I am increasingly seeing articles that talk about the confusion in identifying and building out the right information architecture for the organization. The article here, and with a clip below talk to that point. This is a good thing. People seek simplicity, and are looking for the prescriptive approach: 1) build a data warehouse; 2) build some datamarts for the business folks; 3) get a BI tool and build reports. But this does not cut it as it is too rigid a structure for analysts, or other stakeholders that have to do more than pull reports. The industry has responded by – I am speaking in buzzwords here – by adding “sandboxes”; by adding ODS (Operational Data Stores); and by adding a whole new way of landing, staging, persisting data and using it in analytical tasks (Hadoop). Sitting on top of this data level of the information architecture has been an explosion of tools that cater to (more buzzwords) data visualization, self serve BI, and data mashups to name a few.
Bottom line – how does this all get put together without creating an even bigger data mess than when you started? It is hard. What one sees so often is organizations putting off addressing the issue until they have a real problem. At this point, one sees a lot of sub-optimal management behavior. A consistent theme in the press is agility – organizations and their leaders need to embrace the agile manifesto. I am whole heartedly behind this. HOWEVER, agility needs to be framed within a plan, a vision, or at least some articulated statement of an end point.
The article below is interesting as it presents agility as a key “must have” management approach, and yet it also discusses the fact that in order for an agile approach to be successful, it needs to adopt disciplines that are decidedly un-agile! This creates a dual personality for leaders within the data management related functions of an organization (BI, analytics, ERP, …). On the one hand one wants to unleash the power of the tools and the creative intellect that is resident within the organization; on the other, there exists a desire to control, to reduce the noise around data, to simplify ones life. The answer is to embrace both – build a framework that provides long term guidance, and iteratively delivers capabilities within that framework towards a goal that is defined in terms of business capabilities – NOT technology or tightly defined tactical goals.
The framework – whichever approach one chooses will articulate the information architecture of the organization – how data flows around the organization to feed core business activities, and advance management’s goals! It is important – if it cannot be explained on a one page graphic, it is probably too complicated!
Martin’s approach to tying things together is below…
“”So given that there is not a one size fits all approach anymore how does a company ensure its Information Architecture is developed and deployed correctly? Well, you have to build it from the ground up, and you have to keep updating it as the business requirements and implemented systems change. However, to do this effectively, the organisation must be cognisant of separating related workloads and host data on relevant and appropriate platforms, which are then tied together by certain elements, including:
See also:
- Polyglot persistence
- Data Management Maturity Model as an example of a way to start thinking about governance
- Agile development – a good idea so often badly implemented!
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Tags: Adaptive, agile architecture, best practices, governance
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