Learn how to masterfully disrupt your company's data platform stack with our satirical step-by-step guide, filled with sarcasm and humor.

In the world of corporate politics, there’s a fine line between success and chaos. If you’ve ever wondered how to turn your company’s data platform stack into a labyrinth of confusion and inefficiency, you’ve come to the right place. Here’s a step-by-step guide, filled with a healthy dose of sarcasm and a pinch of merciless humor.

Embrace Low Code Tools for Data Platforms

Why bother with custom code when you can use low code tools? Sure, they might not be as flexible or powerful, but think of all the fun you’ll have when you hit a wall and can’t customize them to your needs!

It’s even more fun when you have to engage your customer-friendly vendor advocate, sales representative, offshore support guy and finally an engineer just to learn that you have to pay more or migrate to an Enterprise Pro+ plan for that feature to work, and it’s in the private preview that will be available for sure(maybe?) in the next quarter(a quarter is usually 6 months for them).

Multiple Warehousing Solutions

One data warehouse is for amateurs. Real pros use at least three. The more, the merrier!

Who cares about seamless integration and efficiency when you can have the joy of juggling multiple systems? It’s boring.

People have the right to sift through a deluge of options, compare and contrast before they land on a decision. Bonus, everyone else now gets to use different warehouses to pull their reports.

Sure it will be slow, but remember what Yoda said? “Patience you must have, my young Padawan.”

Knowledge Platforms Galore

Decentralizing your knowledge base is critical for maximum chaos. You need a few different knowledge platforms. The slower the better. A Word document with 25 different templates will make a good deal too.

The goal here is to ensure that no one can find anything. It’s like a treasure hunt, but with corporate data!

Overstaffing

Managing the data platform isn’t a one man’s job, but Two VPs, three Directors, three Principle Architects, five Associate Directors, and countless Product Managers and Engineers. The more the merrier! With this many people, there’s bound to be conflict, and what’s more entertaining than a good old-fashioned power struggle? Wait a minute, let’s reduce the number of engineers. What are they doing here? No one touches the code!

Just because you are overstaffed, doesn’t mean that you can commit to work. Use Absence to Increase Respect, honor, and credibility.

Centralized Team for Data Mesh

Choose Data mesh but create a centralized team to boss everyone around. Because nothing says “teamwork” like a good dose of micromanagement. People may ask, “But data mesh is all about decentralization”. You got to say everything but the truth, Say little and be ambiguous, leaving the meaning to others to interpret. The less you say, the more intimidating and powerful you are.

Governance? What’s That?

Governance is dangerous. It may one day unite and empower people against you. Don’t govern, just inform (or don’t). But you have to show off, create a dedicated team for Data Governance, work with Enterprise Architecture, write a few 100 documents and best practices.

After all, rules are made to be broken, right?

Perfectionism at Its Finest

Keep evaluating and building multiple products and platforms, but don’t allow anyone to use it until it’s perfect. You know it’s never gonna be perfect.

Don’t ask for feedback though. Who needs feedback or opinions when you can aim for an unattainable ideal?

DIY Platform

Give them the platform and let them figure things out on their own. It’s like throwing someone into the deep end of the pool to teach them how to swim, but with data. Even better, if you can customize the platform and make it complex enough. After all, engineers are hired to solve complex problems.

The Power of Redundancy

In the world of data platforms, redundancy is not just a safety net - it’s a key to success. It’s about creating different data platform teams for each domain or segment, ensuring that there are enough redundancies.

Imagine this scenario: You’re a juggler, and each ball represents a different domain. If you only have one ball (or team) for each domain, what happens if you drop one? The performance stops. But if you have redundancies, you can keep the show going.

This is why we make sure that these teams do the exact same job. It might seem counterintuitive - after all, why do something once when you can do it multiple times? But in the high-stakes world of data, having backup teams ready to step in can mean the difference between a minor hiccup and a major catastrophe.

So, remember the juggler next time you’re planning your data platform teams. Redundancy isn’t just about doing the same thing over and over - it’s about keeping the performance going, no matter what.

The Enigma of Costing

In the realm of application development, the costing process can often feel like navigating through a labyrinth. It’s not always clear how much an application costs, and sometimes, it’s like opening a mystery box when the bill arrives!

Complexity can be your ally. A sophisticated billing system might seem daunting at first, but it can also deter unnecessary scrutiny. It’s like a magician’s trick - the more complex the illusion, the more mesmerizing it is. But remember, the goal isn’t to deceive, but to create a system that accurately reflects the value and resources used by each application.

The Illusion of Savings

Create a slideshow of how you saved millions of dollars and 95% of the effort but never show the details. It’s all about perception, not reality. Dazzle your audience with a flurry of buzzwords and jargon. It’s like a smoke screen - if they can’t see through it, they can’t question it. After all, who needs reality when you’ve got a good illusion?

Conclusion And there you have it, a foolproof guide to ruining your company’s data platform stack. Remember, this is all in good fun. In reality, we should strive for efficiency, clarity, and cooperation in our data platforms. But a little humor can help us see where we might be going wrong and guide us toward better practices.