Please note that our philosophy on the subject enables the TOGAFF 9 Capability Based Planning approach. This enables the CIO / CDO with proper governance from an enterprise architecture and IT perspective since capability-based planning is a powerful mechanism to ensure that the strategic business plan drives the enterprise from a top-down approach. It is also adaptable with capability engineering to leverage emerging bottom-up innovations. This aligns with the Sirius approach of planning, engineering and delivery of solutions to enable strategic business capabilities to the enterprise.
Data vs Information
We are often tasked with this question – what is the difference between data and information architecture? This seemingly simple question (from a technical perspective) might be met with complicated, conflicting answers. Let’s simplify this into something that aligns well with both common sense and industry norm.
Most professionals who started their careers in the data field will agree that two decades ago this was a much simpler question. Not only has the lines between terms such as data and information been blurred due to differing business cases and applications, but the value association of ‘data’ and ‘information’ may differ between businesses. This makes the question relevant within the current ‘big-data’ paradigm.
Let’s first, therefore, clarify our Sirius definition of the difference between data and information. This definition aligns well to all the major, generally accepted frameworks on the subject.:
“Information is data put into action. Where a specific data element may exist in any form of format or another, it has lesser business value until it is integrated with other data elements into a package of data elements. This package can be described as an information package. Hence, information is data with context. Knowledge and insights are further derivations of information, yet, in the IT context, it is still based on data“.
The two forms of ’01011000…’-Architectures
If ‘data’ refers to singular items of values without context, then Data Architecture is necessary to contain and organize the various data resources into a manageable data environment.
Likewise, if ‘information’ refers to contextualized data, then Information Architecture is necessary to combine those resources into a structure that allows the dissemination of that information to be created, shared, analyzed, utilized, and governed throughout an enterprise, across all lines of business, within all departments, with confidence and reliability.
Practical application (Data Architecture VS Information Architecture)
The Data Architect focuses on the technical depth implied by and associated with the design, physical structuring, storage, movement, planning, backup, retention, dissemination and classification of all data elements within the enterprise and may or may not be required to engage across business functions. Such functions would typically result into technical specifications during business application design.
The Information Architect focuses on the technical, business and governance matters implied by and associated with the design, overlap, contextualization, usage, security, sharing, discontinuation, valuation and publication of all information sets across the enterprise and across business functions. The resulting architecture should form part of the greater data governance strategic pack as well as the enterprise architecture and enable the data architects with clearly contextualized application required from resulting information sets.
These two roles have clearly segregated areas of control as well as points of engagement for overlap. If segregated, it is not recommended for one role to report to the other, but it is highly recommended that both report to the ‘Chief Data Officer’ , ‘Information Management Executive’ or ‘Enterprise Architect’.
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