Take a minute to increase awareness and understanding of the terminology, context, and application of data and analytics.
Part four of a series.
It’s 2018 and the realization of data as an asset is at the forefront. As various initiatives around the management and exploitation of data are underway, the term “Data Hub” gets thrown around in a frivolous capacity in an effort to centralize all data.
But what does data hub actually mean?
If you Google “Data Hub,” you will get a number of different explanations and list of tools such as Cloudera’s Enterprise Data Hub, SAP’s Data Hub and Informatica’s Integration Hub. Vendor marketing and overuse of the “Data Hub” terminology increases the confusion.
Defining Data Hub
In order to chase away the confusion around this term, Gartner published “Implementing the Data Hub: Architecture and Technology Choices.” They are able to succinctly summarize a data hub in their opening paragraph:
“Hub architectures for sharing data can be implemented in many ways, with various types of integration technology. Data and analytics leaders and data architects need to understand the common and effective technology choices in order to successfully deliver on the organization’s data hub strategy.”
At its core, a data hub is all about collecting and connecting data to thoroughly understand data and produce meaningful insights that can be shared across the enterprise.
Because of the confusion around the generality of the term “Data Hub,” it is helpful to apply additional context to help clarify the intentions of your data hub initiative with goals such as persistence of data, agreed upon models, or data governance controls.
Depending on your goals, existing governance, and the integration solutions you have implemented, your definition of a data hub will vary from someone else’s.
Ultimately, a ‘hub’ is merely a descriptive word defining a central place of activity, so unless there’s a common understanding of what you are trying to accomplish with your data hub, there will be constant confusion.