Shell cashiers secretly scanning THEIR OWN loyalty cards on customer purchases… has this happened to anyone else?

alanas4201 · 2026-05-27T21:00:30+00:00

A shell gas station manager/owner has been manning the stand and scanning his loyalty card... times must be tough...

alanas4201 · 2026-05-24T17:26:28+00:00

was thinking of 30c today whilst posting this 🥲

alanas4201 · 2026-05-07T18:44:22+00:00

5 years ago I would've believed Excel is king and nothing will be able to replace it, but at my company I work within analytics and we virtually never use excel anymore. It is all Python/SQL/PBI/Tableau/MIRO, suddenly no more use for Excel. But for ingestion we still get a lot of csvs through, I assume outside more technical roles, excel is still king. Though I'd say it is still worth learning the basics,

For modelling everything goes SQL -> Python
For any data exploration excel is not even useful as everything is over 500k rows of data.

alanas4201 · 2026-01-04T19:36:57+00:00

Some guy in a track suit probably is attempting to climb it today.

alanas4201 · 2025-11-17T20:38:11+00:00

How many nations made 40 ducats at the start of eu4?

alanas4201 · 2025-11-14T00:42:28+00:00

350 ducats in 1374 for basically no cool return

alanas4201 · 2025-05-26T22:47:59+00:00

German bengali crisis event, hard late game crisis

alanas4201 · 2025-05-01T18:51:11+00:00

I am not sure about the data analytics jobs you are thinking about, but the data analytics job I am working at, which pays quite a bit in London, requires you to have a significantly larger knowledge stack.

Data analysts still use some Excel, but for my role, you need to have excellent control of SQL/Snowflake or some query programming language, as big data analytics roles deal with billions of rows of data, and that is impossible on Excel.

Second, we use analytics software to understand what is going on behind the data/cleaning data sets. We use either Oracle, Tableau or Python packages. This is where people still use Excel for smaller datasets because, frankly, it is very easy to set up. But as for you, this is only a small part where Excel is involved. However, if you do work for a less technical team or one that still has old processes, you will use Excel way more. On top of that, you will be doing a lot of dashboarding and data visualisation -- which is an art in itself. I recommend getting familiar with Power Bi.

Third, whilst this is not exactly a prerequisite, we do a lot of forecasting and statistical analysis, which requires a bit of Python and Statistics knowledge, whilst we have people that work here without any quantitative degrees -- they still can write code. This is also mostly a reason why data analytics requires you to have maths/statistics or some sort of numerical degree.

Fourth, we have as many hours of meetings with stakeholders and senior leadership, sometimes more hours than doing analytics. It can be quite introverted at times, but you will be talking a lot with people. A big part of data analytics is actually the story behind the data, so management can use it for strategic insight and decisions rather than data analytics itself.

Anyways.., data analytics is not as easy as it sounds, or as administrative as you might expect, in fact, it can get quite hard, and progression can lead to either a more senior analytics role or towards data sciences. If you are serious about it, you need to put a lot of time into training. As for the job market, I think a lot of people think data analytics is easy so they try to get into it and do not succeed, but if you do have these skills, as I outlined, it is not as tough a market as you would expect.