An interactive report that executives will ignore until they ask for the same data… in an Excel sheet.

Corporate for "I forgot what this is about but I need to make noise before someone notices".

Technologically frozen in 1995. Still thinks "the cloud" is for rain and refuses to click anything newer than Solitaire.

The secret sauce behind databases that actually perform.

Rules everyone agrees on but nobody follows.

Translating raw data into real-world meaning so it’s actually useful.

Transforming categorical data into numerical form—because computers just don’t get words.

Getting the most out of your budget before the CFO notices.

“Can you analyze all our data from the last 10 years for a report we’ll ignore?”

A bunch of decision trees working together to make better predictions—because one tree alone isn’t enough.

A gradient boosting algorithm that wins Kaggle competitions—because sometimes brute force just works.

A corporate delusion tactic to feign control, optimism, or progress in the face of complete chaos.

A fancy word for "number we use to see if our model sucks or not."

“Your data reports need to be better, but we won’t give you more resources.”

Load first, transform later—modern data integration in action.

Builds the data highways, then spends half the week fixing potholes caused by everyone else driving like maniacs.

Learned SELECT * yesterday and now wants database admin privileges – what could go wrong?

Wants to monitor every client blink without a clue what to do with it.

Spotting the oddballs in your data, because sometimes anomalies are fraud, and sometimes they’re just mistakes.

Shipping code faster than your team can fix bugs.

A vague, last-minute ask that will inevitably require multiple follow-ups and scope changes.

How much pain your system can handle before collapsing.

Saving progress so your system can crash at a later, more inconvenient time.

Making sure standard data values stay standard—good luck with that.

Makes dashboards for people who will ignore them and then ask you for the same numbers in a spreadsheet.

Trying to guess the future based on past data—like a digital crystal ball, but with spreadsheets.

Sifting through data, hoping for something insightful.

The behind-the-scenes details of how data was collected.

Because someone needs to process transactions in real-time.

A marketing term for "we kinda fixed the Data Lake problem."

Because well-managed data is the difference between insights and chaos.

Machine learning for people who don’t want to do machine learning. Push a button, get a model—hopefully, a good one.

When you want fast answers and minimal thinking.

The reason your reports make no sense.

Because mistakes were made.

Turning raw data into fancy charts that people ignore.

When your system crashes but pretends it never happened.

Hiding sensitive data so developers don’t see what they shouldn’t.

When you pivot data just to confirm what you already knew.

Making sure your app doesn’t make users want to throw their devices.

Making sure data doesn’t become a dumpster fire.

Renting someone else’s servers but paying more.

Because winging it with data governance isn’t a long-term strategy.

Trust no one, verify everything. Paranoia as a security strategy.

Poking around in your data to find trends, outliers, and problems before they ruin your model.

The magic behind neural networks—basically, trial and error on steroids until the model gets it right.

When everyone agrees on what to pretend to care about.

Microsoft’s latest “one tool to rule them all” attempt—until the next one.

The programming language everyone pretends to know.

Making sense of numbers so businesses can pretend to be data-driven.

SQL’s rebellious younger sibling.

The secret sauce that makes data searchable, understandable, and actually useful.

The reason your database admin hates you.

DIY data anarchist whose unholy Excel concoctions somehow hypnotize executives despite breaking every statistical law.

Splitting your database into smaller disasters.

The art of torturing data until it confesses something useful—or at least makes a nice chart.

Because “I have no idea where this data came from” is not a great answer.

Keeping unauthorized users out - until someone shares a password.

Workflow automation, so you don’t have to babysit data pipelines.

Worships clean metadata and version control. Lives for data lineage and will fight you over naming conventions.

Handpicking quality data like it’s fine wine.

Retiring an old dashboard but keeping the dataset running ‘just in case.’

Because just because you can collect data doesn’t mean you should.

Metrics that executives obsess over (but don’t always understand).

For when the cloud is just too far away.

Transforms your bullet point into 40 slides featuring at least two mountain-climbing metaphors.

“We’ll consider all possible factors… except the ones that make us look bad.”

Because not every department deserves full database access.

“I haven’t looked at the data yet, but I will… eventually.”

The thing everyone builds but nobody documents.

A free tool for tracking website traffic—until privacy laws step in.

The key metrics leadership suddenly decided to care about this quarter.

Schedules pre-meetings for the pre-meeting's pre-brief because they couldn't read an email to save their life.

“We need better numbers, but we don’t want to change anything.”

“We made a pretty chart—please pretend it changed your decision-making.”

A flowchart-like model that makes decisions—think "choose your own adventure" but with math.

“This dashboard is broken, but let’s not discuss it in front of leadership.”

When talking about talking becomes your main deliverable. Bonus points if you can turn it into a self-congratulatory Linkedin post.

Because bad data leads to bad decisions and lots of excuses.

When your model is too smart for its own good and memorizes the training data instead of learning useful patterns.

A/B testing’s overachieving cousin.

A strategic delay tactic used to avoid commitment in meetings with more than three directors present.

Spews directives like "make it intuitive" with all the specificity of a drunk fortune cookie.

Because reading rows one at a time is for chumps.

The bare minimum dressed up like a competitive edge.

The chaos of switching from Excel to an actual BI tool.

Someone else’s computer, but shinier.

The Costco of structured data.

The behind-the-scenes data that keeps everything (barely) organized.

The "we'll fix it in production" person. They're just one misplaced comma away from getting fired.

Deciding where to spend time, money, and energy—usually wrong.

Cutting back on data storage costs until everything runs painfully slow.

A chaotic attempt to explain why the numbers don’t match across reports.

When you can’t commit to a single cloud provider.

Keeping multiple copies of your data in sync.

The alarm system for when hackers come knocking.

Treats your dashboards like a digital coloring book.

Deploying apps without touching infrastructure (until something breaks).

Rules about data that everyone agrees on but nobody follows.

A measure of how spread out your data is—basically, how weird or normal your numbers are.

Doing more work with fewer complaints—on a good day.

Collecting data the unethical-but-effective way.

Helping engineers understand how data flows, transforms, and actually works.