О карьерном росте при работе с данными и развитии аналитической культуры в компаниях. РКН: №5218310250
Менторю специалистов и руководителей продуктовых компаний.
Для связи: @pbukhtik
Created
Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Education — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 74% 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 the other topics.
Growth
55 measurements spanning 90 days, net +56. 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 12,711–12,815 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 55
Measured (UTC)
Subscribers
Change
5 Nov 2026, 11:36
12,783
-1
3 Nov 2026, 08:31
12,784
-5
2 Nov 2026, 09:40
12,789
-2
1 Nov 2026, 11:56
12,791
-5
31 Oct 2026, 11:47
12,796
-1
30 Oct 2026, 10:54
12,797
-6
29 Oct 2026, 08:17
12,803
+4
28 Oct 2026, 03:59
12,799
+1
26 Oct 2026, 05:08
12,798
+2
25 Oct 2026, 03:05
12,796
+7
24 Oct 2026, 00:06
12,789
+2
23 Oct 2026, 01:50
12,787
-2
22 Oct 2026, 01:20
12,789
+2
20 Oct 2026, 17:29
12,787
+4
19 Oct 2026, 14:00
12,783
-1
18 Oct 2026, 14:55
12,784
+4
17 Oct 2026, 14:06
12,780
+3
16 Oct 2026, 17:29
12,777
-6
15 Oct 2026, 18:36
12,783
-2
14 Oct 2026, 17:06
12,785
first reading
Engagement
30 posts held, back to 30 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 54 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
27.2%
avg views ÷ 12,783 subscribers
Avg views / post
3,480
6 posts measured
Reaction rate
1.20%
reactions ÷ views · ER floor
Posts in window
6
of 30 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 2 November 2026
Posts held
30 (30 June 2026 – 2 November 2026)
Views total
20,880
Reactions total
250
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 18:49 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
762
Videos
22
Links
275
Lifetime counters from Telegram’s own channel header, read 5 November 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
19s
Average length
19s
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
1,892 reactions across 30 posts, in 27 distinct kinds. The most used accounts for 34.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
656
34.7%
❤
620
32.8%
🎉
280
14.8%
👍
121
6.40%
💯
83
4.39%
🌚
18
0.951%
❤🔥
17
0.899%
🤣
17
0.899%
👏
16
0.846%
🐳
14
0.74%
⚡
10
0.529%
😭
8
0.423%
✍
6
0.317%
😁
4
0.211%
👀
3
0.159%
🕊
2
0.106%
😱
2
0.106%
🤓
2
0.106%
🤔
2
0.106%
🤝
2
0.106%
7 further kinds
9
0.476%
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 30 of the 30 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 1,892 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 30 most recent posts we hold, published 30 June 2026 to 2 November 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
5
of 30 we hold a reading for · 17%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @nodatanogrowth. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 30 most recent posts we hold for this entry, published 30 June 2026 to 2 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 6 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
🇪🇸 Всего месяц учу испанский и уже понимаю живую речь
Больше месяца я каждый день по часу занимаюсь испанским и уже могу смотреть на нем неадаптированные видео без субтитров.
Я не претендую на звание эксперта в изучении языков. Но сегодня хочу поделиться подходами, которые хорошо сработали на мне. Возможно, какие-то из них помогут и вам.
🎧 Comprehensible Input
Это мой главный game changer в изучении языка.
Меня …
🚀 Седьмой поток курса по A/B стартует 2 ноября. Осталось 4 места!
Посчитать A/B-тест сегодня может любая нейросеть. А вот разобраться, можно ли доверять результату и что рекомендовать бизнесу, по-прежнему задача аналитика.
Именно этому я учу на курсе «A/B-тесты и проверка гипотез для продуктовых аналитиков».
За плечами у меня 9 лет работы с A/B (ex-Yandex, FindMyKids, Kupibilet), 100+ лично проведенных эксперимент…
📊 Ценность аналитика в мире AI
Еще пару лет назад умение писать сложные SQL запросы, строить ETL и витрины данных, разрабатывать Python библиотеки для автоматизации A/B было конкурентным преимуществом аналитика.
Сегодня AI заметно снизил порог входа в эти задачи. И дальше техническая реализация будет становиться только доступнее.
Но остается навык, ценность которого на этом фоне только растет. Это умение проверять…
📐 Как связаны продвинутые методы в А/В и линейная регрессия?
Раньше я рассказывал, что A/B тест можно представить как линейную регрессию:
Yᵢ = β₀ + β₁Tᵢ + εᵢ
где β₀ – среднее значение метрики в контроле, β₁ – исследуемая разница между тестом и контролем.
Многие «продвинутые» методы в A/B являются продолжением этой же идеи. На картинке выше я показал, что добавляется в каждом методе и в чем его главная идея.
Ес…
❓ Сколько А/В ты провел?
Или самый бессмысленный вопрос на собеседовании.
Все чаще рекрутеры спрашивают: «Сколько А/В ты провел?» и ждут в ответ большую цифру.
По моим наблюдениям, ответ «до 6 А/В в год» почти гарантированно относит тебя к «недостаточно опытным». «Норм» начинается где-то от 12. И чем больше, тем лучше.
Забавно, что этот вопрос задают даже команды, где А/В нет и не будет. И свой же фильтр они бы н…
🚪 Почему я закрыл свой последний pet project и какие 5 уроков из этого вынес
Год назад я писал про SkillBeast, micro-learning сервис для прокачки хард-скиллов (раз, два, три). Мы сделали несколько версий, исправили баги на закрытой бете и публично запустились. А потом проект довольно быстро перестал существовать как отдельный продукт.
Мне долго не хотелось об этом писать. Про успехи все-таки писать проще и приятнее…
🎱 Разбор задачи с собесов на шары и перегородки
Задачи на чистую комбинаторику на собеседованиях встречаются редко. Обычно комбинаторика это составная часть задачи на теорвер.
Но есть один вид задач, которым любят подловить на собесе. Он выбивается из привычной схемы «сочетания / перестановки / размещения». И если сразу его не узнать, решить такую задачу крайне сложно.
Классическая формулировка звучит так:
Пусть …
🔺 Как связаны бизнесовые, продуктовые и сервисные метрики?
Часто на метрики смотрят как на плоский список. Когда нужно выбрать ключевые, рядом оказываются Revenue, CR, SLA поддержки, среднее время доставки, Retention, NPS и еще десятки метрик.
Но мне кажется полезнее мыслить не списком, а уровнями. Например, можно выделить три крупных уровня:
1️⃣ Бизнесовые метрики
Это взгляд на компанию сверху: что происходит с …
💸 Как мы «потеряли» деньги на опционах Miro
5 лет назад моя жена работала в Miro. Часть ее компенсации была в опционах. После ухода она решила их выкупить и оставить себе, потому что верила в компанию.
Продать такие акции в основном можно в двух случаях: IPO или продажа компании.
В 2022 году Miro привлекла раунд при оценке $17,5 млрд и начала усиливать команду людьми с опытом публичных компаний. Например, наняли H…
📦 Задача с собеседования про новые ПВЗ Ozon
Небольшой продуктовый кейс на сегодня.
«Представьте, что Ozon хочет расширять сеть ПВЗ. Как бы вы определяли гео, в которых компании стоит стимулировать открытие новых точек?»
Мне нравится эта задача тем, что она очень простая по формулировке, но довольно быстро разгоняется.
Какие данные вы запросите? Что и как будете считать? Как сравнивать гео между собой? И как пойме…
👻 Что такое фантомная вакансия?
Иногда бывает так, что вакансия есть, но компания никого нанимать не собирается. При этом отклики могут обрабатываться и даже проводиться собесы. Такие вакансии называют фантомными.
Зачем они тогда вообще нужны? Причин на самом деле довольно много:
🔹 Разведка рынка. Нужно понять, есть ли такие специалисты и сколько денег хотят.
🔹 Поиск единорога. Позиция открыта бессрочно на случай…
🚀 Седьмой поток интенсива по собесам стартует в понедельник
Осталось 2 дня, чтобы присоединиться. Свободно 6 мест на Оптимальном и 1 на Менторстве с сопровождением до оффера.
Это последний поток по собесам, который я веду лично онлайн. Т. е. с теорией в Zoom, практикой и личной обратной связью. Следующий, уже в другом формате, будет не раньше февраля.
Также интенсив стал более интенсивным. Теперь программа занимае…
❤6🔥4👍3😱1
Showing the 12 most recent of 30 posts we hold for @nodatanogrowth. 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
@nodatanogrowth 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
11 August 2026
Most recent edit
11 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 3 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.
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.
Noukash @noukashblog · 21,611 Telegram ranks this channel #1 of 95 here — alongside 94 others — read 23 September 2026
karpov.courses @KarpovCourses · 27,307 Telegram ranks this channel #2 of 96 here — alongside 95 others — read 10 September 2026
LEFT JOIN @leftjoin · 41,531 Telegram ranks this channel #4 of 95 here — alongside 94 others — read 29 August 2026
Инжиниринг Данных @rockyourdata · 23,686 Telegram ranks this channel #5 of 93 here — alongside 92 others — read 17 September 2026
getmatch: канал про карьеру в IT @g_jobchannel · 18,980 Telegram ranks this channel #13 of 95 here — alongside 94 others — read 5 October 2026
Время Валеры @cryptovalerii · 32,016 Telegram ranks this channel #19 of 94 here — alongside 93 others — read 6 September 2026
Job for Analysts & Data Scientists @foranalysts · 37,758 Telegram ranks this channel #25 of 96 here — alongside 95 others — read 1 September 2026
Data Science. SQL hub @sqlhub · 36,052 Telegram ranks this channel #37 of 87 here — alongside 86 others — read 2 September 2026
Data Engineering Zoomcamp @dezoomcamp · 30,181 Telegram ranks this channel #48 of 69 here — alongside 68 others — read 15 September 2026
Reveal the Data @revealthedata · 27,710 Telegram ranks this channel #48 of 96 here — alongside 95 others — read 10 September 2026
Поступашки - ШАД, Стажировки и Магистратура @postypashki_old · 47,060 Telegram ranks this channel #50 of 90 here — alongside 89 others — read 28 August 2026
Анализ данных (Data analysis) @data_analysis_ml · 51,924 Telegram ranks this channel #51 of 93 here — alongside 92 others — read 25 August 2026
настенька и графики @nastengraph · 28,084 Telegram ranks this channel #52 of 94 here — alongside 93 others — read 9 September 2026
Поколение Python 🐍 @pygen_ru · 50,325 Telegram ranks this channel #61 of 93 here — alongside 92 others — read 25 August 2026
Клуб анонимных аналитиков @analyst_club · 33,340 Telegram ranks this channel #68 of 96 here — alongside 95 others — read 4 September 2026
Stepik – онлайн-курсы @stepik_courses · 28,924 Telegram ranks this channel #69 of 93 here — alongside 92 others — read 16 September 2026
Яндекс про аналитику @YAN_analytic · 20,944 Telegram ranks this channel #70 of 98 here — alongside 97 others — read 25 September 2026
GoPractice! @gopractice · 29,374 Telegram ranks this channel #76 of 97 here — alongside 96 others — read 9 September 2026
Connectable Jobs @zarubezhom_jobs · 106,258 Telegram ranks this channel #77 of 94 here — alongside 93 others — read 15 August 2026
Data Science Jobs @datasciencejobs · 22,544 Telegram ranks this channel #83 of 93 here — alongside 92 others — read 21 September 2026
Data Science Jobs @datascienceml_jobs · 21,625 Telegram ranks this channel #85 of 97 here — alongside 96 others — read 24 September 2026
Young & Junior - вакансии IT @young_june · 78,685 Telegram ranks this channel #88 of 99 here — alongside 98 others — read 20 August 2026
Job for Junior @jobforjunior · 85,876 Telegram ranks this channel #92 of 99 here — alongside 98 others — read 18 August 2026
This channel appears in 23 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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“No Data No Growth | Pavel Bukhtik” (@nodatanogrowth), 12,783 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/nodatanogrowth.
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.