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Data-as-a-service, explained and defined

Data integration expert Jill Dyche defines data-as-a service (DaaS) and offers her view on outsourcing data.

What is data-as-a-service? What are the benefits of data-as-a-service?

The concept of data-as-a-service (DaaS) basically advocates the view that -- with the emergence of service-oriented architecture (SOA), which includes standardized processes for accessing data "where it lives" -- the actual platform on which the data resides doesn't matter. With data-as-a-service, any business process can access data wherever it resides. Data-as-a-service began with the notion that data quality could happen in a centralized place, cleansing and enriching data and offering it to different systems, applications or users, irrespective of where they were in the organization or on the network. This has now been replaced with master data management (MDM) and customer data integration (CDI) solutions, accompanying a master data "hub" on which the golden record of the customer (or product, or asset, etc.) resides, and is available as a service (e.g., "Get Customer") to any application that has the services to access it.

Many people hear data-as-a-service and think "outsourcing." While outsourced data is possible, we don't recommend it. We think companies should manage and own their own data assets--again, the platform matters less and can thus be outsourced if the business processes and data are solid. We see architecture groups enabling de-facto master data hubs and offering them as a service to ensure the sanctioned "single version of the truth" is available to everyone.

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This was first published in July 2007

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