Performance = SWITCH( TRUE(), [Profit Margin] >= 0.30, "Excellent", [Profit Margin] >= 0.15, "Good", [Profit Margin] >= 0, "Needs Improvement", "Loss" ) It evaluates conditions and returns the corresponding result. This is useful for: ✔ KPI categories ✔ Business rules ✔ Dynamic labels ✔ Conditional calculations ✔ Performance classification 🔹 10. Building a Dynamic Customer Message You can…

Channel
Data Analytics
@sqlspecialist
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Polls · Citations · Telegram's recommendations · Cite this entry
110,886subscribers
+240 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
Register entry
| Telegram ID | -1001759137927 |
|---|---|
| Type | Channel |
| Username | @sqlspecialist |
| Description | Perfect channel to learn Data Analytics Learn SQL, Python, Alteryx, Tableau, Power BI and many more For Promotions: @coderfun @love_data |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 25 September 2026 |
| Measurements held | 35 |
| Confirmed unchanged | 1 time, most recently 25 September 2026 |
| On Telegram | t.me/sqlspecialist |
Topic
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 9 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 25 Sept 2026, 13:21 | 110,886 | +46 |
| 16 Sept 2026, 15:38 | 110,840 | +4 |
| 14 Sept 2026, 20:41 | 110,836 | -7 |
| 13 Sept 2026, 10:40 | 110,843 | -2 |
| 11 Sept 2026, 16:37 | 110,845 | -27 |
| 9 Sept 2026, 05:57 | 110,872 | +29 |
| 5 Sept 2026, 20:39 | 110,843 | +14 |
| 3 Sept 2026, 15:36 | 110,829 | +58 |
| 2 Sept 2026, 11:13 | 110,771 | +4 |
| 1 Sept 2026, 08:15 | 110,767 | +6 |
| 31 Aug 2026, 07:26 | 110,761 | +27 |
| 30 Aug 2026, 08:17 | 110,734 | +17 |
| 29 Aug 2026, 10:37 | 110,717 | +3 |
| 28 Aug 2026, 08:18 | 110,714 | +7 |
| 27 Aug 2026, 11:45 | 110,707 | +6 |
| 26 Aug 2026, 12:42 | 110,701 | +5 |
| 25 Aug 2026, 11:43 | 110,696 | -36 |
| 24 Aug 2026, 12:12 | 110,732 | -43 |
| 22 Aug 2026, 20:38 | 110,775 | +11 |
| 21 Aug 2026, 10:38 | 110,764 | first reading |
Engagement
171 posts held, back to 25 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 108 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.97%
- avg views ÷ 110,886 subscribers
- Avg views / post
- 2,180
- 91 posts measured
- Reaction rate
- 0.239%
- reactions ÷ views · ER floor
- Posts in window
- 91
- of 171 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 73 of 91 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 September 2026 |
|---|---|
| Posts held | 171 (25 July 2026 – 26 September 2026) |
| Views total | 198,455 |
| Reactions total | 393 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 27 Sept 2026, 00:40 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
- Photos
- 218
- Videos
- 1
- Links
- 944
Lifetime counters from Telegram’s own channel header, read 27 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
- Video runtime
- 30s
- Average length
- 30s
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
1,014 reactions across 145 posts, in 8 distinct kinds. The most used accounts for 90.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 914 | 90.1% | |
| 👍 | 68 | 6.71% | |
| 😁 | 12 | 1.18% | |
| 🔥 | 9 | 0.888% | |
| 👎 | 3 | 0.296% | |
| 👏 | 3 | 0.296% | |
| 🥰 | 3 | 0.296% | |
| 🎉 | 2 | 0.197% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 148 of the 171 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,014 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 171 most recent posts we hold, published 25 July 2026 to 26 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
🚀 Data Analyst Roadmap — Part 29 POWER BI LEVEL 8 — ADVANCED DAX: FILTER(), VALUES(), SELECTEDVALUE() & DYNAMIC CALCULATIONS Now let's move into DAX functions that help you build more dynamic Power BI reports. These functions are especially useful when your calculation needs to react to slicers, selections, or the current report context. 🔹 1. FILTER() You already know that FILTER() can create a filtered table. …
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❤4
Learn SQL from basic to advanced level in 30 days Week 1: SQL Basics Day 1: Introduction to SQL and Relational Databases Overview of SQL Syntax Setting up a Database (MySQL, PostgreSQL, or SQL Server) Day 2: Data Types (Numeric, String, Date, etc.) Writing Basic SQL Queries: SELECT, FROM Day 3: WHERE Clause for Filtering Data Using Logical Operators: AND, OR, NOT Day 4: Sorting Data: ORDER BY Limiting Re…
👍19❤8
Born to vibe. Forced to survive.
😁12
🚀 𝐁𝐞𝐜𝐨𝐦𝐞 𝐚𝐧 𝐀𝐈 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐢𝐧 𝟐𝟎𝟐𝟔 🎯 Choose Your Learning Track: 💻 Java Full Stack + AI Engineering 🌐 MERN Full Stack + AI Engineering Placement Highlights: ₹41 LPA highest package | ₹7.4 LPA average package | 2,000+ students placed | 500+ hiring partners 🔗 𝗕𝗼𝗼𝗸 𝗙𝗥𝗘𝗘 𝗗𝗲𝗺𝗼 𝗖𝗹𝗮𝘀𝘀 :- https://pdlink.in/4fWJVID ⚡ AI is creating new career opportunities—start building the skills companies need in 2026!
❤5
employee = { "name": "Alex", "age": 25, "salary": 50000 } employee["name"] # Output: Alex 9. Tuples Tuples store ordered values that cannot normally be changed. coordinates = (10, 20) 10. Sets Sets store unique values. numbers = {1, 2, 2, 3} # Result: {1, 2, 3} SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v ❤️ Double Tap & React For More!
❤12
🚀 SQL & Python Quick Cheatsheet for Beginners 🗄️ SQL Programming 1. What is SQL? SQL stands for Structured Query Language. It is used to communicate with databases and work with stored data. You can use SQL to: ✅ Retrieve data ✅ Filter data ✅ Analyze data ✅ Insert data ✅ Update data ✅ Delete data 2. SELECT Used to retrieve data from a table. SELECT name, salary FROM employees; SELECT → columns you want …
❤8
🚀 𝗧𝗼𝗽 𝟳 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀! 📊 Want to start a career in Data Analytics? Explore these 7 free Microsoft-backed learning resources covering Power BI, Excel, SQL and data fundamentals 🔗 𝗔𝗰𝗰𝗲𝘀𝘀 𝘁𝗵𝗲 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 👇 https://pdlink.in/3Tm2D3Z 💡 Ideal for students, freshers and professionals who want to build practical data skills.
❤4
What does the "X" in functions such as SUMX() and AVERAGEX() indicate?
- A) The function works only with Excel13%
- B) The function uses row-by-row iteration69%
- C) The function removes filters7%
- D) The function creates a relationship11%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
❤4
Which function would you use to calculate the average of a row-level expression?
- A) AVERAGE21%
- B) AVERAGEX55%
- C) AVGX18%
- D) MEANX7%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
What is the main difference between SUM() and SUMX()?
- A) SUM() works only with text1%
- B) SUMX() works only with dates5%
- C) SUM() aggregates a column, while SUMX() evaluates an expression row by row93%
- D) There is no difference1%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Showing the 12 most recent of 171 posts we hold for @sqlspecialist. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Polls
The 6 most recent of 8 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
What does the "X" in functions such as SUMX() and AVERAGEX() indicate?
- A) The function works only with Excel13%
- B) The function uses row-by-row iteration69%
- C) The function removes filters7%
- D) The function creates a relationship11%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Which function would you use to calculate the average of a row-level expression?
- A) AVERAGE21%
- B) AVERAGEX55%
- C) AVGX18%
- D) MEANX7%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
What is the main difference between SUM() and SUMX()?
- A) SUM() works only with text1%
- B) SUMX() works only with dates5%
- C) SUM() aggregates a column, while SUMX() evaluates an expression row by row93%
- D) There is no difference1%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Which DAX function evaluates an expression row by row and then adds the results?
- A) SUM14%
- B) SUMX62%
- C) COUNT12%
- D) CALCULATE12%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
You need to find the top 3 employees in each department. Which approach is most appropriate?
- A) GROUP BY Department only14%
- B) ORDER BY Salary DESC only10%
- C) RANK() OVER (PARTITION BY Department ORDER BY Salary DESC) followed by filtering73%
- D) AVG(Salary) OVER () only4%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Which function is most appropriate for comparing a row's value with the previous row?
- A) LEAD()19%
- B) LAG()38%
- C) RANK()37%
- D) NTILE()7%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 171 most recent posts we hold, published 25 July 2026 to 26 September 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Mentions
Named by 21 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
@udacityfreecourse · 46,70430 postsFree Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert
@free4unow_backup · 74,60012 postsData Analytics & AI | SQL Interviews | Power BI Resources
@Data_Visual · 27,54610 postsCoding & AI Resources
@leadcoding · 35,44410 postsCoding & Data Science Resources
@codingfreebooks · 32,5559 postsData Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
@learndataanalysis · 53,2628 postsPrograming Resources: Python - Java - R - SQL - Javascript - C++
@the_programming_girls · 30,4915 postsBest AI Tools | ChatGPT | Perplexity | Deepseek | Artificial Intelligence
@AI_Best_Tools · 58,4704 postsFreelancing Tips: Earn Money Online
@freelancing_upwork · 22,3664 postsData Science Jobs
@datasciencej · 8,3163 postsPower BI & Tableau Resources
@PowerBI_analyst · 55,8423 postsPython for Data Analysts
@pythonanalyst · 51,8573 postsSQL Programming Resources
@sqlanalyst · 76,6753 postsArtificial Intelligence & ChatGPT Prompts
@Curiousprogrammer · 42,2382 postsData Analyst Interview Resources
@dataanalystinterview · 52,6092 postsDevelopers India 🇮🇳
@developersindiamain · 2,5512 postsProgramming Resources | Python | Javascript | Artificial Intelligence Updates | Computer Science Courses | AI Books
@programming_guide · 56,0382 postsThe World Of Programming
@w_of_programming · 13,5902 postsCoding Interview Resources
@crackingthecodinginterview · 52,2321 postትኩስ የስራ ማስታወቂያ
@mrtmrt_ch · 2071 postThe Sarcastic Bot
@Sarcasticbott · 2581 post
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
@sqlanalyst · 76,675#1
@jobs_SQL · 91,421#2
@excel_analyst · 72,836#3
@PowerBI_analyst · 55,842#4
@datasciencefun · 77,580#5
@datasciencefree · 68,434#6
@pythonspecialist · 56,321#7
@learndataanalysis · 53,262#8
@dataanalystinterview · 52,609#9
@dsabooks · 59,137#10
@pythonanalyst · 51,857#11
@machinelearning_deeplearning · 55,794#12
@pythondevelopersindia · 63,430#13
@sql_engineer · 11,126#14
@Programming_experts · 67,682#15
@sqlproject · 39,680#16
@DataPortfolio · 38,028#17
@crackingthecodinginterview · 52,232#18
@programming_guide · 56,038#19
@LearnPython3 · 125,222#20
@Python53 · 50,715#21
@MachineLearning9 · 41,424#22
@learngpt · 38,216#23
@DataScienceInterviews · 27,673#24
@CodeProgrammer · 68,301#25
@PaperNexus · 33,858#26
@pythonRe · 40,364#27
@Jobs204 · 22,576#28
@PythonInterviews · 28,969#29
@sql_databases · 70,599#30
@codingfreebooks · 32,555#31
@datasciencej · 8,316#32
@Learn_Startup · 32,970#33
@datascience_bds · 13,926#34
@DataAnalyticsX · 30,208#35
@pythonfreebootcamp · 40,776#36
@InterviewBooks · 40,516#37
@data_visualization_bds · 6,314#38
@ml_ds_ai_jobs · 25,932#39
@DataAnalyticsJob · 13,015#40
@webdevelopmentbook · 32,466#41
@bdscience · 3,563#42
@Data_Visual · 27,546#43
@aijobss · 13,777#44
@powerbi_sql_analyst · 6,794#45
@thinkbroadly · 6,763#46
@AWS_GCP_Azure · 5,465#47
@ApacheSparkDevelopers · 7,803#48
@datamindscape · 5,184#49
@Learn_Business_101 · 52,476#50
@jobinterviewsprep · 27,626#51
@datascience69 · 20,492#52
@getjobss · 113,437#53
@AI_Best_Tools · 58,470#54
@udemy_free_courses_with_certi · 70,681#55
@webdevcoursefree · 79,578#56
@javascript_courses · 55,698#57
@linkedin_learning · 217,924#58
@aiindi · 58,966#59
@stockmarketinginsights · 25,970#60
@generativeai_gpt · 30,777#61
@Curiousprogrammer · 42,238#62
@aineeringdotcom · 16,029#63
@trueminds · 27,344#64
@englishlearnerspro · 41,600#65
@Finance_Stock_Trading · 23,207#66
@machine_learning_courses · 95,724#67
@webdev_trainings · 133,855#68
@Bitcoin_Crypto_Web · 23,194#69
@Java_Programming_Notes · 33,275#70
@BestFinanceBooks · 25,148#71
@OpenAI_Mastery · 50,064#72
@JavaScript_Trainings · 96,712#73
@Machine_learn · 24,295#74
@internshiptojobs · 48,447#75
@remote_python_jobs · 4,955#76
@the_programming_girls · 30,491#77
@deeplearning005 · 11,155#78
@AlwaysFreeUdemyCourses · 18,460#79
@FAANGJob · 26,890#80
@remote_ai_jobs · 8,179#81
@HealthFitnessGymTips · 19,780#82
@aipost · 700,241#83
Read from Telegram’s recommendation API, most recently 14 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
@PythonInterviews · 28,969
Telegram ranks this channel #1 of 86 here — alongside 85 others — read 9 September 2026
@PowerBI_analyst · 55,842
Telegram ranks this channel #1 of 84 here — alongside 83 others — read 23 August 2026
@sqlanalyst · 76,675
Telegram ranks this channel #1 of 85 here — alongside 84 others — read 19 August 2026
@jobs_SQL · 91,421
Telegram ranks this channel #1 of 86 here — alongside 85 others — read 17 August 2026
@dataanalyticsbuddy · 27,254
Telegram ranks this channel #2 of 88 here — alongside 87 others — read 11 September 2026
@pythonanalyst · 51,857
Telegram ranks this channel #2 of 82 here — alongside 81 others — read 24 August 2026
@learndataanalysis · 53,262
Telegram ranks this channel #2 of 83 here — alongside 82 others — read 24 August 2026
@excel_analyst · 72,836
Telegram ranks this channel #2 of 84 here — alongside 83 others — read 20 August 2026
@jobinterviewsprep · 27,626
Telegram ranks this channel #3 of 72 here — alongside 71 others — read 10 September 2026
@cloudymlofficial · 47,680
Telegram ranks this channel #3 of 88 here — alongside 87 others — read 26 August 2026
@dataanalystinterview · 52,609
Telegram ranks this channel #3 of 85 here — alongside 84 others — read 24 August 2026
@pythonspecialist · 56,321
Telegram ranks this channel #3 of 89 here — alongside 88 others — read 23 August 2026
@pythondevelopersindia · 63,430
Telegram ranks this channel #3 of 86 here — alongside 85 others — read 21 August 2026
@DataScienceInterviews · 27,673
Telegram ranks this channel #4 of 86 here — alongside 85 others — read 10 September 2026
@sqlproject · 39,680
Telegram ranks this channel #4 of 84 here — alongside 83 others — read 30 August 2026
@thedataschoool · 42,192
Telegram ranks this channel #4 of 85 here — alongside 84 others — read 29 August 2026
@dsabooks · 59,137
Telegram ranks this channel #4 of 89 here — alongside 88 others — read 22 August 2026
@datasciencefree · 68,434
Telegram ranks this channel #4 of 88 here — alongside 87 others — read 20 August 2026
@datasciencefun · 77,580
Telegram ranks this channel #4 of 85 here — alongside 84 others — read 19 August 2026
@DataPortfolio · 38,028
Telegram ranks this channel #5 of 83 here — alongside 82 others — read 31 August 2026
@sql_databases · 70,599
Telegram ranks this channel #5 of 73 here — alongside 72 others — read 20 August 2026
@datalemur · 20,794
Telegram ranks this channel #6 of 72 here — alongside 71 others — read 26 September 2026
@Data_Visual · 27,546
Telegram ranks this channel #6 of 83 here — alongside 82 others — read 10 September 2026
@machinelearning_deeplearning · 55,794
Telegram ranks this channel #6 of 86 here — alongside 85 others — read 23 August 2026
This channel appears in 131 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 25 September 2026 — this entry's latest reading, not the date you are reading this.
“Data Analytics” (@sqlspecialist), 110,886 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/sqlspecialist.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.