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11/03/2026

comment “ai” to get the link to my full interview with Michael Andrew on YouTube as we talked about how AI is changing data!!

I interviewed the Chief Data Officer of Salesforce 🎉

I learned a lot, and we also had a lot of fun too.

And here’s what I learned from Michael Andrew:

↳ Sometimes you learn the HARD way your data is NOT ready for AI

↳ AI is making data analytics EVEN BETTER and more fun

↳ Agents need high-quality, clean & fresh data to make good decisions

↳ When it comes to security, encryption and managing scope & access are vital to protect the data

↳ The biggest skill he’s hiring for right now is curiosity and the ability to learn and change

↳ AI Agents are like babies— you have to hold their hand and manage them closely!

TLDR: Be thoughtful & in control!

11/02/2026

comment “Data” to get the link to my full YouTube video and find out which data job ACTUALLY pays the most in 2026!!

In 11 months, I negotiated $71K to $153K as a data analyst in tech

My secret is shutting your mouth and not saying any numbers.

I never would’ve thought I was worth $140K-153K, so I probably wouldn’t have asked for that much… but multiple companies willingly offered it to me!

I realized that saying a number first was me doing their job for them. I was basically telling them exactly how little they could pay me without negotiating. And this way, I was definitely going to lowball myself.

Because their budget is almost always more than you think it is.

So I stopped saying numbers.

Every time a recruiter asked “what are your salary expectations?”

I’d say: “I’d love to meet with more members of the team and better understand the role so I can assess the market value. But if you have a budget, I wouldn’t mind hearing it.”

Then SIT IN THE SILENCE. Don’t fill the awkwardness. Just wait for them to talk.

Silence is your power, own it.

Companies will almost tell you their budget and if they don’t thats a red flag.

Once they named their number, I either said yes, I’m aligned with that range or I moved on.

Good negotiation skills literally make you money over time not just in your salary but in your %-based bonuses and raises, 401K contributions, and compounding interest 💅🏻

11/02/2026

I interviewed the CVP of Azure Databases at , Shireesh Thota!

And yes, this is the 3rd time I’ve interviewed him, so we’re basically besties now 🤣

Shireesh has been at Microsoft for 19 years, and started as a SQL Server Intern. What a career to get to where he is now!

We did some fun rapid fire data questions, and I also checked to see how his daughter’s vibe coding is going:

Favorite SQL Function?
↳ Window Functions

Writing Queries in All Caps or All Lowercase?
↳ Keywords in all caps and the regular identifiers in lowercase

Spreadsheets or Databases?
↳ Databases of course!

Real-time or Batch Processing?
↳ Real-time is EXTREMELY important in terms of how the world is moving but both work in conjunction and are really important.

How’s his daughter’s vibe coding?
↳ Every time she learns a new math concept, she tries and builds an app for it with levels of difficulty and shows it off to her friends.

Shireesh also says the best way to learn AI is to learn by doing!

I had a great time in Barcelona at FabCon SQLCon EU and can’t wait for next year 💃

Full sit down interview with Shireesh coming soon!

10/30/2026

84% of people have NEVER used AI, so AI is going to create one of the largest wealth gaps in human history.

I see if happening right now even in my own business.

I’m doing things that I normally wouldn’t even know how to do and accessing information I wouldn’t normally have.

It’s helped me produce work at a quicker and deeper level allowing me to scale my knowledge, team, and business much more rapidly than I would be able to without AI.

Here are the 3 levels… what level are you on??

↳ Level 1: LLMs
You write prompts and receive answers. Claude, Gemini, and ChatGPT are fluent in language tasks such as summarizing, translating, and coding, but they only predict based on your input and their training data. They don’t have awareness once you close down the chat window.

↳ Level 2: Agents
They take actions on your behalf using an LLM combined with tools like browsers, Notion, Google Sheets, Slack, and more. You can build agents in tools like Cursor, Zapier AI Agents, n8n, GitHub Copilot, and Claude Code. You’re no longer involved approving every single decision.

↳ Level 3 Agentic AI:
Agentic AI systems complete end-to-end tasks completely autonomously, evaluating & iterating completely on its own. Tools like ManusAI, Gemini Deep Research, Claude Research. These run in a continuous loop with one prompt, multiple iterations, and no hand-holding required.

What level are you on??

10/30/2026

Georgia Tech invited me to meet with Atlanta’s first ever Senior Technology Advisor, Donnie Beamer Jr. to talk about how our city is becoming a tech and AI hub.

His take: Silicon Valley will build the frontier models but Atlanta has its own lane to be the APPLIED AI capital of the world because there are so many large enterprises headquartered there.

As someone born & raised in ATL, what stood out to me was:

↳ Atlanta has the 4th most Fortune 500s of ANY city in America, so it has a booming economy of BIG enterprises implementing AI across their workforce.

↳ The city of Atlanta practices what they preach and they installed AI to detect anomalies in its water systems and patched 61 leaks BEFORE they became breaks, saving millions of gallons of water.

↳ Georgia Tech is a leader in supporting AI initiatives for not only the city of Atlanta but for their students.

And Donnie’s advice on the one skill everyone should be learning is:

How to LEARN to use AI

Because there’s an AI tool built for almost everything now, and the person who knows how to use it is the one who’s going to take your spot (or your customers)

It’s great to see Atlanta partnering with Georgia Tech to keep AI at the forefront of business and government.

That’s real BDE™⚡️
Avant South

10/26/2026

most data projects use the same boring datasets. here’s one that actually keeps you interested 👀

save this + comment “F1” to see how F1 uses data & AI to win races

I pulled the 2025 Las Vegas Grand Prix first — my FIRST EVER F1 race — and watching that data come back on my laptop after being in the pit lane makes it feel like it’s happening in real time 😭

Here’s how to connect to it:
↳pip install fastf1 and import it into your script
↳ enable caching first to save your data locally. this avoids re-downloading it every time you run
↳ pull any session by passing 3 things: year, circuit name, session type and you’re in

Here’s what you get back:
↳ session.results gives you finishing positions, points, and DNF status
↳ session.laps gives you every lap for every driver with lap times, sector times, tyre compound, tyre life, and pit data
↳ session.weather_data gives you track temp, air temp, humidity, wind speed, and rainfall mapped to each lap
↳ telemetry off any individual lap gets you speed, RPM, throttle, brake, gear, and exact X and Y coordinates of the car on track

Everything comes back as a Pandas DataFrame so you can filter, group, and plot it like any dataset you’ve already worked with

Real data that’s ACTUALLY interesting to analyze 🏎️

10/23/2026

If you think your manager is trying to fire you… they probably are!

I wish I could say it’s all in your head but I’d be lying 😅

Take it from me, I got suddenly FIRED from my $153K Senior Data Analyst role after being pushed out for 6 months.

And yes, I was doing all of my work, crossing my Ts and dotting my Is… But they still found a way to paint me as a poor performer and fire me because they didn’t like me.

Managers set people up to fail all the time, so trust your gut if you think it’s happening to you.

This is how it happens:

↳ Mistakes seem innocent but they’re calculated.
You’ll start to get excluded from meetings. They’ll “forget” to loop you into communications and you’ll slowly get removed from important projects visible with leadership. You might think it’s an accident at first but they’re all part of the bigger plan.

↳ They’ll turn everyone else against you.
A manager who’s working against you will make sure leadership, stakeholders, and even your own coworkers don’t like you too and keep you from getting any visibility with leadership. With no visibility, you don’t get raises or promotions, and nobody speaks up for you when things get bad.

↳ When subtle doesn’t work, they escalate.
If you keep doing good work and pushing back professionally, they get more aggressive, direct, and explicit. Expect heavy micromanaging, with every small mistake written down and blown out of proportion. At that point they’re collecting documentation for HR.

Their ultimate goal is to make you miserable so you quit. If you quit, they usually pay no severance and carry less legal liability vs. firing you. Firing someone is very hard because you have to have a documented case of providing feedback and giving them a chance to improve.

Which is what they spent 6 months building against me because I kept doing my job and making it very difficult for them.

If this sounds familiar…

Start job searching right away and keep your own records of EVERYTHING.

Just know the game is not designed for you to win 😉

10/23/2026

Data angel reporting for duty 🪽🪽🪽📈📊📉

10/23/2026

Data angel reporting for duty🪽🪽🪽 📊 💻

10/22/2026

Comment “Data” to get the link to my full 3 data analyst projects tutorial YouTube video! Save for later and follow for more!

THESE are the 3 data projects I’d put in my portfolio if I started over in 2027 (and wanted to specialize in AI!)

The average data portfolios are still using the same sales dashboard and churn model…. which are still relevant.

But if you want to stand out, you need to lean into AI.

With companies putting a ton of money into AI, they need analysts who can measure it, manage it, and understand how people are actually using it.

So these are the hottest data projects in 2027:

↳ Token Analytics
Where I’d track AI usage and cost by team and then connect it to money made or time saved, so every team ends up with one clear ROI output (like cost per ticket resolved).

↳ Data Analyst AI Agent
I’d give the AI the business rules and the meaning of every table, along with info about the data itself. After that I’d test it on questions I already know the answers to and show the accuracy before and after fixing its context.

↳ AI Product Analysis
This is where you can analyze technical AI products and track things like how users edit the AI outputs and how often they regenerate or reject it, plus what each successful output costs the company.

If you do all three, you’re showing that you can analyze how a company spends on AI and how people actually use it. Which is exactly what companies need in 2027!

Which project are you building first?

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Atlanta, GA

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https://linktr.ee/jessramosdata

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