Why Data Orchestration Matters
At its core, data orchestration is about managing and coordinating data flow across multiple systems so a business can operate efficiently and deliver what customers expect. Think about a retailer. To sell products online, it needs accurate inventory data, updated product catalogs, pricing info, customer profiles, and order management—all coming from different systems. Without orchestrated data, these systems live in silos, creating delays, errors, and poor experiences.
But achieving this isn’t simple. Most companies rely on a patchwork of integrations: flat file imports, API connections, custom-built middleware, or direct database work. Each integration requires time, specialized skills, and ongoing maintenance. Every system update or new platform can break these connections, forcing constant firefighting.
Despite the cost and effort, these integrations are essential. Without them, businesses can’t offer the product availability, personalization, or speedy service customers expect in today’s digital world.
The Hidden Complexity of Data Integration
Integration sounds straightforward—connect system A to system B, move data, and done. But real-world data orchestration quickly becomes complex. Different systems speak different data languages, have varying update frequencies, and enforce different business rules. Handling these inconsistencies is where most organizations get stuck.
Moreover, integration efforts often end up tightly coupling data to the specific software or platform it supports. This makes switching tools or adopting new technology painful. Instead of a flexible setup that adapts quickly to changing business needs, companies find themselves locked into rigid systems.
AI Adds a New Layer of Demand
The rise of AI and large language models (LLMs) has added another wrinkle. AI tools don’t just need data; they need structured, relational data they can understand and reason over. This means businesses must provide data that’s not only accurate but organized in ways AI can use effectively.
If data remains scattered or inconsistently formatted, AI’s value diminishes. For example, an LLM can only generate helpful insights or automation when it has clear access to connected datasets—product info tied to inventory, customer profiles linked to purchase history, etc. Data orchestration isn’t just about integration anymore; it’s about making data AI-ready.
Why Most Organizations Shy Away from True Data Composability
Given the stakes, you’d expect organizations to chase true composability—building modular, loosely coupled data systems that plug and play with different platforms. But the reality is different.
The main barrier is legacy architecture and tightly bound integrations that prevent agile change. New platforms come with their own data models, APIs, and quirks, making migration or expansion costly and risky. The fear of disruption pushes businesses to stick with what they know, even if it’s inefficient.
The result is a technology stack that grows in complexity but not in flexibility. Martech and business systems become rigid, slowing innovation and limiting the ability to respond to new customer demands or market shifts.
Enter: Umbraco Compose
If all this sounds like a massive headache, you’re right. But there’s good news. Last week, while attending the Umbraco Codegarden conference in Denmark, I learned about a new product that gets to the root of the data orchestration problem:
Umbraco Compose. This isn’t just another integration tool—it’s a platform-agnostic, open graph infrastructure designed to revolutionize how organizations handle their data.
Here’s why this matters.
Umbraco Compose lets you combine data from any source and deliver it headlessly through their CDN-based API infrastructure. That means no more wrestling with custom API endpoints for every new data set or digital channel. No more painstaking database architecture just to maintain relationships between different business data. Simply put: the traditional barriers of data ingestion and delivery are gone.
Imagine this: you can put any data, from any system, into an Open Graph environment without writing a single API. Then, you can query and combine that data however you want—across all your connected sources—without building integrations yourself.
The Implications Are Huge
For one, this slashes costs. Companies often spend tens of thousands on building and maintaining APIs and integrations alone. Umbraco Compose eliminates much of that overhead.
It also accelerates time to market. Projects that used to take months or even years to connect and configure can now be launched in weeks—or days.
System migrations? They become far less painful because your data isn’t locked into rigid, platform-specific architectures. Instead, you have a flexible graph that adapts quickly to new platforms or tools.
Ultimately, Umbraco Compose doesn’t just solve data orchestration—it redefines it. It enables organizations to move faster, innovate smarter, and deliver the seamless digital experiences their customer’s demand.
The Future of Data Orchestration Is Here
The complexities of data orchestration have long held businesses back, but with innovations like Umbraco Compose, the game changes. By breaking down integration barriers and freeing data from legacy constraints, companies gain the agility and speed they need to compete in an AI-driven digital world.
If your business struggles with slow, expensive, and brittle data flows, it’s time to rethink your approach. Data orchestration isn’t just a back-office technical challenge anymore—it’s the foundation for modern digital success.