Conclusion: The days of viewing BI as a single solution are over. Organisations should view Business Intelligence as four distinct, but interlocking services that each addresses a different critical business imperative: reporting; self-direct data exploration; operational decision support; and data science. Each of these imperatives addresses different stakeholders and will have its own architect.

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Conclusion: Machines are becoming increasingly proficient at tasks that, in the past, required human intelligence. Virtually all human domain expertise can be encoded in digital data with the right knowledge engineering tools. The bottleneck in understanding between humans and software is shaped by the ambiguities inherent in human communication, not by the challenge of developing machine intelligence. To benefit from big data, organisations need to articulate knowledge in the language of data, i.e. in a format that is not only understandable by humans but also actionable by machines.

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