Data as an Enabler

For data to be a key enabler of business success, it needs to meet four requirements:

1. Findable — People should be able to quickly find the data they need to make decisions.

2. Accessible — Access should be provided to the right people, at the right levels, based on clear rules and governance.

3. Interoperable — Data should integrate across systems so it stays relevant and usable across business functions.

4. Reusable — Data assets should be reliable and repeatable so that the organisation can consistently extract value from them.

An enterprise model is a computational representation of an organisation’s structure and operations—its activities, processes, information, resources, people, behaviours, goals, and constraints. To make this model useful, it’s important to validate assumptions about how data actually exists and flows today. That work starts with prioritising a clear business glossary and taxonomy.

At a high level, an enterprise model spans three areas: people, processes, and technology.

To support enterprise integration, we need a shareable way to represent knowledge that reduces ambiguity and improves clarity and precision in communication. Ideally, this representation also reduces the amount of custom programming needed to answer “simple” common-sense questions about the enterprise.

An enterprise model can be both descriptive (what is) and definitional (what should be). Ultimately, its purpose is to enable model-driven enterprise design, analysis, and operations.

A strong enterprise data model typically has these characteristics:

• It provides shared, reusable terminology that everyone in the enterprise can understand and use.

• It defines the meaning (semantics) of each term as precisely and unambiguously as possible.

• It encodes those semantics as a set of axioms that allow business users to automatically derive answers to many “common sense” questions about the enterprise.