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Channel

PrepNPlaced

@dataanalyticsbuddy

On this record: Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry

27,813subscribers

-191 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001891664362
TypeChannel
Username@dataanalyticsbuddy
CreatedBetween 1 October 2022 and 30 September 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live17 August 2026
Measurements held11
Confirmed unchanged1 time, most recently 17 August 2026
On Telegramt.me/dataanalyticsbuddy

Growth

27,81328,00427,908.57 August 2026 — 28,004 subscribers7 August 2026 — 28,004 subscribers8 August 2026 — 27,991 subscribers9 August 2026 — 27,982 subscribers10 August 2026 — 27,963 subscribers11 August 2026 — 27,949 subscribers12 August 2026 — 27,921 subscribers13 August 2026 — 27,894 subscribers15 August 2026 — 27,869 subscribers16 August 2026 — 27,844 subscribers17 August 2026 — 27,813 subscribers7 August 202617 August 2026
11 measurements spanning 10 days, net -191. 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 27,784–28,033 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Aug 2026, 19:1627,813-31
16 Aug 2026, 14:5327,844-25
15 Aug 2026, 00:0627,869-25
13 Aug 2026, 12:3627,894-27
12 Aug 2026, 11:5427,921-28
11 Aug 2026, 11:1427,949-14
10 Aug 2026, 11:3627,963-19
9 Aug 2026, 14:1527,982-9
8 Aug 2026, 17:3527,991-13
7 Aug 2026, 18:3028,004no change
7 Aug 2026, 18:2228,004first reading

Engagement

31 posts held, back to 11 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 23 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.50%
avg views ÷ 27,813 subscribers
Avg views / post
973
24 posts measured
Reaction rate
0.095%
reactions ÷ views · ER floor
Posts in window
25
of 31 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. It is computed over the 7 of 24 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 16 August 2026
Posts held31 (11 July 202616 August 2026)
Views total23,343
Reactions total7
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken17 Aug 2026, 13:36 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

10 reactions across 9 posts, in 3 distinct kinds. The most used accounts for 80.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
880.0%
👏110.0%
😁110.0%

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 10 of the 31 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 10reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 31 most recent posts we hold, published 11 July 2026 to 16 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.

Recent posts

16 Aug 2026, 07:07 UTC366 views1 reactionsread 17 August 2026

Hey Your Project Webinar is at 1 pm IST and Abhinav Singh a 7 Year Experience Data Engineer is going to take your Webinar on *Azure Data Engineering Project Link to Join the Session after 30 minutes - https://us06web.zoom.us/j/82084947108?pwd=ctzqc2t9EzNXfyVvlR7JzIwv7LM8zc.1 Dont miss today otherwise you will regret tomorrow✅️

😁1

13 Aug 2026, 06:16 UTC750 viewsread 17 August 2026

Most people fail data engineering interviews for the same reason. Not because they don't know Spark. Not because their SQL is weak. But because when the interviewer asks "how would you make this pipeline reliable?", they freeze. The answer was never one clever trick. It's idempotency, retries, checkpointing, monitoring, and data quality checks. Say those five and you've already beaten most candidates. I put togethe

12 Aug 2026, 08:58 UTC710 viewsread 17 August 2026

FREE LIVE WEBINAR — This Sunday 💸 What is Spark? What are RDDs, DataFrames & PySpark? If Spark still feels like a black box, this is the session that fixes it. 📅 Sunday, 16 August 🕛 12:00 PM – 2:00 PM IST 🎙️ By Pragya Rathi — Data Engineer @ 7-Eleven 💰 100% Free What you'll walk away with: ✅ What Spark actually is & why every DE job asks for it ✅ RDD vs DataFrame — when to use what ✅ PySpark basics you can start

11 Aug 2026, 11:07 UTC656 viewsread 17 August 2026

🚀 FREE Live Webinar — Azure Data Engineering (End-to-End Project) Build one real Azure pipeline with me — live, from scratch. No slides-only theory. 📅 Sunday, 16 August 2026 ⏰ 1:00 – 3:00 PM IST 💰 Free · Beginner friendly · Hands-on What we'll build together: 1️⃣ Azure Data Factory → ingest source data on a schedule 2️⃣ ADLS Gen2 + Storage Account → land raw files in a lakehouse zone 3️⃣ Azure Databricks → clean &

10 Aug 2026, 08:48 UTC720 viewsread 17 August 2026

FREE LIVE WEBINAR — This Sunday 💸 What is Spark? What are RDDs, DataFrames & PySpark? If Spark still feels like a black box, this is the session that fixes it. 📅 Sunday, 16 August 🕛 12:00 PM – 2:00 PM IST 🎙️ By Pragya Rathi — Data Engineer @ 7-Eleven 💰 100% Free What you'll walk away with: ✅ What Spark actually is & why every DE job asks for it ✅ RDD vs DataFrame — when to use what ✅ PySpark basics you can start

9 Aug 2026, 07:00 UTC876 viewsread 17 August 2026

Major Webinar to Help you to Understand How to Get interview Calls in 45 Days Join the Webinar at 1 pm IST Today - https://us06web.zoom.us/j/82084947108?pwd=ctzqc2t9EzNXfyVvlR7JzIwv7LM8zc.1 Please Join the Class on Time & This is very important Webinar for all

8 Aug 2026, 08:17 UTC958 viewsread 17 August 2026

📌 183 apprenticeships & internships are open right now — and every single one was checked against the official notification. Freshers know the trap: Every job wants 1 year of experience. Nobody wants to be the one who gives it to you. 🙃 🔗 https://www.prepnplaced.com/apprenticeships Apprenticeships are the way out. Real work, real pay, real line on your resume. What's on PrepNPlaced right now 👇 🏛️ Government & PSU

5 Aug 2026, 18:10 UTC≈1,070 views1 reactionsread 17 August 2026

🚀 End-to-End Data Analytics Preparation Kit – Everything You Need to Crack a Data Analytics Job! Master the skills that companies are looking for with our complete preparation kit. 💰 Price: Just ₹999 🎁 What's Included? ✅ Complete End-to-End Data Analytics Preparation Kit ✅ Exclusive access to our weekend webinars (Members Only) ✅ Lifetime access to session recordings on PrepNPlaced ✅ Interview-focused learning, pr

1

Showing the 12 most recent of 31 posts we hold for @dataanalyticsbuddy. 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.

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.

Data Analyst Jobs
@jobs_SQL · 91,182
Telegram ranks this channel #14 of 86 here — alongside 85 others — read 17 August 2026
FRESHER OFFCAMPUS JOB DRIVES
@fresher_offcampus_drives · 109,408
Telegram ranks this channel #51 of 91 here — alongside 90 others — read 14 August 2026
Mohan Careers
@mohancareers · 144,285
Telegram ranks this channel #69 of 92 here — alongside 91 others — read 13 August 2026

This channel appears in 3 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 August 2026 — this entry's latest reading, not the date you are reading this.

“PrepNPlaced” (@dataanalyticsbuddy), 27,813 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/dataanalyticsbuddy.

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.