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 why it has no browse page of its own yet.
Growth
31 measurements spanning 41 days, net +46. 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 12,714–12,791 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, 14:37
12,773
+11
15 Sept 2026, 11:40
12,762
+3
13 Sept 2026, 19:59
12,759
+2
12 Sept 2026, 05:36
12,757
-10
10 Sept 2026, 00:58
12,767
-12
6 Sept 2026, 17:59
12,779
-3
4 Sept 2026, 05:18
12,782
+11
2 Sept 2026, 18:27
12,771
+3
1 Sept 2026, 19:53
12,768
-2
31 Aug 2026, 19:58
12,770
-1
30 Aug 2026, 17:58
12,771
-1
29 Aug 2026, 19:28
12,772
+5
28 Aug 2026, 18:14
12,767
-13
27 Aug 2026, 19:28
12,780
+7
26 Aug 2026, 21:45
12,773
+5
25 Aug 2026, 18:44
12,768
+1
24 Aug 2026, 17:43
12,767
+13
23 Aug 2026, 03:23
12,754
+5
21 Aug 2026, 16:37
12,749
+2
20 Aug 2026, 18:06
12,747
first reading
Engagement
15 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 48 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
23.0%
avg views ÷ 12,773 subscribers
Avg views / post
2,940
4 posts measured
Reaction rate
4.49%
reactions ÷ views · ER floor
Posts in window
4
of 15 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 September 2026
Posts held
15 (30 June 2026 – 2 September 2026)
Views total
11,740
Reactions total
527
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
2 Sept 2026, 21:13 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
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
1,248 reactions across 15 posts, in 19 distinct kinds. The most used accounts for 36.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
453
36.3%
❤
341
27.3%
🎉
280
22.4%
👍
55
4.41%
💯
39
3.13%
🤣
13
1.04%
👏
12
0.962%
⚡
10
0.801%
❤🔥
10
0.801%
🐳
9
0.721%
😭
8
0.641%
✍
6
0.481%
👀
3
0.24%
😁
3
0.24%
🤓
2
0.16%
😨
1
0.08%
🙈
1
0.08%
🤔
1
0.08%
🤩
1
0.08%
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 15 of the 15 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 1,248 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 30 June 2026 to 2 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
5
of 15 we hold a reading for · 33%
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 15 most recent posts we hold for this entry, published 30 June 2026 to 2 September 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.
🔥 Полный гайд по собеседованиям на продуктового аналитика
Быть сильным аналитиком и уметь показать свой уровень на интервью – это два разных навыка. Первый развивается за счет рабочих задач. Второй почти никто специально не тренирует.
Поэтому даже опытный аналитик, который на работе тащит сложные проекты, приходит на собес и выглядит слабее, чем он есть на самом деле. А в фидбеке ему просто скажут «мы решили продол…
💍 Я женился! 🥳
Как продуктовый аналитик, я, конечно, не мог спокойно жениться.
Сначала мне казалось, что свадьба устроена просто. Нужно выбрать красивую площадку, еду, декор, ведущего и не забыть прийти. Самая сложная часть, выбрать человека, с которым хочешь прожить жизнь, была уже позади.
Потом я понял, что свадьба очень похожа на запуск полноценного продукта без багов с первого раза. Тут есть привлечение, онбор…
🎲 Разбор задачи про три броска кубика
Напомню формулировку: кубик бросают три раза, какова вероятность, что дважды выпадет одно и то же число.
Правильный ответ – 5/12. Или 4/9? Может, 11/36? Или вообще 5/18?
На самом деле ни один из них. Правильный ответ – сначала уточнить условие, и только потом считать. Вероятность зависит от того, что именно имелось в виду.
Всего возможных исходов: 6³ = 216.
1) Ровно два один…
🎲 Популярная задача с собеса: кубик бросают три раза
Меня не было на канале почти две недели. За это время в моей жизни произошло одно важное событие. Расскажу о нем через пару дней, когда будут фотографии,)
А пока возвращаемся к подготовке к осеннему сезону найма. Держите задачку, которую довольно часто дают на собеседованиях:
Кубик бросают три раза. Какова вероятность, что дважды выпадет одно и то же число?
Все…
🐢 Эта фраза на финале может стоить вам оффера
Когда я ушел из найма, то все равно продолжал ходить по собесам. Посматривал рынок и был открыт к действительно интересным предложениям.
Однажды я дошел до финала в международном стартапе, который мне понравился. В конце меня спросили:
– Ты же не торопишься?
– Не тороплюсь, – на свою голову ответил я.
– Просто позиция новая, хотим посмотреть еще кандидатов...
Вернулис…
❄️ Разбор задачи с собеса про заморозку подписки
Формулировку задачи оставил постом выше, поэтому сразу к разбору.
Главная ошибка – услышать «проверить гипотезу» и сразу побежать в A/B.
Эксперимент здесь может оказаться дорогим решением в лоб. Чтобы увидеть не только краткосрочный эффект на выручку, но и последствия для удержания и LTV, его придется вести достаточно долго. При этом ошибка с решением убрать замороз…
❄️ Популярная задача с собесов на заморозку подписки
Есть задачи, которые кочуют из компании в компанию. Эта одна из них. И несмотря на кажущуюся простоту, на ней регулярно сыпятся кандидаты:
Вы продуктовый аналитик в подписочном сервисе с ежемесячной оплатой.
В управлении подпиской есть функция «заморозки». Вместо отмены пользователь может поставить подписку на паузу на срок до трех месяцев. Списаний в это время …
🔄 Как изменились собесы для аналитиков в 2026 году
За последний год они стали не столько сложнее, сколько требовательнее к качеству мышления. Дать правильный ответ уже недостаточно. Нужно решать быстро и точно, показывая ход рассуждений.
Сразу оговорюсь: ниже не исследование рынка, а мои наблюдения из общения с сотнями кандидатов и нанимающими руководителями. Процессы везде разные, но эти шесть изменений я вижу все…
⏸️ Досрочно останавливаем A/B: подглядывание или нет?
Классика жанра. Тест идет третий день, денежная метрика упала на 8%, p-value уже 0,03. Менеджер давит: «Надо останавливать, мы теряем деньги!» Аналитик отвечает: «Нельзя подглядывать, нужно дождаться выборки!»
Но подглядывание ли это?
Есть разница между подглядыванием как нарушением методологии проведения A/B-теста и мониторингом как проверкой здоровья эксперим…
🤔 Раньше я думал, что понимаю бизнеc
Многие идут в продуктовую аналитику, чтобы быть ближе к бизнесу. Растить продукт, драйвить метрики и выручку, влиять на решения. Девять лет назад я выбрал это направление ровно по такой причине.
Но что значит «приносить пользу бизнесу», я понял не тогда, когда набрался опыта в найме и стал хедом. По-настоящему это пришло только со своими продуктами. В частности, онлайн-школой. И…
📹 «Ты не против, если мы запишем собес?»
Работодатель хочет записать собес – норм или стрем?
На самом деле, может быть и так, и так.
Я сам был по обе стороны. Когда нанимал, просил записать интервью, чтобы показать команде и обсудить кандидата вместе. А когда не мог прийти на собес, но участвовал в решении – запись показывали мне.
📝 Причины для записи обычно скучные и рабочие:
-> Интервьюеру хочется слушать тебя…
🎯 В чём идея Uplift-моделирования?
Привычные ML-модели отвечают на вопрос: «Кто с большой вероятностью купит?» или «Кто может уйти?»
Но бизнесу часто нужен ответ на другой: «На кого подействует наше воздействие?»
И это разные задачи.
Например, мы хотим удержать пользователя и отправляем ему скидку на следующий заказ. Возможны четыре сценария:
🔸 Он остался бы и без скидки (Sure Things) – мы потеряли часть маржи, …
🔥35❤12
Showing the 12 most recent of 15 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
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.
karpov.courses @KarpovCourses · 27,430 Telegram ranks this channel #2 of 96 here — alongside 95 others — read 10 September 2026
LEFT JOIN @leftjoin · 42,064 Telegram ranks this channel #4 of 95 here — alongside 94 others — read 29 August 2026
Инжиниринг Данных @rockyourdata · 23,767 Telegram ranks this channel #5 of 93 here — alongside 92 others — read 17 September 2026
Время Валеры @cryptovalerii · 30,829 Telegram ranks this channel #19 of 94 here — alongside 93 others — read 6 September 2026
Job for Analysts & Data Scientists @foranalysts · 36,643 Telegram ranks this channel #25 of 96 here — alongside 95 others — read 1 September 2026
Data Science. SQL hub @sqlhub · 35,969 Telegram ranks this channel #37 of 87 here — alongside 86 others — read 2 September 2026
Data Engineering Zoomcamp @dezoomcamp · 30,342 Telegram ranks this channel #48 of 69 here — alongside 68 others — read 15 September 2026
Reveal the Data @revealthedata · 27,839 Telegram ranks this channel #48 of 96 here — alongside 95 others — read 10 September 2026
Поступашки - ШАД, Стажировки и Магистратура @postypashki_old · 45,274 Telegram ranks this channel #50 of 90 here — alongside 89 others — read 28 August 2026
Анализ данных (Data analysis) @data_analysis_ml · 50,631 Telegram ranks this channel #51 of 93 here — alongside 92 others — read 25 August 2026
настенька и графики @nastengraph · 28,213 Telegram ranks this channel #52 of 94 here — alongside 93 others — read 9 September 2026
Поколение Python 🐍 @pygen_ru · 50,072 Telegram ranks this channel #61 of 93 here — alongside 92 others — read 25 August 2026
Клуб анонимных аналитиков @analyst_club · 33,554 Telegram ranks this channel #68 of 96 here — alongside 95 others — read 4 September 2026
Stepik – онлайн-курсы @stepik_courses · 24,445 Telegram ranks this channel #69 of 93 here — alongside 92 others — read 16 September 2026
GoPractice! @gopractice · 29,053 Telegram ranks this channel #76 of 97 here — alongside 96 others — read 9 September 2026
Connectable Jobs @zarubezhom_jobs · 102,984 Telegram ranks this channel #77 of 94 here — alongside 93 others — read 15 August 2026
Data Science Jobs @datasciencejobs · 22,057 Telegram ranks this channel #83 of 93 here — alongside 92 others — read 21 September 2026
Young & Junior - вакансии IT @young_june · 73,984 Telegram ranks this channel #88 of 99 here — alongside 98 others — read 20 August 2026
Job for Junior @jobforjunior · 85,036 Telegram ranks this channel #92 of 99 here — alongside 98 others — read 18 August 2026
This channel appears in 19 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.
“No Data No Growth | Pavel Bukhtik” (@nodatanogrowth), 12,773 subscribers as measured 17 September 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.