and make better decisions. Instead of focusing on particular tools, he concentrates on general procedures that can help you solve specific problems. Barton covers how to prepare and adapt data, explore it visually, and use statistical methods to describe it. He goes in depth on probability and interference and also touches on data ethics and explainable AI.
71 041
🔅 Data Literacy: Exploring and Describing Data
🌐 Author: Barton Poulson
🔰 Level: Beginner
⏰ Duration: 5h 14m
🌀 Learn the fundamentals of data fluency and how data can help you make better decisions.📗 Topics: Data Science 📤 Join Data Analysis for more courses
71 041
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🔰 Web Development
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220k| 🔰 Linkedin Learning
138k| 🔰 Udemy Premium
133k| 🔰 Web Development
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116k| 🔰 Python 3
099k| 🔰 JavaScript Training
088k| 🔰 Machine Learning
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067k| 🔰 Artificial Intelligence
067k| 🔰 Data Analysis and Databases
064k| 🔰 React and NextJs
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060k| 🔰 Linux and DevOps
048k| 🔰 100 Days of Python
047k| 🔰 OpenAI Mastery
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046k| 🔰 Business and Finance
044k| 🔰 Best Telegram Channels
040k| 🔰 Zero to Mastery
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040k| 🔰 Mobile Apps
040k| 🔰 Udemy Learning
035k| 🔰 Linkedin Learning Courses
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035k| 🔰 Codedamn Courses
033k| 🔰 React 101
031k| 🔰 Crypto Tutorials
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030k| 🔰 Coding Interview
025k| 🔰 Telegram's Shorts
022k| 🔰 Linux Training
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021k| 🔰 The Coding Space
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🔰 2hrs on top & 8hrs in channel!
71 041
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