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Channel

Ivan Begtin

@begtin

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry

9,104subscribers

-43 since we began measuring on 5 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001018951478
TypeChannel
Username@begtin
DescriptionI write about Open Data, Data Engineering, Government, Privacy, Digital Preservation and etc. CTO&Founder of Dateno https://dateno.io Telegram @ibegtin Facebook - https://facebook.com/ibegtin Email [email protected] Ads/promotion agent: @k0shk
Created16 January 2016 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live8 November 2026
Measurements held25
Confirmed unchanged1 time, most recently 8 November 2026
On Telegramt.me/begtin

Topic

National news — 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 69% 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

9,0949,1489,1215 August 2026 — 9,147 subscribers6 August 2026 — 9,147 subscribers6 August 2026 — 9,148 subscribers9 August 2026 — 9,145 subscribers12 August 2026 — 9,139 subscribers16 August 2026 — 9,131 subscribers19 August 2026 — 9,127 subscribers23 August 2026 — 9,130 subscribers26 August 2026 — 9,119 subscribers28 August 2026 — 9,124 subscribers31 August 2026 — 9,122 subscribers10 September 2026 — 9,121 subscribers14 September 2026 — 9,115 subscribers18 September 2026 — 9,116 subscribers27 September 2026 — 9,114 subscribers5 October 2026 — 9,096 subscribers12 October 2026 — 9,095 subscribers15 October 2026 — 9,094 subscribers21 October 2026 — 9,099 subscribers25 October 2026 — 9,103 subscribers28 October 2026 — 9,102 subscribers30 October 2026 — 9,100 subscribers2 November 2026 — 9,097 subscribers5 November 2026 — 9,101 subscribers8 November 2026 — 9,104 subscribers9,1045 August 20268 November 2026
25 measurements spanning 95 days, net -43. 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 9,086–9,156 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)SubscribersChange
8 Nov 2026, 15:199,104+3
5 Nov 2026, 11:509,101+4
2 Nov 2026, 11:479,097-3
30 Oct 2026, 16:279,100-2
28 Oct 2026, 00:499,102-1
25 Oct 2026, 02:079,103+4
21 Oct 2026, 15:369,099+5
15 Oct 2026, 07:079,094-1
12 Oct 2026, 13:219,095-1
5 Oct 2026, 10:149,096-18
27 Sept 2026, 13:379,114-2
18 Sept 2026, 00:599,116+1
14 Sept 2026, 04:159,115-6
10 Sept 2026, 01:379,121-1
31 Aug 2026, 19:259,122-2
28 Aug 2026, 13:589,124+5
26 Aug 2026, 00:029,119-11
23 Aug 2026, 00:479,130+3
19 Aug 2026, 09:269,127-4
16 Aug 2026, 04:529,131first reading

Engagement

91 posts held, back to 10 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 50 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
11.7%
avg views ÷ 9,104 subscribers
Avg views / post
1,070
29 posts measured
Reaction rate
1.69%
reactions ÷ views · ER floor
Posts in window
29
of 91 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 12 November 2026
Posts held91 (10 July 2026 – 12 November 2026)
Views total30,969
Reactions total522
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Nov 2026, 12:14 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
≈2,770
Videos
≈5
Links
≈5,650

Lifetime counters from Telegram’s own channel header, read 12 November 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.

Reaction mix

1,277 reactions across 91 posts, in 26 distinct kinds. The most used accounts for 31.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍40831.9%
✍22517.6%
🔥18614.6%
❤1199.32%
💯856.66%
😢564.39%
🤔524.07%
🎉312.43%
❤‍🔥292.27%
⚡241.88%
🌚90.705%
🕊90.705%
👏80.626%
💔60.47%
🗿50.392%
😁50.392%
🤣40.313%
🤝30.235%
🍾20.157%
🏆20.157%
6 further kinds90.705%

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 91 of the 91 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 1,277 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 91 most recent posts we hold, published 10 July 2026 to 12 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
19
across the posts below
Posts paid on
7
of 91 we hold a reading for · 8%
Most on one post
11
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @begtin. 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 91 most recent posts we hold for this entry, published 10 July 2026 to 12 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: 5 of 29 posts held from the last 30 days (17.2%) 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).

12 Nov 2026, 06:40 UTC462 views14 reactionsread 12 November 2026

Поскольку я уже столько лет не работал по найму и испытываю аллергию на корпоративные коммуникации, то какие-то дискуссии понимаю недостаточно вовлеченно что-ли. И вот что это за срач вокруг HR Яндекса начался? И чем их подход к найму отличается отличается от российского и мирового ИТ крупняка? Да и вообще от всего "кровавого энтерпрайза" ?

🌚6🤔5👍3

Signed Ivan Begtin

11 Nov 2026, 15:07 UTC647 views16 reactionsread 12 November 2026

Очередная порция размышлений вслух: - Новые фронтирные модели всё более приближаются к тому чтобы заменять уже не джуниоров, а миддлов и даже синьёров. Уже сейчас они проектируют архитектуру ПО очень даже хорошо, а делают ревизию документов лучше многих экспертов. Я проверял на документах на которые я несколько лет назад писал отзывы и они находили в них даже больше ошибок и неточностей чем я тогда. - Я не просто так…

👍8✍4⚡2❤2

Signed Ivan Begtin

11 Nov 2026, 13:08 UTC789 views6 reactionsread 12 November 2026
Photo

В рубрике как это устроено у них Fields of The World (FTW) проект от Taylor Geospatial с геоданными по распознанным сельскохозяйственным полям с охватом 241 страны мира. Отдают данные, код, API, модели для распознавания, плагин к QGIS и тд. #opendata #opensource #ai #agriculture

🔥3👍2✍1

Signed Ivan Begtin

11 Nov 2026, 06:53 UTC663 views6 reactionsread 12 November 2026

Полезные ссылки про данные, технологии и не только: - The Data Product Platform Navigator на сайте Мартина Фаулера обзор того как создавать дата продукты и дата мэш. С одной стороны концептуально описано многое неплохо, а с другой слишком часто в описании концептуальных вещей автор сваливается в технологическую конкретику которая у многих может сильно отличаться. - auto-ontology фреймворк для Python от NVIDIA который…

✍6

Signed Ivan Begtin

10 Nov 2026, 15:55 UTC634 views8 reactionsread 12 November 2026
Photo

В продолжение ранее опубликованных данных официальной статистики, на портале открытых данных мы опубликовали полную базу статистики Статбанка Армстата в виде цельного набора данных. Это не первичные данные, ранее извлеченные и опубликованные "как есть", а собранная из них база данных. Что о ней важно знать: 1. База данных создана как сводная из 824 таблиц индикаторов к которым теперь можно делать запросы с помощью …

👍3🔥3✍2

Signed Ivan Begtin

9 Nov 2026, 09:32 UTC815 views35 reactions11 Starsread 12 November 2026
Photo

А вот и вторая книга над которой я работал в этом году Инвентаризация данных. Собрана из десятков моих текстов, лекций и презентаций и посвящена тому как инвентаризировать данные находящиеся в собственном управлении или под свои задачи - тут еще и пересекается с data discovery (поиском и обнаружением данных). Книга пересекается с книгой Каталоги данных поскольку многое в том как устроены каталоги данных проистекает …

👍18🔥8🎉5✍4

Signed Ivan Begtin

9 Nov 2026, 06:32 UTC780 views9 reactionsread 12 November 2026
Photo

Семантические типы данных - это смысловое и терминологическое описание содержимого колонки таблицы или привязанной к ключу записи в дата файле. Например, называется колонка country и можно предполагать что там название страны на одном из языков. Перечислены в колонке значения 2026-01-01, 2026-01-02 и тд., можно определить что это даты и так далее. Я много лет возился семантическими типами данных и даже писал об этом…

👍6✍3

Signed Ivan Begtin

7 Nov 2026, 10:02 UTC915 views20 reactionsread 12 November 2026
Photo

Когда-то очень давно я сделал такой простой сервис под названием Plain Russian по аналогии с Plain English. В сервисе я тогда адаптировал к русскому языку некоторое число формул оценки простоты текста о чем написал заметку на Хабре. За много лет сервис не менялся, не доходили руки, если честно. Хотя изначально задумка была в том чтобы кроме русского охватить и другие языки. С появлением ИИ сервисов и LLM вопрос стал…

❤‍🔥8🔥4👍3❤2🎉2🤔1

Signed Ivan Begtin

5 Nov 2026, 14:32 UTC≈1,210 views27 reactionsread 12 November 2026

По слухам российский портал открытых данных Москвы data.mos.ru скоро закроется с переносом датасетов оттуда на общий домен города www.mos.ru. Так что он у нас в планах на архивацию уже подвергся архивации. Там если брать последние версии наборов данных то всего 7.7GB данных, а если брать вообще все версии за все время то 70+GB. Есть ли смысл выкачивать все версии я не знаю, а последние версии сохранены и будут куда-т…

😢18✍3💯2🕊2😐2

Signed Ivan Begtin

5 Nov 2026, 08:24 UTC≈1,120 views23 reactionsread 12 November 2026
Forwarded from @opendataamPhoto

Для тех кто работает с геоданными и интересуется географией Армении мы открываем сервис Open Data Armenia Atlas https://maps.opendata.am/ Это геопортал на базе открытого кода TerriaJS и позволяющий не только подключать разные картографические слои, но и объединять их, настраивать уровень прозрачности и даже подключать собственные данные для визуализации. Сейчас мы подключили геоданные на нашем портале открытых данн…

🔥13❤4✍3👍3

Signed Ivan Begtin

4 Nov 2026, 12:35 UTC≈1,040 views16 reactionsread 12 November 2026

Мой маленький-большой пэт проект - это открытые связанные инструменты qddate и newsworker. qddate - это Python библиотека для ускоренного парсинга и идентификации шаблона дат, заточенная под парсинг миллионов строк в очень быстром режиме. Для Python'а есть библиотеки вроде dateparser и dateutil охватывающие большее число языков, но qddate существенно быстрее и в новом релизе 1.1.0 она была еще сильнее оптимизирована…

👍9🔥5✍2

Signed Ivan Begtin

4 Nov 2026, 06:15 UTC≈1,100 views14 reactionsread 12 November 2026
Photo

America on Data Centers интерактивная визуализация которую можно назвать data story по результатам анализа 10 202 общественных комментариев в 417 местных сообществах США за 2026 год. Интересна, и визуализация, и результаты. В визуализации много интерактивных графиков, причем те что показывают комментари на карте по клику открывают видео с конкретными выступлениями где произносят слова которые далее расшифрованы в вы…

❤5👍3🔥3✍2🤣1

Signed Ivan Begtin

Showing the 12 most recent of 91 posts we hold for @begtin. 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.

Forward network

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 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.

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.

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.

Если быть точным
@tochno_st · 19,605
Telegram ranks this channel #28 of 97 here — alongside 96 others — read 2 October 2026
Privacy Advocates
@prv_adv · 21,842
Telegram ranks this channel #43 of 98 here — alongside 97 others — read 22 September 2026
Нецифровая экономика
@antidigital · 24,479
Telegram ranks this channel #54 of 96 here — alongside 95 others — read 16 September 2026
настенька и графики
@nastengraph · 28,082
Telegram ranks this channel #73 of 94 here — alongside 93 others — read 9 September 2026
Об ЭП и УЦ
@ep_uc · 21,396
Telegram ranks this channel #76 of 97 here — alongside 96 others — read 24 September 2026
Evening Prophet
@eveningprophet · 19,092
Telegram ranks this channel #77 of 94 here — alongside 93 others — read 5 October 2026
Все о блокчейн/мозге/space/WEB 3.0 в России и мире
@blockchainRF · 20,455
Telegram ranks this channel #78 of 97 here — alongside 96 others — read 27 September 2026
Немкин
@ainemkin · 45,870
Telegram ranks this channel #85 of 97 here — alongside 96 others — read 7 September 2026

This channel appears in 8 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 8 November 2026 — this entry's latest reading, not the date you are reading this.

“Ivan Begtin” (@begtin), 9,104 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/begtin.

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.