While a lot has been written about what it is to be data-driven, up until now there has been relatively little written about enterprise data-driven applications, and how it relates to other types of applications, and data management infrastructure.
I thought it might be fun to extend the pizza analogy that was previously blogged about by Albert Barron, IBM Software Client Architect, in which he cleverly showed the differences between on-premises systems and “as a service” concepts through the various components that make up a pizza meal.
If you will forgive me I’m taking his “pizza as a service” concept to an even cheesier level. Starting with a baseline of software as a service, modern data management Platform as a service (PaaS), data-driven applications and adding the following capabilities:
- Data as a Service – to provide the raw multi-domain, structured and unstructured data from third party, social and transaction sources (such as through our Delivered by Reltio partner program)
- Master Data Management – to create reliable data by cleansing, verifying, matching and merging, ultimately uncovering affiliations and relationships between siloed sets
- Analytics – to deliver in context, relevant insights with visualize cues specific to the role of the frontline business user
- Machine Learning – to give recommended actions, that can be immediately actioned within the data-driven application, by the user or autonomously executed on their behalf. With closed loop feedback to continuously improve outcomes
So there you have it, the secret “sauce” of data-driven applications delivered as a pizza for your enjoyment. Sorry I didn’t squeeze the beer into the post, but I think beer can be taken as foundational, like big data infrastructure and cloud for today’s modern data management Platform as a Service.
If you’d like a more technical view of what a data-driven application entails, please check out Phil Russom, PhD’s first of its kind checklist for data-driven applications.
Better data, better pizza, #berightfaster