Канал Ромы Бунина про визуализацию данных, дашборды и развитие BI-систем.
Подробнее про канал, рубрики, правила и контакты — https://t.me/revealthedata/386
Сайт и блог — https://revealthedata.com/
Created
26 February 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 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
31 measurements spanning 42 days, net -117. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 27,809–27,975 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 31
Measured (UTC)
Subscribers
Change
17 Sept 2026, 01:22
27,839
+11
15 Sept 2026, 05:58
27,828
-13
13 Sept 2026, 13:57
27,841
-2
11 Sept 2026, 16:41
27,843
-13
9 Sept 2026, 05:17
27,856
+28
5 Sept 2026, 20:22
27,828
-19
3 Sept 2026, 15:38
27,847
-4
2 Sept 2026, 11:44
27,851
+1
1 Sept 2026, 14:37
27,850
-3
31 Aug 2026, 14:28
27,853
-9
29 Aug 2026, 12:04
27,862
+4
28 Aug 2026, 15:16
27,858
+6
27 Aug 2026, 12:55
27,852
-7
26 Aug 2026, 14:52
27,859
-2
25 Aug 2026, 15:13
27,861
-16
24 Aug 2026, 13:58
27,877
-27
22 Aug 2026, 21:15
27,904
-4
21 Aug 2026, 08:57
27,908
-4
20 Aug 2026, 08:48
27,912
+1
19 Aug 2026, 10:03
27,911
first reading
Engagement
21 posts held, back to 23 June 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 63 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
18.5%
avg views ÷ 27,839 subscribers
Avg views / post
5,140
7 posts measured
Reaction rate
0.712%
reactions ÷ views · ER floor
Posts in window
7
of 21 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 14 September 2026
Posts held
21 (23 June 2026 – 14 September 2026)
Views total
35,980
Reactions total
256
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
23 Sept 2026, 15:20 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
≈1,080
Videos
≈41
Links
≈754
Lifetime counters from Telegram’s own channel header, read 23 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
1m 10s
Average length
1m 10s
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
949 reactions across 21 posts, in 7 distinct kinds. The most used accounts for 51.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
486
51.2%
🔥
196
20.7%
👍
194
20.4%
😁
66
6.95%
😈
5
0.527%
🕊
1
0.105%
😢
1
0.105%
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 21 of the 21 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 949 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 23 June 2026 to 14 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.
🛠 Инструменты
Продолжим разбирать архитектуру агентов. Какая бы умная и крутая модель ни была, хоть AGI, без рук она ничего не сделает. Почта, Jira и база данных сами к ней не подключатся.
Встроенные и свои тулы
В AI-продуктах есть поиск, браузер, работа с файлами, калькулятор, запуск Python-кода и т. п. Всё это устроено как перечень функций с описаниями: модель может выбрать нужную функцию при ответе на запрос.
Ес…
⚡️ Конференция про AI-кейсы в бизнесе
Соберёмся онлайн с классными ребятами, чтобы обменяться практическим опытом. Будет много живых кейсов и честных разборов того, что действительно работает.
Я расскажу, как мы подходим к внедрению AI в большой компании: какие важные части этого процесса выделяем, что работает и как можно повышать вовлечённость сотрудников. Расскажу, что сработало, а что нет, и где я вижу самые бол…
📄 Harness и скиллы
В прошлом посте был мозг агента, теперь переходим ко всему, что находится вокруг него: инструкции, инструменты, память и контекст. Всё вместе это сейчас называют модным словом harness. Это вся обвязка, которая помогает агенту работать так, как нужно именно вам.
Начну с инструкций — промптов и скиллов. Ещё год назад было много хайпа вокруг prompt engineering. Сейчас же уже не нужно разбираться в ма…
🧠 Модели
Следующий блок агента — это мозг. Забавно как из очень важной и революционной части модели быстро стали почти что комоддити. Каждые несколько месяцев выходит что-то новое, а опенсорс догоняет лабы всё быстрее. Ещё месяц назад все говорили о революции от Fable, но вот модель тут и ничего каординально не изменилось.
В это смысле надо помнить, что модели обучены на огромном количестве данных и по-сути всегда о…
🕹 Как управлять агентом
Начну с первого блока. Управлять агентами сейчас можно пятью способами (в будущем можно будет еще и мыслью 🙃):
— Веб-чат: самый привычный способ, здесь рассказать чего-то интересного нечего.
— Десктоп: агент работает с вашими папками и приложениями: может читать файлы, запускать команды, использовать другие программы и инструменты. Если до сих пор работаете только через веб-версию, попробуйт…
🤖 Из чего состоит AI-агент
Сейчас пишу следующую главу книги — она будет про AI в BI и аналитике. Материалов накопилось много, и часть из них в книгу не войдёт. Поэтому решил опубликовать в канале небольшую затравку.
Хочу разобрать несколько вроде бы всем понятных, но важных частей о том, как устроены агенты. По разговорам вижу, что люди часто понимают их по-разному и не до конца представляют, как всё это работает.
…
🤖 Вайб-салон
Вчера сходил на вайб-салон — это такой формат, где люди собираются в одном месте, несколько часов вайбкодят, а потом показывают и обсуждают, что у кого получилось.
Если честно, я шёл туда с небольшим скепсисом. Вайб-салоны сейчас стали очень модной темой, но со стороны всё это звучало для меня как-то скорее как дань моде. Но оказалось, что это очень прикольный формат.
По ощущениям я как будто сходил на…
📘 От дашборда к системе
Вышла следующая глава книги — про стратегию развития BI в компании.
В этот раз разбираемся, что происходит с BI-системой по мере роста компании. В какой-то момент просто делать хорошие дашборды уже недостаточно и появляются куча всего: процессы поддержки и обучения, стайлгайды и сертификация, управление контентом и доступами, мониторинг, отдельные роли и центр компетенций. И только чтобы прос…
Ахахах, я чёт не думал, что найду себя в воскресенье в окружении трех ноутбуков с агентами, которые гоняют таски 🙈 Агенты реально как какая-то зависимость блин.
И моя эго-часть явно хочет с вами поделиться и похвастаться, смотрите блин какой же я крутой. А нормальная моя часть рекомендует — если вы нашли себя в такой же ситуации, то пойдите отдохните пожалуйста 🫂 Я пошёл!
Showing the 12 most recent of 21 posts we hold for @revealthedata. 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.
Posts edited after publishing
@revealthedata edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
30 August 2026
Most recent edit
30 August 2026
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 14 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.
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.
Read from Telegram’s recommendation API, most recently 10 September 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.
настенька и графики @nastengraph · 28,213 Telegram ranks this channel #1 of 94 here — alongside 93 others — read 9 September 2026
Клуб анонимных аналитиков @analyst_club · 33,554 Telegram ranks this channel #1 of 96 here — alongside 95 others — read 4 September 2026
LEFT JOIN @leftjoin · 42,064 Telegram ranks this channel #1 of 95 here — alongside 94 others — read 29 August 2026
Инжиниринг Данных @rockyourdata · 23,767 Telegram ranks this channel #3 of 93 here — alongside 92 others — read 17 September 2026
karpov.courses @KarpovCourses · 27,430 Telegram ranks this channel #5 of 96 here — alongside 95 others — read 10 September 2026
Google Таблицы @google_sheets · 60,505 Telegram ranks this channel #15 of 98 here — alongside 97 others — read 22 August 2026
Data Science. SQL hub @sqlhub · 35,969 Telegram ranks this channel #23 of 87 here — alongside 86 others — read 2 September 2026
Магия Excel @lemur_excel · 49,863 Telegram ranks this channel #28 of 95 here — alongside 94 others — read 25 August 2026
Job for Analysts & Data Scientists @foranalysts · 36,643 Telegram ranks this channel #30 of 96 here — alongside 95 others — read 1 September 2026
Excel Everyday @excel_everyday · 52,365 Telegram ranks this channel #31 of 97 here — alongside 96 others — read 24 August 2026
Время Валеры @cryptovalerii · 30,829 Telegram ranks this channel #43 of 94 here — alongside 93 others — read 6 September 2026
Рациональные числа @rationalnumbers · 25,686 Telegram ranks this channel #46 of 93 here — alongside 92 others — read 13 September 2026
Секреты аналитики | Data Science, BI, Tableau @analytics_secrets · 47,005 Telegram ranks this channel #52 of 85 here — alongside 84 others — read 27 August 2026
Анализ данных (Data analysis) @data_analysis_ml · 50,631 Telegram ranks this channel #57 of 93 here — alongside 92 others — read 25 August 2026
Базы данных | Access, SQL, Big Data @databases_secrets · 30,034 Telegram ranks this channel #60 of 82 here — alongside 81 others — read 7 September 2026
Noukash @noukashblog · 21,622 Telegram ranks this channel #66 of 95 here — alongside 94 others — read 23 September 2026
ProductDo: практика продакта @productdo · 24,067 Telegram ranks this channel #73 of 97 here — alongside 96 others — read 17 September 2026
GoPractice! @gopractice · 29,053 Telegram ranks this channel #78 of 97 here — alongside 96 others — read 9 September 2026
Нормально делай, нормально будет / Саша Клименко @normalno_delaj · 21,737 Telegram ranks this channel #82 of 96 here — alongside 95 others — read 22 September 2026
Поколение Python 🐍 @pygen_ru · 50,072 Telegram ranks this channel #87 of 93 here — alongside 92 others — read 25 August 2026
Продукторий Владимира Меркушева @vladimir_merkushev · 22,031 Telegram ranks this channel #89 of 96 here — alongside 95 others — read 21 September 2026
No Flame No Game @proproduct · 38,826 Telegram ranks this channel #92 of 96 here — alongside 95 others — read 31 August 2026
This channel appears in 22 seed channels' Telegram-generated recommendation lists in total. 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“Reveal the Data” (@revealthedata), 27,839 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/revealthedata.
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.