Balancing Enterprise Data Management Models

Balancing Enterprise Data Management Models

4 Minute Read

The right data model could be the difference between scalable insights and a tangled mess of individual mappings.

Successfully framing enterprise data management (EDM) requires balancing the structure to capture current business processes with the flexibility to accommodate the ever-changing requirements – so establishing the right data model is key.

Some may argue EDM hardly needs a data model. They’ll argue it’s simply a matter of mapping data items from input sources to downstream systems, then adding in validation across sources for each item.

So, what's the point of considering the data and what it means to the business? Why not just keep adding more data sources, more mappings and more end points?

A Matter of Scale

Simply stated, EDM without a data model doesn't scale well. The complexity of mapping increases exponentially with the number of input sources multiplied by the number of downstream systems. Without a centralized body of information to describe the fundamental relationships and dependencies between the different data sets and business objects, organizations will encounter tremendous difficulty building out any business logic.

Capturing the relationships and dependencies between different data – especially financial data –requires a structured model. Building these relationships and dependencies into a centralized data model provides structure for business aware EDM processes. And developing a common framework of data – including what it means and its relationships with other data and business objects – avoids the tangled mess of individual mappings.

Benefits of Scale

Classical relational data models, where it’s necessary to define relationships before they’re needed, are notoriously inflexible. Unless the design is perfect from the start, it is often prohibitively challenging to add or modify new attributes without extensive design changes.

Having a data model to build on offers benefits of scale and efficiency. But it’s important to look towards the more ‘modern technologies’, which build and manage structure and are designed for change from the outset. These approaches cope easily with new data sources and new data requirements while removing the need for costly database re-engineering or continual and expensive consultations with a vendor partner.

Tomorrow’s technology is shaping business today. To learn more about how MNP can help you find the right data model for your business, contact John Desborough, Director Consulting and Technology Solutions at [email protected]


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