Why your business needs canonical data and how to achieve it

By Mervyn Mooi

Most companies did not suddenly emerge with hundreds or thousands of employees, hundreds of thousands of customers and millions in turnover. They grew organically, by merging, being acquired or acquiring other companies.

Growth, though mostly desirable in the business world, creates its own problems and challenges within an organisation. And it is likely the cause of one of your biggest headaches – alignment. For example: one part of the business has no idea what another is up to and the executives struggle to get at the information they need to make educated decisions of how to run the growing, merged, or acquired business. Furthermore, it is a humungous manual process to capture, recapture and synchronise data between the full spectrum of systems – this includes data on printed sheets of paper or even apps on mobile devices.

Most programs pass data or information to and from a data store, such as a database, file or storage repository. Most programs, such as apps, processes and so on, operate against an underlying data store. Even Outlook is just a fancy front-end sitting on top of a data store, and business systems are no different. Many business applications and processes share a data store – some companies go a step further and create data warehouses and master hubs that collate, integrate and standardise the data from many sources.

(image not owned by KID)

(image not owned by KID)

The next problem then is that there are so many data storesthat need to share the data. They may share data from manufacturing, finance, the product department, human resources, the help desk – all over your business. It helps executives and management make smarter decisions about the future based on what’s happening in the business today. It also helps improve customer service, make the supply chain more efficient and a deliver a raft of other business benefits.

Incompatible data becomes a major snag to system integration. Canonical data helps resolve that issue. Essentially it’s breaking the data down into its simplest possible form that still meets your business requirements. And even better: there are standard canonical data models for different industries so much of the work is already done. But not all of it.

In the next addition we will look into the standard models and how to customize them to your business needs.


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