One Big Burger or a Buffet? The Data Strategy Mistake You're Probably Making

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Disclaimer: Any resemblance to real persons, living or dead, or actual events, or actual organizations is purely coincidental.

Over my many years of navigating the peculiarities of corporate life, I have encountered some truly baffling phenomena. But none quite as absurd (or as oddly appetizing) as the Great Data Burger Dilemma.

You see, within the labyrinthine corridors of an international company where I once resided (a company whose name I shan’t mention, for I value my skin), there arose a grand notion: “Let us build the Ultimate Multi-Layer Data Burger!”

What is this, you ask?

Imagine a towering culinary masterpiece: layers upon layers of governance, platforms, integrations, and automation. Each region would have its own slice of the pie (or, rather, its own multi-layer burger) but unified under the glorious vision of a centralized data team.

Sounds marvelous, doesn’t it?

Indeed, so thought the executives, the consultants, and the PowerPoint slides that accompanied this grand declaration.

And thus began the construction of the great burger, funded by millions of dollars and fortified by strategic endorsements.

The Birth of the Multi-Layer Burger

In its infancy, the plan seemed noble. Four platforms for four global regions. Each designed to serve the specific needs of its locale while still adhering to a centralized vision.

The architects (those wise but often-overlooked sages of the enterprise) hesitated.

“Will the burger not collapse under its own weight?” asked one.

“The multi-cloud complexity alone will choke us” muttered another.

"How about data integration tool, or other fundamental prerequisites?" asked a third one.

Their words swallowed in the gale of executive enthusiasm.

But alas, management dismissed these murmurs with a wave of the hand: “Too late! We’ve already presented it to the board, and the slides were brilliant.”

Thus, the multi-layer burger came to life. It was impressive to behold; gleaming with S3 buckets, airflow instances and, stacked with EMRs and parquet files, layered in bronze, silver and gold, dripping with integrations and leading to an "Azure" lake. Blobs, vaults, synapses, and more orchestration. It was almost like magic when a number came out right from one end to the other!

But like all grand feasts, it came with unforeseen consequences.

The Seven-Year Appetite

Seven years passed.

The burger, once a symbol of hope, now loomed over the organization like an over-engineered monument to inefficiency. Business teams were hungry for insights, but the burger was too large, too unwieldy. Cutting a slice (or, in practical terms, delivering projects) became a Herculean task.

The architects’ warnings echoed through the halls:

“The multi-cloud setup is a nightmare!”

“We cannot deliver insights fast enough!”

"We didn't streamline the tools before starting!"

At last, the "genius data CTO" with the enthusiasm of a chef unveiling instant noodles as fine dining, declared: "Let’s give everyone their own burger!"

The business teams rejoiced. The architects groaned. And the chaos quietly brewed.

The Era of the Small Burgers

Thus began the age of decentralization.

Every region, every business unit, was granted the freedom to build their own burger: a compact, two-layer affair customized to their specific needs. Agility was the new gospel. Speed was king.

And, here come the architects once again, raising their hands:

“Who will ensure consistency in the data models?”

“How do we prevent silos and duplication in ingestions?”

“What about governance, security, and alignment?”

To which management, now masters of delayed introspection, replied: “Good questions! But we’ll think about that later.”

And so, the company descended into what I can only describe as a data buffet free-for-all.

The Feast of Chaos

The initial thrill of small burgers was undeniable.

Business teams, freed from the shackles of governance, celebrated their newfound agility by building dashboards and data products faster than you can grab a frozen pizza at the supermarket. Like a starving shopper with no meal plan, they grabbed the easiest, shiniest tools and cobbled together solutions. Convenient, yes, but about as nutritious as a bag of chips.

But this freedom came at a cost:

Each team built its own burger, unaware (or unconcerned) that another team was using the same ingredients in a different way. Revenue meant one thing to Finance, another to Sales, and something entirely different to Marketing.

Every team ingested, cleaned, and modeled the same data in slightly different ways. Millions of dollars were spent reinventing the wheel (or, in this case, rebuilding the burger).

Business users, emboldened by self-service tools but lacking expertise, created SQL queries that would make a data engineer weep. Insights were riddled with errors, and trust in data plummeted.

Leadership meetings became a theatre of chaos. One team reported $100M in revenue; another insisted it was $97M. The CEO, bewildered, asked, “Which one is correct?” No one could answer (haven't heard about "source of truth"!)

Sensitive data was mishandled, compliance risks grew, and the governance team (if you could call it that) was reduced to a frazzled group of firefighters.

The Lessons Learned (Or Not)

And so, dear reader, we arrive at the crux of the matter: What is the right approach to data strategy?

Is it the towering multi-layer burger, served up as a single solution for everyone? Or is it the decentralized buffet, where each team grabs their own ingredients and cooks what they like?

As with all things in life, burgers and data included, the truth lies somewhere in the middle: striking a balance between over-engineered complexity and chaotic freedom.

Like preparing a balanced meal, a data strategy must satisfy hunger without sacrificing nourishment, agility without descending into chaos, and freedom without losing control.

Here’s two of the 8 things on how to get it right (DM me if you need the rest of the list):

A Centralized Core with Decentralized Flexibility like a central kitchen that prepares the base ingredients: a perfectly seasoned core data model, prepped and ready to be adapted by regional teams.

This approach ensures that: Everyone works with the same trusted ingredients (e.g., standardized metrics, single sources of truth). Teams can still customize their data “recipes” to meet local needs, but only within the boundaries of a well-stocked kitchen and clear rules.

Without this core, you risk each team snacking on their own silos, filling up on fragmented and conflicting data. A decentralized buffet might feed hunger in the short term, but it leads to data indigestion when the entire enterprise sits down at the same table to make decisions.

Governance as a Non-Negotiable because it is often seen as the stern parent at the table, insisting on vegetables when everyone wants fries.

But in reality, governance is the nutritionist that ensures your data strategy is as satisfying as it is healthy in the long term:

Role-based access controls: Ensuring the right people access the right data.

Data lineage tracking: Knowing exactly where your data comes from and how it’s transformed.

Standardized metrics: Preventing conflicting definitions that lead to organizational chaos.

Without governance, your enterprise risks binging on junk data; fast, unverified insights that may look good but ultimately weaken trust and decision-making.

Why the Right Balance Matters: Are We Eating, or Are We Starving?

Hungry teams will always gravitate toward the easiest, fastest options, just as a starving shopper grabs chips and candy instead of planning a proper meal.

A buffet of individual data solutions might look tempting, but without a cohesive strategy, it creates chaos, waste, and malnutrition at the enterprise level.

And you know what? Just like stuffing yourself with candies, the cost will catch up to you: bloated infrastructure bills, bad governance hangovers, multiple ingestion nightmares, and a rash of data breaches (a.k.a. "I downloaded the model onto my laptop"). It’s a feast of chaos with no satisfying ending.

Conversely, a rigid, multi-layer burger that’s too complex to deliver risks starving the business altogether.

Ask yourself: “Who’s cooking? Who’s eating? And who’s cleaning up the mess?”

The solution lies in striking a balance:

Build the core once.

Govern with discipline.

Empower teams to cook responsibly.

Because at the end of the day, your data strategy feeds your business and should be nourishing enough to guarantee your long-term growth and performance.

For more content on data strategy, and CXO topics check out: https://www.globaldataandbi.com/resources

Disclaimer: Any resemblance to real persons, living or dead, or actual events, or actual organizations is purely coincidental.

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