The Rise of DaaS: Why You Should Treat Reference Data as a Service

Every developer knows the feeling. You're deep into a new feature, and you need a list of countries for a dropdown menu. The "quick and dirty" solution is tempting: find a list online, paste it into a file, and hardcode it into your application. Problem solved... for now.

Fast forward six months. A new microservice needs the same list. Another team copies your file. A third service needs currency codes, so they create a separate list. Suddenly, your organization has a dozen different, slightly-out-of-sync lists of "static" data scattered across its codebase.

This is the hidden chaos of reference data management. But there's a better way. It's time to stop treating reference data as a static asset and start treating it as a dynamic, centralized service.

What is Reference Data, Anyway?

Before we dive into the solution, let's establish a clear definition.

Reference data is the foundational, stable data used to classify and add context to other data within your systems. It's the "master data" that rarely changes but is essential for business operations.

Common examples include:

ISO Codes: Country codes (ISO 3166), currency codes (ISO 4217), and language codes (ISO 639).
Geographic Data: Lists of states, provinces, continents, or airport codes.
Industry Standards: Units of measurement, industry classification codes, or financial market identifiers.
Internal Data: Your company's own list of office locations, product categories, or user roles.

This data seems simple, but managing it inefficiently creates significant technical debt and business risk.

The High Cost of "DIY" Data Management

Hardcoding a list of countries or keeping a CSV in a repository is a solution that doesn't scale. The "do-it-yourself" approach to reference data quickly snowballs into a maintenance nightmare with hidden costs.

Data Inconsistency: When each application has its own copy of the data, inconsistencies are inevitable. Your analytics database might use "USA," while your shipping service uses "United States." These discrepancies lead to broken reporting, failed integrations, and hours of debugging.
Maintenance Paralysis: What happens when a country changes its name or a new currency is adopted? You now face the daunting task of hunting down every instance of that data across all your applications, coordinating updates, and deploying multiple services for one simple data change.
Duplicated Effort: Every new project requires developers to re-solve the same problem: find, vet, and implement reference datasets. This is a waste of valuable engineering time that could be spent building core product features.
Lack of a "Single Source of Truth": Without a central authority for reference data, no one knows which list is the correct, most up-to-date version. This erodes trust in your data and the systems that rely on it.

The Solution: Reference Data as a Service (DaaS)

The solution is to abstract away the complexity. Just as we use Stripe for payments or Twilio for communications, we should use a dedicated service for data. This is the core principle of Data as a Service (DaaS).

By treating reference data as a service, you centralize it behind a simple, reliable API. Instead of embedding static lists in your code, you make a quick API call to a single source of truth.

This is exactly what we built at reference.do.

With a DaaS approach, fetching a list of all official ISO 4217 currencies becomes a single, simple API call.

import { Do } from '@do-inc/sdk';

const an = new Do(process.env.DO_API_KEY);

// Get a list of all ISO 4217 currencies
const currencies = await an.reference.get('iso-4217');

console.log(currencies);
/*
=> [
     { "code": "USD", "name": "United States Dollar", "symbol": "$" },
     { "code": "EUR", "name": "Euro", "symbol": "€" },
     { "code": "JPY", "name": "Japanese Yen", "symbol": "¥" },
     ...
   ]
*/

The benefits are immediate and transformative:

A True Single Source of Truth: Every application, from your front-end to your backend microservices, pulls from the same place. Data is consistent by default.
Effortless Updates: Need to update a dataset? Do it once in the central service, and every application instantly receives the new information on its next call. No code changes, no redeployments.
Increased Developer Velocity: Free your developers from the tedious work of data management. They can now integrate standard or custom reference data in minutes, not days.
Manage Custom Data Seamlessly: The best DaaS platforms don't just stop at public datasets. With reference.do, you can upload, manage, version, and query your own proprietary reference datasets right alongside standard ones, all through the same simple API.

Stop Managing Data, Start Using It

The ad-hoc management of reference data is a relic of a bygone era. In today's world of microservices, distributed teams, and rapid development cycles, a centralized, API-driven approach isn't just a "nice-to-have"—it's a necessity for scalable and robust architecture.

By embracing Data as a Service, you eliminate a whole class of potential bugs, streamline your data management processes, and empower your developers to build faster.