I started as customer service with my company, but recently got promoted by the Client Services director to help with locating trends, and also keeping together data for calls for upcoming “outbound call projects.” He mentioned that in our feedback sessions regarding their Salesforce and website upgrades and mentioned the way that I approached certain issues and solutions I proposed, they felt right giving this opportunity to learn something new and be of assistance, behind the scenes. Great opportunity, I also believe I’m gonna be a great benefit. I only used excel for school work so nothing crazy but as soon as I learned what formulas are and how to make the charts look right, adding calculations/formulas to show results, it’s been so fun and interesting learning about how to make the most and how people have made the most of excel. Applying AI to it makes it so much more fun and of course easier. I’ve used ai to teach me formulas and what each component in the formula means. Ive learned to read existing formulas, but have had AI mostly make my formulas for less room for user error. I give it what I think
Up and we go from there. Feels like I’m gonna do great in this job and I look forward to learning more.

I’ve been trying to make cleaner, more readable graphs lately and realized most default tools don’t look that great out of the box.

Excel works, but it often ends up looking… basic.

Some tools look better, but take way more effort to learn.

So I’m curious what people actually use in practice:

• what you consistently go back to
• what gives you good results without too much friction
• what you’d recommend to someone who cares about how charts actually look
• Bonus if you’ve switched tools and noticed a big difference.

Im learning data analysis and curious which skills professionals feel make the biggest difference early on.

So yeah. AI tool to talk to Epstein and his files

Good day everyone, I wanted to find out how important is ETL in data analysis? I'm contemplating buying an Azure Data Engineering course in order to learn ETL and Databricks. Is this overkill?

Hey I got tagged to a project at my organisation for a RETAIL client. They need someone to make sense of their data, find patterns, forecast and explain their data to them so they can try new pricing and discounts depending on the geographical location and price profiles.

I've worked in the past as part of the team where most things were already set up and I just got requirements from a BA and created the workbooks.

This client doesn't have that and I'm the only one here who's gonna be creating tableau reports.

Anyone suggest how to start and do this from scratch?

What key points should I consider?

How should I approach the cloud vs server approach?

How do I join and figure out the data they have cause right now all they have is data in some snowflake server and I have to be the person who uses sql to fetch that.

Any suggestions would be really appreciated.

In real-world analytics / BI environments, how do you decide when Silver-layer data is ready for downstream analysis?

I understand the standard cleaning steps (null handling, deduplication, type casting, formatting, standardization, etc.), but I’m trying to understand what “production-grade” Silver data actually looks like in practice.

More specifically:

* What data quality checks do you enforce in Silver vs what you intentionally leave for Gold?
* Do you rely on explicit rules (tests, thresholds, data contracts, SLAs), or is it mostly driven by business context and downstream use cases?
* In financial datasets, what are the minimum validations you would never skip before exposing data to analysts or BI consumers?

I’m trying to avoid two extremes:

* over-engineering Silver until it effectively becomes Gold
* under-validating data and pushing unreliable datasets downstream

I’d really appreciate real-world examples or mental models from production environments, especially around how you draw the line between “clean enough” and truly analysis-ready data.

I have been working on collecting raw data from kalshi markets and now have about a week worth of data I collected. I want to do some ML or make a bot, was wondering if anyone had advice for next steps as I am new to the space

I'd like to work in data analytics but want to make sure my foundation is solid. Would love some book recommendations, preferably one with practice questions but okay if not if its a really good book

Hi

I just done my final uni project on analytics

I used python for cleaning

There were multiple data sets were involved (some are 1.8+million rows)

I have done my analysis and reviews and recommendations

The only thing I regretted is that i haven't cleaned data properly because the entire data is too messy and given in "raw txt" format by professor

Whatever i do with cleaning still some mistakes were

So i all want to ask you is

Suggest some youtube tutorials and books for me to improve data cleaning

And also which other software should i learn other than python for cleaning data

I am looking for a free, open-source free would be great, for a dms, or cms. Possibly something completely different. I'm not sure "what" type of software system I should be looking for and researching.
I am looking for a software system to digitize our paper system. Specifically, our promissory notes.
I would like to be able to scan the paper P.N. into a jpg (directly into the system isn't necessary). Then, be able to create multiple fields to enter the data from the PN. Fields like: PN Number, Ticket Number, Date, Type of PN, Name, ID Number, Address, Phone Number, Total Charge, Amount Paid, Amount Due, Total Due With Admin Fee, Vehicle License Plate, and Vehicle Description. When a PN is generated we charge a 35.00 admin fee. Sometimes we waive that fee. I would like the system to be able to handle subtracting the 35.00 for the record. Then when the customer pay off the PN, I need a way to bring that total to 0.00 and show as PN paid off.
I would also like the system to be able to have the ability to show PN's Due and are Active. PN's that have been sent to collections. And be able to keep records of the PN that have been paid and the date they were paid. Also, a preferred function would be a way to separate by years. When 2026 ends, we can export all the data to a file of some sort that can be searched and read if needed later. And the current "batch" would be 2027, hopefully that makes sense. If the system keeps them all sequential but contains a way to sort by year, that would be acceptable.
There should also be a way to search anything that has been typed. I also want the ability to attach media (images and videos) to each PN record. I would also need to be able to create and print reports. Reports would be all PNs for a month. All PN due and active for a timeframe. All PNs that have been paid, or paid in a timeframe. A report for all Ticket numbers between Tickets 00000001 - 10000000. All PNs with the same name. All that type of data manipulation.
Also, I would need to be able to have users with a login/password, and the ability to assign different levels of access. Like Read-only, Editor, Admin. Those type of levels. Also, needs to be able to be stored on a shared drive. Webserver is not available. Needs to be able to open the system from a shared drive on the network.
I know I have written a lot. If anyone could recommend the type of system I should be looking at (i.e. CMS, DMS, or whatever else). And if you know of any good free, or open source free, software with the type of system I should be looking at, I would appreciate the pointing in the right direction.
Thank you for anyone that takes the time to read through this and help me out.

I'm in a data analyst job where my boss cancels all our projects partway through and I am miserable.