Telegram RegisterThe public register of Telegram

Channel

Книги по аналитике (BA, DA, SA, PA)

@analyst_books

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

2,121subscribers

-2 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001664449009
TypeChannel
Username@analyst_books
CreatedBetween 1 December 2021 and 17 September 2022— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 11 August 2026
On Telegramt.me/analyst_books

Growth

2,1212,1232,1227 August 2026 — 2,123 subscribers7 August 2026 — 2,123 subscribers7 August 2026 — 2,122 subscribers11 August 2026 — 2,121 subscribers7 August 202611 August 2026
4 measurements spanning 4 days, net -2. 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 2,121–2,123 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 07:412,121-1
7 Aug 2026, 21:252,122-1
7 Aug 2026, 04:002,123no change
7 Aug 2026, 03:482,123first reading

Engagement

20 posts held, back to 17 September 2022the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
28.4%
avg views ÷ 2,121 subscribers
Avg views / post
603
1 post measured
Reaction rate
1.33%
reactions ÷ views · ER floor
Posts in window
1
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 19 July 2026
Posts held20 (17 September 202219 July 2026)
Views total603
Reactions total8
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:57 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.

Reaction mix

198 reactions across 19 posts, in 6 distinct kinds. The most used accounts for 42.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍8542.9%
6532.8%
🔥3819.2%
🤔42.02%
💯31.52%
🥱31.52%

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 20 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 198reactions 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 17 September 2022 to 19 July 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.

Recent posts

19 Jul 2026, 11:43 UTC603 views8 reactionsread 7 August 2026
Forwarded from @data_study

Из-за глупой ошибки в SQL компания чуть не потеряла 5 млн. и репутацию перед поставщиками Наши действия при работе с данными напрямую влияют на конечные метрики в бизнес-отчетах. И любая ошибка аналитика может стать критичной Из-за нехватки знаний и опыта аналитики допускают максимально глупые ошибки в конструкции CASE, которые критически могут менять метрики. ❌ пишут неправильный порядок условий ❌ не пишут ELSE

👍53

1 Jun 2026, 12:16 UTC≈2,600 views9 reactionsread 7 August 2026
Photo

SQL: быстрое погружение / Уолтер Шилдс Книга для тех, кто только начинает изучение SQL и работу с базами данных. Скачать книгу

9

26 Mar 2026, 14:30 UTC≈1,920 views2 reactionsread 7 August 2026

Устали на работе выполнять рутинные задачи или киснуть без роста в профессии и перспектив развития? Хватит тратить свое время на выгрузку данных из Excel, ручные сверки и обновление отчётов! Хотите перейти от monkey job к реальной аналитике и инженерии данных, но не хватает навыков и инструментов? Я запускаю новый поток курса «Продвинутый SQL и автоматизация витрин данных» — и он создан именно для тебя! Что освоишь

2

22 Nov 2025, 12:50 UTC≈3,290 views28 reactionsread 7 August 2026
Photo

Статистика и котики / Владимир Савельев "Из этой книги вы узнаете, что такое дисперсия и стандартное отклонение, как найти t-критерий Стьюдента и U-критерий Манна-Уитни, для чего используются регрессионный и факторный анализы, а также многое и многое другое. И все это – на простых и понятных примерах из жизни милых и пушистых котиков, которые дарят нам множество приятных эмоций." Скачать книгу

🔥1410👍2💯1🤔1

9 Aug 2025, 15:55 UTC≈6,580 views8 reactionsread 7 August 2026
Photo

Analytics Engineering with SQL and dbt / Rui Machado "With the shift from data warehouses to data lakes, data now lands in repositories before it’s been transformed, enabling engineers to model raw data into clean, well-defined datasets. The data build tool (dbt) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service

🔥5👍21

9 Jul 2025, 15:30 UTC≈6,630 views14 reactionsread 7 August 2026
Photo

Оптимизация запросов в PostgreSQL / Домбровская Г. "Книга поможет вам писать запросы, которые выполняются быстро и вовремя доставляют результаты. Вы научитесь смотреть на процесс написания запроса с точки зрения механизма базы данных и начнете думать, как оптимизатор базы данных. Объясняется, как читать и понимать планы выполнения запросов, какие существуют методы воздействия на них с точки зрения оптимизации произв

🔥64👍4

26 Jan 2025, 17:38 UTC≈7,120 views20 reactionsread 7 August 2026
Photo

Кирилл Еременко / Работа с данными в любой сфере "Что общего у аналитика данных и Шерлока Холмса? Как у Netfl ix получилось создать 100%-ный хит — сериал «Карточный домик»? Ответ кроется в правильном использовании данных. Эта книга — практическое руководство и увлекательное путешествие в науку о данных, независимо от того, хотите ли вы использовать анализ данных в своей профессии, собираетесь ли стать аналитиком дан

👍127💯1

24 Dec 2024, 10:15 UTC≈8,120 views12 reactionsread 7 August 2026
Photo

Дэн Роэм / Визуальное мышление "Визуализация — это простой и остроумный способ объяснить трудные проблемы и решить запутанные вопросы. Прочитав эту книгу, вы поймете, что один рисунок подчас стоит тысячи слов. Автор книги демонстрирует, как можно ясно представить идею путем ее визуализации и убедительно донести суть до других людей, зрительно разделив ее на отдельные компоненты и применив инструменты визуального мыш

8👍2🤔2

19 Nov 2024, 17:52 UTC≈7,880 views3 reactionsread 7 August 2026
Photo

Роб Фитцпатрик / Спроси маму "Обычно у мамы не выясняют, хороша ли та или иная бизнес-идея, потому что она любит вас и не хочет ранить правдой. Да, это так, но не совсем. Вы не должны спрашивать, является ли ваша идея хорошей. Это плохой вопрос, потому что не только мама, но и все остальные на него будут лгать, хотя бы чуть-чуть. И в самом деле, это же не их обязанность, говорить всегда правду. Выяснять истину и дел

👍21

10 Nov 2024, 16:20 UTC≈7,950 views9 reactionsread 7 August 2026
Photo

Джин Желязны / Говори на языке диаграмм "Как наилучшим образом представить ваши идеи с помощью диаграмм? Как привлечь и удержать внимание аудитории? На страницах этой книги вы найдете все необходимое для этого: практические рекомендации по выбору типа диаграммы (круговая, линейчатая, точечная и т.д.), правила подготовки и использования каждого из них, а также мастер-класс по исправлению неудачных диаграмм." Скачать

👍72

30 Sept 2024, 15:32 UTC≈4,220 views0 reactionsread 7 August 2026
Forwarded from @data_study

Оконные функции простым языком - Фреймы (часть 2) Спустя 2 года после написания первой части статьи наконец дошли руки до второй части. 🚨 Материал исключительно для новичков в SQL и применении оконок, опытные SQLисты проходите мимо. А то там в комментариях уже начали накидывать сложные кейсы, что я их в статье не указал, и вообще не расписал учебник вместо статьи со всей теорией и практикой в одном месте 😅 Читать

2 Sept 2024, 16:33 UTC≈8,150 views4 reactionsread 7 August 2026
Photo

Bill Inmon / Building the Data Lakehouse "The data lakehouse architecture presents an opportunity comparable to the one seen during the early years of the data warehouse market. The unique ability of the lakehouse to manage data in an open environment, blend all varieties of data from all parts of the enterprise, and combine the data science focus of the data lake with the end user analytics of the data warehouse wi

👍3🤔1

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

Citation-graph rank

Citation-graph rank — 946,472 of 1,160,990entries 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

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

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.

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

“Книги по аналитике (BA, DA, SA, PA)” (@analyst_books), 2,121 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/analyst_books.

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.