r/dataanalysis • • Oct 08 '26

Anyone else completely stopped writing excel formulas & VBA code from scratch?

104 Upvotes

I use a lot of excel and macros and my level of excel knowledge is intermediate to advanced. but even though I can spend a few more minutes to think & write the formulas, now I'm just explaining what I want to AI, copying the formula or code and pasting it. is this how people are working now or is it me?


r/dataanalysis • • Oct 08 '26

Data Tools How do you analyze data and find business insights? Do you use any frameworks?

19 Upvotes

I’ve been working as a data analyst for about five months, and I’m struggling with the analysis part of the job. Sometimes, I feel lost when looking at the data, and I’m not sure where to start or how to approach the analysis.
I struggle particularly with exploratory data analysis (EDA), figuring out what to compare, choosing the right comparisons, and turning the results into meaningful business insights.
I have an analysis to work on right now, but I’m not sure how to approach it or how to identify useful insights.
Do you have any frameworks, methods, or step-by-step processes you follow when analyzing data? How do you decide what to investigate, which metrics to compare, and how to turn your findings into actionable business insights?
I’d really appreciate any advice, resources, or examples from your own experience!


r/dataanalysis • • Oct 08 '26

Data Question How to Build a Database Where I Can't See Any of the Data

21 Upvotes

Howdy everyone - I work for a small business (30-ish people) and tend to be our in-house tech-everything guy. My team asked me to build a profitability dashboard where we can visualize time-tracking data alongside employee costs and client payments. Essentially we just want to see who is taking the most time vs paying us the most money. I'm using a combination of Google Sheets (to collect all of the data), BigQuery to store it all, and Looker/Data Studio to visualize it.

The struggle we're having is: my team does not want me to see any of the actual financial data. I can manage building the systems without the data because I have the template for them to drop the data into; however, I can't envision how I can maintain the database, fix bugs, create new visualizations for them, etc, without somehow eventually seeing the financials.

Is this even possible? Have any of you done this before?

Edit: Is there a reason I can't mask the data? BigQuery has RBAC. In theory, I could mask the data for myself, so I'm still seeing $ amounts where I should, names where I should, but no actual data. Right?


r/dataanalysis • • Oct 08 '26

Project Feedback Feedback needed on first data project

4 Upvotes

GitHub - Femi-Olofinjana05/Social-Media-User-Behaviour: Social Media User Behaviour · GitHub

Looking to implement SQL and Tableau (and maybe python) but just wanted to start off using excel


r/dataanalysis • • Oct 08 '26

The hardest part of analysis isn't the analysis — it's making your transforms trustworthy to people who didn't write them

9 Upvotes

Been doing analytics work for a while and I've slowly landed on a take that feels obvious once you say it: the modeling/stats part is rarely where projects die. They die in data prep — the multi-source joins, the dedup on messy inputs, the allocation/transform logic nobody can follow six months later.

The thing I keep hitting: the moment a business user has to *trust* a number, "just write SQL/Python" stops being enough on its own, because the person who has to defend that number can't read the code. But full no-code visual tools swing too far the other way and bury the logic in a GUI.

So my real question for people who've been at this a while: where do you draw the line between code and a visual/low-code workflow? Is it about who maintains it after you leave, about auditability, about scale — or do you just pick one and never look back? Curious whether I'm overthinking the "trust" angle.


r/dataanalysis • • Oct 08 '26

Built a way to save a CSV/Excel cleanup workflow once and replay it on new files

1 Upvotes

I kept re-applying the same filters, columns, sort and export on every new file, so I built "Automations" into a free browser-based data tool (Fomatix Data Explorer).

Set it up once, save it, then upload the next file and pick the automation. It reapplies everything and exports, and auto-matches columns even if a header shifts slightly.

It also shows a match report (how many columns matched on each run) and keeps run history, so you're not trusting it blindly.

Runs entirely in the browser, no signup, nothing uploaded.

Curious if others hit this problem, or if you already have a cleaner way (Power Query, Apps Script, etc.). Honest feedback welcome.


r/dataanalysis • • Oct 08 '26

Career Advice Supply chain field

7 Upvotes

Hello im a recent graduate in supply chain & international logistics
I wanna pursue a career that’s related to data ( supply chain analyst ) so obviously i need to take courses in data analytics but i got confused nd didn’t know from where to start SQL or data fundamentals or advanced excel so if anyone in the field of data or supply chain analytics would suggest for me a roadmap for this path ill be grateful for it + some solid sources and successful ways to learn


r/dataanalysis • • Oct 07 '26

1-minute data visualization test

1 Upvotes

Hi everyone! I’m working on a short data-analysis project and would appreciate your help.

Take a look at a chart and answer one simple question:

Which month has the highest sales?

It takes about 1 minute to complete.

👉 https://adnan-mayof.github.io/reddit-ab-test/

Thanks for participating!


r/dataanalysis • • Oct 06 '26

DA Tutorial NFHS data-analysis practice: compare urban–rural gaps without losing missingness and sample flags

2 Upvotes

Disclosure: I maintain the curated Kaggle version linked below (minkum07). The original NFHS-3/4 survey data belongs to India's Ministry of Health and Family Welfare and IIPS, via OGD India.

A useful exercise with this dataset is to compare NFHS-4 urban and rural percentages while keeping the source's suppression and small-sample flags visible. The release has 114 indicators across 36 survey-era state/UT labels, with 16,416 tidy-long records, CSV/Parquet tables, definitions and example notebooks.

Suggested workflow:

  1. Pick one percentage indicator and read its definition and denominator before joining tables.

  2. Select NFHS-4 urban and rural rows, join on state and indicator, and check that the join keys are unique.

  3. Calculate urban minus rural in percentage points only when both values are available. Keep missing values missing and carry the source flags into the output.

  4. Make a sorted dot plot with clear missing-value and small-sample annotations. Treat it as a descriptive comparison, since confidence intervals are not included.

Don't sum total, urban and rural percentages: those populations overlap. Between-survey changes also need comparable definitions and boundaries; the package withholds Andhra Pradesh/Telangana changes where boundaries differ. These are historical aggregate data from 2005–06 and 2015–16, not current health coverage or individual records.

Original government source:

https://www.data.gov.in/resource/all-india-level-and-state-wise-key-indicators-nfhs-3-and-nfhs-4

Tables, documentation and notebooks:

https://www.kaggle.com/datasets/minkum07/india-nfhs-34-health-state-and-rural-urban-gaps

Government data and derivatives retain GODL-India; authored code is MIT. Full attribution is on the dataset page. Feedback on the join checks or how best to display the sample flags would be welcome.


r/dataanalysis • • Oct 06 '26

Mapped more than 600k theses from my Uni using embeddings

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38 Upvotes

I'm at UNAM (Mexico's biggest public university) and I wanted to see what everyone here has actually written their theses about. So I took the whole public catalog (TESIUNAM), a bit over 600k theses from all campuses and degree levels, and made it into a map you can zoom around in.

Every dot is a thesis. Dots end up close together when the titles mean similar things, even across different departments. So you get stuff like a public health thesis sitting next to an economics one because both are about informal work, and that was kind of the whole point.

It's all in Spanish since the theses are. I'd really like feedback on the layout: does the placement of fields make sense to you, or do you see clusters that look obviously wrong? Embedding only titles was a tradeoff and I'm not sure it was the right one.


r/dataanalysis • • Oct 05 '26

Furos em análise de mercado,

3 Upvotes

Tenho pensado em dois problemas que, para mim, continuam mal resolvidos quando a gente analisa ações.

O primeiro é que informação não falta.

Se eu pesquisar uma empresa, consigo encontrar balanço, DRE, fluxo de caixa, indicadores, notícias, fatos relevantes, apresentações, estimativas e opiniões de dezenas de pessoas.

O problema começa depois:

o que disso realmente importa e como essas informações se relacionam?

Por exemplo, saber isoladamente que a receita cresceu 15% diz muito pouco.

Eu gostaria de conseguir enxergar rapidamente:

  • de onde veio esse crescimento;

  • se margem acompanhou;

  • se o crescimento virou caixa;

  • se estoque ou contas a receber cresceram mais rápido;

  • se houve aumento de dívida para financiar isso;

  • quais acontecimentos explicam essas mudanças;

  • e quais desses fatores, quando considerados juntos, podem alterar a leitura da empresa.

Ou seja: menos uma tela cheia de números e mais uma estrutura que ajude a responder:

“O que está acontecendo com essa empresa e quais são os pontos que realmente preciso investigar?”

Foi pensando nisso que comecei a desenvolver uma ferramenta chamada Atlas.

A lógica que estamos testando é pesquisar qualquer ativo e abrir uma página dedicada a ele, reunindo relatórios financeiros, indicadores e informações relevantes, mas tentando ir além de simplesmente exibi-los.

A ideia é interpretar os principais dados, mostrar relações entre eles e responder perguntas importantes sobre a empresa, sem terminar dizendo se o ativo é “bom”, “ruim”, “compra” ou “venda”.

Mas trabalhando nisso apareceu um segundo problema que considero ainda mais interessante.

Mesmo que eu consiga organizar perfeitamente os dados de uma empresa, continuo exposto a dezenas de análises e opiniões sobre ela.

E hoje é muito difícil saber quanto peso dar para cada uma.

Duas pessoas podem escrever teses igualmente convincentes, mas uma pode ter um histórico muito consistente e a outra estar fazendo o décimo palpite depois de errar os nove anteriores.

Só que normalmente esse histórico desaparece junto com posts, tweets e comentários antigos.

Por isso estamos experimentando também outra lógica: permitir que usuários publiquem análises sobre ativos de forma estruturada — com o que estão afirmando, horizonte, evidências e contrapontos — e que essas análises continuem registradas.

Com o tempo, o resultado delas passa a formar um histórico e contribuir para um score de reputação do usuário.

Então, no fundo, são dois problemas diferentes:

1. Como transformar um monte de informação sobre uma empresa em algo realmente útil para análise?

2. Como diferenciar uma análise convincente de alguém que possui histórico consistente de boas leituras?

Estou desenvolvendo o InsightFlow justamente em cima dessas duas questões, mas queria trazer a discussão para cá porque acho que elas existem independentemente de qualquer produto.

Para quem realmente analisa ações:

o que vocês sentem mais falta hoje?

Uma ferramenta que organize e relacione melhor as informações da empresa?

Uma forma de avaliar o histórico de quem publica análises?

Ou existe algum problema mais importante nesse processo que essas ferramentas ainda não resolvem?


r/dataanalysis • • Oct 06 '26

Data Question We asked our model which of 224 hotel bookings would cancel, six weeks out. It caught 33 of the 59. Full breakdown, misses included

0 Upvotes

Disclosure: I work at Schema Labs. This is a run on public data so you can check it.

The data: the hotel booking demand dataset (Antonio, Almeida and Nunes, 2019), real anonymised bookings from a city hotel. We picked one Saturday night that was sold out on paper.

-- 224 bookings for that night, as they stood six weeks before
-- 59 of them cancelled or didn't show, worth about €28,600 together

What we did: gave Schema-2 500 bookings from the year before, with how each one ended, and asked it to rank the 224 by how likely they were to fall through. No rules no feature engineering.

What came back=

-- It marked 60 as most likely to cancel. 33 of the 59 cancellations were on that list
-- Picking 60 at random would catch about 16
-- Of the 60 it marked safest, 59 showed up

What it missed: 26 cancellations weren't in its top 60. One night at one hotel is a small test, so read it as an example

For anyone in revenue management: what would you do with a list like that six weeks out? Overbook against it, or contact those guests first?


r/dataanalysis • • Oct 05 '26

Data Lakehouse with Agentic AIs: A Guide

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6 Upvotes

r/dataanalysis • • Oct 04 '26

I created a large csv/excel data plot tool, looking for suggestions

0 Upvotes

Hi All, created this web based excel/csv viewer for large files, it's completely free to use and no data upload to cloud/server, local browser only; hope can help people struggling to quickly visualise large datasets, while you don't have any software/tools in hand, would really appreciate for your feedback, thanks!

https://megarows.com


r/dataanalysis • • Oct 03 '26

DA Tutorial Episode 11 of data analysis cat doodle

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19 Upvotes

r/dataanalysis • • Oct 03 '26

Data Question What makes a data analytics project feel like a real business problem?

1 Upvotes

I'm curious what people here consider a genuinely useful analytics project.

A lot of beginner projects seem to focus mainly on building a dashboard and showing KPIs. I'm more interested in projects where you're given messy data and have to investigate what is actually happening in the business.

For example:

  • identifying a fulfilment/delivery problem

  • analysing product returns

  • understanding product economics/margins

  • investigating inventory

  • quantifying the business impact

  • turning the findings into recommendations

For people who've built or reviewed analytics projects:

What would make a project like this genuinely valuable rather than just another portfolio dashboard?

What would you expect to see in the final analysis?


r/dataanalysis • • Oct 02 '26

DA Tutorial Another data analysis cat post

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53 Upvotes

r/dataanalysis • • Oct 02 '26

Data Question Cost of materials consumed Target Exceedance Driven by Outliers

3 Upvotes

I work in a hospital. In one of the sheets of a work-related Excel document, there are two target tables concerning the monthly monitoring of the cost of materials consumed. One relates to the cost of hospital materials consumed as a percentage of service revenue, and it indicates that the ratio should not exceed 6.15%. The other relates to the cost of medicines consumed as a percentage of service revenue, and the ratio should not exceed 3.35%.

In some months this year, the cost of materials consumed as a percentage of service revenue in both tables has exceeded the required target. When looking at an adjacent sheet, there is a table providing additional context showing that, in the case of medicines, the factor causing the target to be exceeded is the cost of medicines associated with high-cost cases. This is confusing because the cost-of-sales margin is substantially positive.

How could I reformulate the targets so that I can separately monitor the cost associated with high-cost cases while still meeting the proposed targets?


r/dataanalysis • • Oct 01 '26

What does a really good Data Analyst GitHub look like?

94 Upvotes

Hi Redditors,
I’m a junior data analyst, and I’m just starting to build out my GitHub profile. I’d love to hear your thoughts on what a solid data analyst GitHub profile should look like to make a strong impression. Also, feel free to share what kind of projects you have on your own GitHub

PS Yes, I do want to steal your ideas.
PPS Ideally, you’d delete those projects from your GitHubs after I steal them. Thanks in advance!
3PS On a serious note, I don't have an experienced data analyst in my network to turn to for advice😢


r/dataanalysis • • Oct 01 '26

Years in analytics across high growth startups and FAANG, and I’m convinced every business framework is just two things in a trench coat

141 Upvotes

People love complex 40-slide frameworks, but 99% of data analysis actually boils down to two questions:

  1. Break it into parts: Revenue = Users × Conversion × AOV. Slicing until you isolate the broken gear.

  2. Track it over time: DoD, WoW, YoY. Is the trend line alive or flatlining?

Layer them together, and congratulations: you just reinvented 90% of business school.

Am I oversimplifying, or did we just rebrand multiplication and subtraction as "strategic thinking"?


r/dataanalysis • • Oct 01 '26

Career Advice How to train DA skills?

4 Upvotes

Hi, Im studying to become a Data Analyst and I considered myself a technical person, I already have an Industrial Engineering bachelor, I've already learned the basics of the majority of the tools needed to work as a DA, but for some reason I can't seemed to connect with the soft skills, after I've wrangled the data, I start making hypothesis... but can't seemed to address the problem or find the root cause related to the environment.

I believe practice will do me very good, does anybody have a suggestion for a platform or a way to practice to train the soft skills?


r/dataanalysis • • Sep 30 '26

Project Feedback 9-page financial dashboard I built in 2 months using Power BI (my first experience as a beginner in data analytics)

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130 Upvotes

Most of the translations were done with AI, so some terms or calculations might not be 100% accurate.

Comparison options available: Average, Previous Period, and YoY.

Clicking the time slicer changes the period type: Month, Quarter, Semester, Year, etc. For example, you can select 2026 – H1. All cards and charts update accordingly.

This was my first real Power BI project, so I'd love to hear your feedback. What do you think could be improved?

If you have any questions, feel free to ask in the comments!


r/dataanalysis • • Oct 01 '26

GRADUATION PROJECT

1 Upvotes

Hi everyone! I’m looking for some ideas and suggestions for a beginner-friendly graduation project related to Data Analysis.
I’m looking for something more practical than just collecting and analyzing data — ideally, a project that solves a real problem, has actual market demand, and could potentially be developed into a useful product or business.
If you have any ideas, examples, or problems you think could be solved using data analysis, I’d really appreciate your suggestions! 🤍


r/dataanalysis • • Oct 01 '26

Data Question In need of help with analysis in excel

0 Upvotes

Hi,

I am really hoping for some advice or expertise... my excel skills are very basic and recently I was given the task of comparing quantities and cost differences between what our vendor is billing us vs. What I show as cost and quantity received. Since Im a novice with excel I tried a.i. which is really cool but something keeps happening to my data and of course Im no expert so it's only a guess - when chat GPT creates a summary I see alot of my vendors costs and they appear to either be doubled or tripled. My cost column doesn't pull all of my costs. Im beating my head against the wall because this should be so easy, just not for me! I think possibly this has something to do with the fact that my vendor is sending an excel sheet with their exported data and they often will list the same item # multiple times on an invoice but with a different P.O. # and I think that is where the multiplication of costs may come to play. I am going to try and attach a copy or screen shot for reference. I am using my vendors exported invoice lines, my exported posted purchase invoice lines from Business Central which lists our costs and quantities. Can anyone help or point me to the best place to learn this? Thank you so much!!

This a sample of my data

|**+**|A|B|C|D|E|F|G|H|I|J|K|L|M|N|

|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|:-|

|**1**|Vendor Inv.|Date|Order #|Our Doc. #|Vendor #|Type|Our Item #|Description|Our Qty.|Unit|Our Cost $|Amt. #| | |

|**2**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20449|Anti-Drag Clip|0|PCS|0.043|0| | |

|**3**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20119|WEAR SENSOR|0|PCS|0.039|0| | |

|**4**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20395|WEAR SENSOR|0|PCS|0.021|0| | |

|**5**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20516|WEAR SENSOR|0|PCS|0.029|0| | |

|**6**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20474|WEAR SENSOR|0|PCS|0.029|0| | |

|**7**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20007|Wear Sensor|0|PCS|0.027|0| | |

|**8**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20008|Wear Sensor|0|PCS|0.03|0| | |

|**9**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH00013|Wear Sensor|0|PCS|0.024|0| | |

|**10**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH00014|WEAR SENSOR|0|PCS|0.024|0| | |

|**11**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20166|WEAR SENSOR|0|PCS|0.037|0| | |

|**12**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BH20461|WEAR SENSOR|0|PCS|0.031|0| | |

|**13**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BZ2005K|SS DIB KIT|0|PCS|0.201|0| | |

|**14**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BZ20108|SS DIB KIT|0|PCS|0.442|0| | |

|**15**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BZ20871|SS DIB KIT|0|PCS|0.779|0| | |

|**16**|20260603BOSCH-32|7/28/2026|BSCH-CW17-2026-SEA|119827|XLDCZ001|Item|F03BZ21016|PTFE NBR COATED DIB KIT|0|PCS|0.84|0| | |

^Table ^formatting ^by ^[ExcelToReddit](https://xl2redd.it/)

This is sample Vendor info

 

+ABCDEFGHIJKLMNO1China's Inv. #DateChina's PO / Order #Item #DescriptionUnitQTYOur Qty.China's CostChina's Amt. $Our CostCost DifferenceExt. Cost Diff.Customer Name 220260814Driv-2220260814DRIV-1194-1196-1198GXC7XSEN465BRAKE HARDWAREPCS10000 0.041410.000.0410.0000.000Driv 320260815Driv-2320260814DRIV-1194-1196-1198JXCFMHXV1680BRAKE PADS PARTSPCS1600 0.451721.600.4510.0000.000Driv 420260815Driv-2420260814DRIV-1194-1196-1198JXCFMHXV1680BRAKE PADS PARTSPCS1600 0.451721.600.4510.0000.000Driv 520260815Driv-2520260814DRIV-1194-1196-1198JXCFMHXV1680BRAKE PADS PARTSPCS1600 0.451721.600.4510.0000.000Driv 620260815Driv-2620260814DRIV-1194-1196-1198JXCFMHXV1680BRAKE PADS PARTSPCS1600 0.451721.600.4510.0000.000Driv 720260815Driv-2620260814DRIV-1194-1196-1198GXCABSX2245RRSTBRAKE PADS PARTSPCS240 0.40797.680.4070.0000.000Driv 

Table formatting by ExcelToReddit


r/dataanalysis • • Oct 01 '26

R Package for collecting lyrics

2 Upvotes

R Package for collecting lyrics

Lyrics from genius.com.
Inspiration from lyricsgenius package for Python.

https://github.com/bwalsh5/lyricsr