Sr. Data Analyst @ Crunchbase | Founder @ Big Data Energy⚡️ | LinkedIn [in]structor | Empowering career growth in data | Breaking industry stereotypes

💌 partnerships@bdeanalytics.com
Hi 👋🏼 I’m Jess Ramos, the founder of Big Data Energy ⚡️ and a content creator with a community of over 450,000 followers across LinkedIn, YouTube, Instagram, and Substack. I'm an ex-corporate data analyst and data scientist turned entrepreneur. 

I'm also a Top Voice on LinkedIn and one of the leading voices in B:B marketing in tech partnering with big brands like IBM, Claude, Lyft, and the NFL!

After spending years in high-growth tech startups, I realized my true passion is working for myself as a developer advocate striving towards making tech, data, and AI more accessible to all. Through my business, I offer brand partnerships in the form of social media content, conference attendance, and live events. I also teach SQL and data courses for current and aspiring analysts.  

Highlights:

- Creator of Big SQL EnergyⓇ ⚡️ (the world’s greatest SQL course!)
- Partnered with brands like IBM, AWS, NFL, Atlassian, Lyft, Claude, Notion, and Snowflake
- Advocate for making data careers more accessible & human in an AI-driven world

Brands: partnerships@bdeanalytics.com
🎥 Youtube: @JessRamosData
📸 Instagram: @jessramosdata
💌 Newsletter: https://jessramosdata.substack.com/
🤳🏼 TikTok: @jessramosdata

Jess Ramos, MSBA

There are only 3 levels in SQL.

It took me years as a data analyst to reach the last one.

(you're gonna wanna save this 🏷️)

Here are all the skills you need to know in each level: 

Level 1: Newbie 
(the basic syntax) 
↳ select
↳ from
↳ where
↳ order by 
↳ group by 
↳ aggregate functions
↳ NULLs
↳ basic joins
↳ string manipulation 
↳ date manipulation
↳ arithmetic operators 

Level 2: False Confidence
(intermediate skills)
↳ CTEs
↳ subqueries
↳ set operations
↳ self joins
↳ window functions
↳ views & temp tables 
↳ case
↳ optimization
↳ pivoting & unpivoting 

Level 3: Reality sets in 
(advanced business problems)
↳ recursive CTEs
↳ indexing
↳ data modeling
↳ dealing with stakeholders

Level 4: Dunning-Kruger effect
(imposter syndrome all over again)
↳ realizing skills don’t matter and you still don’t know what you’re doing

♻️ repost this to your network and save this for later!

Jess Ramos

⚡️ Data Science & AI Content Creator w/ 500K+ followers | Developer Advocate & Solopreneur | LinkedIn Learning Instructor | Big Data Energy⚡️ | helping you leverage tech & AI

LinkedIn’s job match feature that helps you strategically focus your job search on all the right roles. Instead of mass applying for ALL the roles you can find, you can now apply for the ones that match your skills and experience the best.

This means that you’re optimizing your job search since you’re applying for roles that you’re MOST qualified for. In this challenging and competitive job market, you truly have to be strategic, data-driven, and work smarter— not harder!

LinkedIn is getting a major upgrade since they’re not JUST recommending roles to you anymore— they’re also telling you how good of a fit it is for you!!

I’m so excited to be partnering with LinkedIn on this since it’s been the biggest platform for my career growth over the past few years 💙

With LinkedIn dare to discover where you best fit with job match: linkedin.com/jobs
#ad #LinkedInPartner

Brand partnership • ⚡️ Data Science & AI Content Creator w/ 500K+ followers | Developer Advocate & Solopreneur | LinkedIn Learning Instructor | Big Data Energy⚡️ | helping you leverage tech & AI

I'll save you about $1M in consulting fees & 12 months of disappointment:

Your data strategy IS your AI strategy.

Most AI transformations are failing not because of the models and technology but because of what's upstream: the data.

Over the years it's been a never-ending cycle of promises:

↳ Machine learning was going to change everything. 
↳ AI was going to change everything. 
↳ Generative AI was going to change everything.
↳ Now Agentic AI is going to change everything.

The technology is never the problem.

Most organizations are sitting on databases full of duplicates, missing fields, undocumented schemas, and business logic that lives entirely inside one person's head who left the company in 2019. 

And that's exactly what you're feeding into these models. And now we're enabling agents to act autonomously at scale with confidence.

Agent confidence is NOT human confidence.

And the most dangerous part is that non-technical (and even some technical stakeholders) don't understand that. They see the little verified check mark, and take it as absolute truth.

We have to fix what's upstream before we can accelerate what's downstream.

♻️ repost to give your network a laugh today!

37% of companies plan to replace entry level roles w/ AI.

But IBM is doing the opposite. 

They're tripling their entry-level roles due to limits of AI adoption.

They're thinking about the longterm strategy instead of the quick financial savings.

Mid-level and senior-level talent doesn't just magically appear later on if you haven't had entry-level roles learning and growing within your company. 

Not only that, but they're rewriting their roles to account for AI adoption and use so people focus more time on the things that are harder to replace with AI.

Turns out implementing AI enterprise-wide is harder than we thought.

⚡️ Data Science, & AI Content Creator w/ 500K+ followers | Developer Advocate & Solopreneur | LinkedIn Learning Instructor | Big Data Energy⚡️ | helping you leverage tech & AI

Data Analyst | Tableau Consultant | Author of How to Become a Data Analyst

If you're reading this you probably either:
1. Want a job in data. 
2. Want a friend in data.
3. Need a data analyst. 

If you're #1, I was you, just one year ago! I've shared how I went from beginner to experienced data professional since the beginning.

Its my goal to create the kind of content a younger version of me would have wanted to consume!

#2, thanks for being here! Feel free to give me a wave. Lets be social!

#3's, hello 👋. If you haven't yet, check out my portfolio site, or my Annie's Analytics company page on here where I offer consulting services.

Heres my story. 

In February of 2022, I decided to learn data analytics for fun. I created a Tik Tok account, and started documenting my journey to learn this new hobby (@anniesanalytics). 

Very soon, I realized that every day I was waking up and just wanting to write SQL, build visualizations, learn Python.... Work with data! So, I decided that once I finished graduate school (in Healthcare) in July, I was going to become a data analyst. 

Along the way, I have shared here and on Tik Tok everything I can about what it's like to learn data analytics, and how you can do it for free or at least very cheaply. I've shared about the ups and downs of job searching. I've even shared about how I have built a portfolio, and set myself up as a real analyst. 

Now I also do YouTube videos, especially my series where I invite other data analysts to have a coffee chat with me, but we live stream it! We talk about our journeys into data and what our jobs look like now. https://youtube.com/playlist?list=PL3wIL0Blsv2vf8aAjTQXo017YntAXqrZc


Want to see my Portfolio as it was when I got my first job in analytics? I left it here in exactly the same state that it was when I got my job in July of 2022 to serve as an example to you, if you are a job seeker now! https://anniesanalytics.wixsite.com/annie-nelson/projects-6 

Want to see my current portfolio I am using now that I have gained some more skills? https://anniesanalytics.carrd.co/

Or the LinkedIn group here: https://www.linkedin.com/groups/12635532

Discord here! https://discord.com/invite/m9vZKtReFM

Annie Nelson

Why have a big profile if you can't use it for fun sometimes? Eveyrbody, Meet Harper! 

Harper is a goofy, loving, playful, and beautiful 1yr 7mo old girl and she is available for adoption with the San Diego Humane Society! (pet ID #977211) 

We are fostering her and spend a lot of our day going "look at Harper!!!!" because she's constantly doing something adorable. 

She's so easy to love. I hope she finds her forever home soon 🫶

If anyone's interested in learning more, you can find her profile by searching the adoptable pets list on the SDHS website. She's a gem!

I made a rookie error the other day. I asked AI to help me with some code that generally it is pretty well suited to handle.

But it got it wrong the first time. And rather than resetting the conversation, I tried to reason with it to change it's approach.

The code was really just dealing with sequential logic that at the time of writing I felt too lazy to do myself.

I spent over an hour going back and forth with it when I could hhlave probably just done it from scratch in 15 mins.

Lesson learned: once AI makes a decision, it sticks to it. If it's way off base with its first answer, stop. Reset. Start fresh.

Have we hit and are passing a golden 'easy' age for being a data analyst?

In the past, getting access to data was messier and required a higher technical skill set.

Today, a combination of advances in technology and a well saturated market (aka, having coworkers who handle the data /analytics engineering) means that there are many people with data analyst titles who get by exclusively building dashboards or even only using Excel.

But technology is still progressing. And it's taking away the edge that these people have enjoyed by making it easier for * everyone * to do those things. 

Although I think the "AI is going to take your job" argument is lazy and overblown, it likely is true that standing out from the competition is going to take more than the ability to build a sleek dashboard or write a complicated formula.

Not to mention, the way people access and use data is continuing to change. Why rely on a dashboard to load that takes 40 seconds and has a limited number of cuts when you could ask [AI tool] instead? 

Again, I think there is still a lot of value to the data analyst role and am not saying AI is replacing it, but I am saying I think that the role is changing and it seems that all of the "easiest" parts are the first to go.

Luckily for me, the parts of my job that I enjoy the most are the parts that are not going to be automated away any time soon 🤠

How many interviews do YOU think are necessary to fill a data analyst role? (or similar)

As everyone knows, tech companies put people through 5,6,7,8 rounds - some of which take hours!!

Someone mentioned to me the other day that while the current market is really tough, it's also hot. Some companies are moving candidates through their pipelines quickly.

In my opinion, this puts the companies with a long and arduous process at a competitive disadvantage.

But competition aside - how many do you actually NEED?

I've never hired someone, and can empathize with the stress (especially for less experienced hiring managers) that you'll make a bad choice. I've seen the impact that can have on teams, and I know it can be hard to get rid of someone.

But as a candidate.... There's nothing new you're getting out of me after a hiring manager interview, technical, and exec/stakeholder interview.

And the technical doesn't need to be some long rocket science experiment. A good interviewer (which I have experienced more than once) knows how to ask questions that help them understand if you actually understand the concepts, and how you approach problem solving.

I'd be really curious to see if you could put together a study correlating interview length & candidate success. At what point do you hit "diminishing returns" territory?

If we were ready for AI to take over all of our work then we also would have already nailed self - serve analytics.

In order to be ready for true self serve analytics we typically need a huge budget for a great, large team, or a business that moves slowly and has time to pay down all tech debt.

In order to pay down tech debt we need the people making the reports to change their behavior to stop creating so much in the first place.

Welcome to the real world.

We talk about self serve analytics and we dream about zero technical debt. But then we get back to work in the messy middle, doing our best and moving as fast as we can.

The view out of the train window on my commute to a coworking spot. My life is so hard! 😉

Petition to replace the sycophantic AI slop comments with the good, old fashioned "Interested".

The only people who use that anymore are creators who remember when their posts/feeds were flooded with a wall of "Interested" 😕

You don't know how good you have it until it's gone!

Everyone, meet Terk! He is available for adoption with the San Diego Humane Society and just looking for a soft place to spend his Golden years 💛

Terk is 16lbs, and enjoys your company and having a good sniff while out on a walk. We normally foster larger dogs, but our last sweetie was a handful so we asked for a mellow, easy dog to balance it out! 

As you can tell Terk is an old man, so he walks with a bit of a wide gait but if you look closely you can still see a little tail wiggle as he sets off on walks.

So far it seems like he is fairly indifferent to other dogs (not reactive!) and will sometimes solicit attention from passerbys out on walks.

He prefers to hang out at our side while we work from home, and enjoys a good head scratch every now and then.

If you know someone in SoCal looking for a mellow companion who they can spoil with love during their golden years, Terk might be your guy!

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The Battle

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