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Channel

SQL | Data Analytics | AI

@sql_and_dbt

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

1,896subscribers

+12 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-1002193501295
TypeChannel
Username@sql_and_dbt
CreatedBetween 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live8 October 2026
Measurements held15
Confirmed unchanged1 time, most recently 8 October 2026
On Telegramt.me/sql_and_dbt

Topic

Technology — 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 16 September 2026 and assigned it the closest of 31 fixed categories, at 93% 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

1,8841,8991,891.57 August 2026 — 1,884 subscribers7 August 2026 — 1,884 subscribers7 August 2026 — 1,885 subscribers10 August 2026 — 1,888 subscribers13 August 2026 — 1,889 subscribers17 August 2026 — 1,894 subscribers20 August 2026 — 1,898 subscribers24 August 2026 — 1,897 subscribers28 August 2026 — 1,896 subscribers31 August 2026 — 1,892 subscribers4 September 2026 — 1,893 subscribers13 September 2026 — 1,896 subscribers16 September 2026 — 1,899 subscribers1 October 2026 — 1,898 subscribers8 October 2026 — 1,896 subscribers1,8967 August 20268 October 2026
15 measurements spanning 62 days, net +12. 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 1,882–1,901 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
8 Oct 2026, 09:561,896-2
1 Oct 2026, 21:371,898-1
16 Sept 2026, 14:581,899+3
13 Sept 2026, 01:361,896+3
4 Sept 2026, 02:141,893+1
31 Aug 2026, 10:371,892-4
28 Aug 2026, 01:041,896-1
24 Aug 2026, 21:151,897-1
20 Aug 2026, 20:141,898+4
17 Aug 2026, 10:081,894+5
13 Aug 2026, 09:031,889+1
10 Aug 2026, 18:211,888+3
7 Aug 2026, 20:521,885+1
7 Aug 2026, 15:321,884no change
7 Aug 2026, 13:341,884first reading

Engagement

20 posts held, back to 15 July 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 9 July 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

124 reactions across 20 posts, in 8 distinct kinds. The most used accounts for 62.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤7862.9%
👍2822.6%
👏75.65%
🔥54.03%
🥰32.42%
💩10.806%
😐10.806%
🤯10.806%

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 124 reactions 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 15 July 2025 to 9 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

9 Jul 2026, 03:01 UTC402 views7 reactionsread 7 August 2026

🔥 Top 8 SQL Tricks Every Data Person Should Know 1️⃣ QUALIFY instead of subqueries Filter window function results directly — no wrapping needed: QUALIFY ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC) = 1 2️⃣ EXCEPT in SELECT * (BigQuery) Grab everything but the noise: SELECT * EXCEPT (raw_payload, _synced_at) FROM t 3️⃣ COUNT(DISTINCT x) vs APPROX_COUNT_DISTINCT(x) On billions of rows, approxima…

❤4👍2🔥1

8 Jul 2026, 05:36 UTC416 views3 reactionsread 7 August 2026

https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claude

❤3

25 Mar 2026, 23:41 UTC≈1,260 views5 reactionsread 7 August 2026

https://blog.querylab.io/so-you-think-youre-a-bigquery-power-user-11e1e2334896

❤5

7 Mar 2026, 09:22 UTC≈1,370 views8 reactionsread 7 August 2026
Photo

🔰 The 4 Types of SQL Joins SQL joins combine rows from two or more tables based on a related column. Here are the different types of joins you can use: 1⃣ Inner Join Returns only the matching rows between both tables. It keeps common data only. 🔢 Left Join Returns all rows from the left table and matching rows from the right table. If a row in the left table doesn’t have a match in the right table, the right table…

👍6❤2

24 Feb 2026, 14:41 UTC≈1,290 views5 reactionsread 7 August 2026
Photo

Key Differences between List and Tuple in #Python

❤5

21 Feb 2026, 07:01 UTC≈1,340 views11 reactionsread 7 August 2026
File

Rui Machado / Analytics Engineering with SQL and dbt

👍4❤2👏2🔥2😐1

20 Feb 2026, 12:39 UTC≈1,290 views4 reactionsread 7 August 2026
Photo

What is difference between COUNT and COUNT (DISTINCT) ?

🥰3💩1

17 Feb 2026, 15:59 UTC≈1,050 views6 reactionsread 7 August 2026
Photo

SQL execution order📈 One day at an interview you will be asked this question

❤4👍2

16 Feb 2026, 14:16 UTC≈1,010 views5 reactionsread 7 August 2026

🚀 Essential SaaS Metrics: What Really Matters? A SaaS business runs on subscriptions. Its health = predictable revenue + strong retention + efficient growth. Here are the core metrics every SaaS founder, operator, and investor should track. --- ## 💰 Core Financial Metrics 🔹 MRR / ARR — Monthly / Annual Recurring Revenue Your primary indicator of predictable revenue. 🔹 ARPU — Average Revenue Per User How much re…

❤5

15 Feb 2026, 06:22 UTC815 views6 reactionsread 7 August 2026

All algorithms implemented in #Python - for education 📚 https://github.com/TheAlgorithms/Python

❤3👍1👏1🔥1

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

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

“SQL | Data Analytics | AI” (@sql_and_dbt), 1,896 subscribers as measured 8 October 2026. Telegram Register, tgregister.com/channel/sql_and_dbt.

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.