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Channel

Кусочек пиццы | Аналитика данных

@dataslice

On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

627subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002776406409
TypeChannel
Username@dataslice
DescriptionПро карьеру, аналитику, ии и все, что с ними связано Для связи: @ikovalevv
CreatedBetween 1 June 2025 and 30 September 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live8 August 2026
Measurements held2
On Telegramt.me/dataslice

Growth

6277 Aug 2026, 17:51 — 627 subscribers8 Aug 2026, 03:01 — 627 subscribers7 Aug 2026, 17:518 Aug 2026, 03:01
2 measurements taken within a single day. 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 626–628 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
8 Aug 2026, 03:01627no change
7 Aug 2026, 17:51627first reading

Engagement

20 posts held, back to 1 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
46.8%
avg views ÷ 627 subscribers
Avg views / post
294
6 posts measured
Reaction rate
3.98%
reactions ÷ views · ER floor
Posts in window
6
of 20 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
WindowRolling 30 days · latest post in window 6 August 2026
Posts held20 (1 June 20266 August 2026)
Views total1,761
Reactions total70
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 03:01 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
28
Links
35

Lifetime counters from Telegram’s own channel header, read 8 August 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.

Reaction mix

227 reactions across 19 posts, in 8 distinct kinds. The most used accounts for 37.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥8637.9%
custom 54178563062141125907131.3%
custom 53504446727895197654921.6%
custom 5442983582882601962114.85%
🙏52.20%
custom 538410401795569012920.881%
custom 538431458731730852520.881%
custom 541574170054076168410.441%

Custom emoji. 6 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.

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 19 of the 20 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 227reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 1 June 2026 to 6 August 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
1
across the posts below
Posts paid on
1
of 19 we hold a reading for · 5%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @dataslice. 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 20 most recent posts we hold for this entry, published 1 June 2026 to 6 August 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

6 Aug 2026, 08:39 UTC155 views9 reactionsread 8 August 2026

Как LLM убеждает нас верить в ошибочные гипотезы Замечали ли вы, что ИИ часто вам поддакивает? Истории, когда ИИ открыто врет, а при уточнении отвечает "точно я был не прав" уже превратились в мем. Но у этого «подхалимства» есть обратная, куда более опасная сторона. Свежее исследование MIT подсветило фундаментальную проблему: ИИ спроектирован так, чтобы поддакивать нам (AI Sycophancy), загоняя даже опытных специал

custom 54178563062141125909

3 Aug 2026, 05:58 UTC217 views6 reactionsread 8 August 2026

Как статистика применяется в бизнесе? Недавно получил вопрос от менти: «Я прошла курс, прочитала книгу Сары Бослаф, поняла все принципы и методы. Однако я всё ещё не могу понять, как это всё применять на практике». Я попробовал разделить все концепции на 3 уровня в зависимости от того, на какой вопрос бизнеса они помогают ответить. ™️Уровень 1. Описать то, что уже произошло Вопрос бизнеса: как у нас дела и на что

custom 54178563062141125905custom 53504446727895197651

3 Aug 2026, 05:58 UTC236 views17 reactionsread 8 August 2026

отвечает только на вопрос, насколько наблюдаемая разница необычна для мира без эффекта. Практический вывод: p-value решает, отвергаем ли мы гипотезу, но ничего не говорит о размере эффекта. Что именно вы получили - показывает доверительный интервал из Уровня 2. Выбор критерия. Определяет, по какой формуле считается разброс разности средних. Решается природой метрики: доли, средние, отношения сумм и ранги считаются

custom 541785630621411259017

27 Jul 2026, 06:00 UTC398 views27 reactionsread 8 August 2026

Кейс с собеседования: дизайн AB-теста для новых тарифов Этот кейс давали на собеседовании в дейтинг-приложение, но условие универсальное для любого подписочного сервиса. Контекст кейса: Представьте, что вы аналитик в дейтинговом приложении. У вас в продукте есть 3 тарифа, которые отличаются функционалом и количеством доступных действий в месяц + триал период на 1 неделю. К вам приходит продакт и говорит: хочу под

🔥25custom 53504446727895197652

24 Jul 2026, 06:58 UTC367 views3 reactionsread 8 August 2026

Наткнулся на интересное выступление Константина Крестникова (CTO GigaChain) на Data Fest. Он рассказал про этапы развития агентов, Harness и loop-циклы. Если вы когда-либо хотели узнать про что-то из перечисленного, го смотреть: https://www.youtube.com/watch?v=aBcW01Qbuws

🙏3

23 Jul 2026, 05:43 UTC388 views8 reactionsread 8 August 2026

Что такое сетевой эффект? Классический A/B стоит на простом допущении: контроль и тест не влияют друг на друга. Поведение юзера из группы B определяется только тем, что ему показали, и никак не отражается на юзерах из группы A. Это называется SUTVA, Stable Unit Treatment Value Assumption. Именно поэтому эффект фичи можно посчитать как обычную разницу средних между группами. Проблема в том, что иногда это допущени

custom 54178563062141125904🔥2custom 53504446727895197652

13 Jul 2026, 05:55 UTC452 views13 reactionsread 8 August 2026

Реальность 2026 года: ИИ не уменьшает нагрузку, а увеличивает количество дел, которыми мне приходится заниматься одновременно. Компаниям нравится эта математика. Один человек с ИИ-агентами теперь делает то, что раньше делали двое или трое. Зарплаты меньше - производительность та же, а то больше. Чистая победа для бизнеса (особенно если не считать затраты на токены) В то же время, если смотреть на это глазами испо

custom 541785630621411259010custom 53504446727895197653

8 Jul 2026, 07:22 UTC485 views6 reactionsread 8 August 2026

Anthropic выпустила новую библиотеку подсказок для Claude Code прямо в документации Пока что там 52 подсказки, сгруппированные по типам с объяснениями, почему и как это работает. Забираем здесь.

🔥6

6 Jul 2026, 05:41 UTC494 views5 reactionsread 8 August 2026

Потестировал новую модель Claude Fable на выходных для своего пет-проекта. Для тех, кто в танке: Anthropic вернули Fable в открытый доступ. До 7 июля модель можно покрутить бесплатно (по крайне мере в рамках подписки Pro). Я решил, не терять время и потестировать ее на своем сайте. Что сделал: 1) Сделал ревью UI/ UX на сайте, используя Claude Design и taste-skill и внес некоторые правки 2) Сделал ревью контента и

custom 53504446727895197654🙏1

1 Jul 2026, 06:02 UTCviews —

Кусочек пиццы | Аналитика данных pinned «Как потрогать статистику руками? Когда я учил статистику, у меня была одна проблема: формулы я запоминал, а картинку в голове собрать не мог. Вот есть, например, формула дисперсии. Я мог посчитать её на бумаге, мог написать на собесе. Но что она представляет…»

1 Jul 2026, 05:47 UTC614 views22 reactions1 Starread 8 August 2026

Как потрогать статистику руками? Когда я учил статистику, у меня была одна проблема: формулы я запоминал, а картинку в голове собрать не мог. Вот есть, например, формула дисперсии. Я мог посчитать её на бумаге, мог написать на собесе. Но что она представляет на самом деле я понять не могу. Как говорят - "не чувствовал на пальцах" Или центральная предельная теорема. Сформулировать ее можно просто заучив, но осозна

🔥20custom 54178563062141125902

29 Jun 2026, 05:59 UTC423 views16 reactionsread 8 August 2026

Я не люблю А/В-тесты 🤷 На днях увидел очередную рекламу курса по А/В-тестам и поймал себя на мысли: почему это стало едва ли не самой хайповой темой в аналитике? На каждом собесе обязательно спросят про А/В. Грейд аналитика часто меряют тем, насколько глубоко он шарит в стат.методах: мощность, поправки на множественные сравнения, бутстрап, CUPED. Со стороны кажется, будто умение грамотно раскатить эксперимент - эт

custom 541785630621411259015custom 54157417005407616841

Showing the 12 most recent of 20 posts we hold for @dataslice. 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.

Citation-graph rank

Citation-graph rank — 198,638 of 1,336,469entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Mentions

Named by 4 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.

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.

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 8 August 2026 — this entry's latest reading, not the date you are reading this.

“Кусочек пиццы | Аналитика данных” (@dataslice), 627 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/dataslice.

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.