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The Emergence of the Analytics Architect

As analysis of big data matures, analytics architects bring a key set of skills for achieving business objectives

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  • George Mouratidis

    Thanks for writing this article. I found it very interesting and it gives us an example of how the IT industry continues to evolve and mature. Here are my comments:

    1) I think closing the data-to-insight-to-action loop is key for organisations that wish to achieve an advanced level of maturity in information management as a way to place themselves in a stronger market position. I see this as supporting proactive evidence-based process improvement, whereby the actions taken are more clearly justified and traceable to the insight gained.

    2) Regarding mapping requirements to implementation, the prioritisation of the requirements as you describe, lends itself to an iterative/agile approach to implementation, which can help achieve faster return on investment, obtain buy-in from stakeholders, validate technology and architectural choices, and manage risk.

    3) The importance of data quality is probably worth a mention here. In this third phase of using data to help deliver business insights, it is even more significant to have valid and accurate data to rely upon, for improved discovery, visualisation and insight. Companies which have well understood and organised operational systems, where business information originates, will be able to obtain greater value from their analytics initiatives.

    4) Following from (3) I believe that the relational model (and good conceptual data modelling), will continue to play a key role here as foundation knowledge for achieving well-designed databases which can support diverse downstream uses of the information.

    Thank you :-)

    • Ahmed Fattah

      Hi George,

      Thank you very much for very valuable insights. Here are brief comments to your points.

      1) Agree and I like very much the “evidence-based process improvement” point.

      2) Agile is definitely a very integral to the analytics approach and feeds to the previous point.

      3) Fully agree. Many companies want to do advanced analytics realise that they don’t have the foundations of data quality.

      4) I need to understand this more. Hi George,

      Thank you very much for very valuable insights. Here are brief comments to your points.

      1) Agree and I like very much the “evidence-based process improvement” point.

      2) Agile is definitely a very integral to the analytics approach and feeds to the previous point.

      3) Fully agree. Many companies want to do advanced analytics realise that they don’t have the foundations of data quality.

      4) I need to understand this more especially in the context of ‘big data’. Although I agree that enterprise data with known value must be analysed, modelled and persisted in well-designed databases, in many ‘big data’ scenarios modelling is postponed and there are now emerging tools that interpret the data ‘automatically’.

      Thanks again for your feedback.