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CASE ai

BDC's unique Causal analytic search engine performs a search of your data via our proven, breakthrough algorithms to unlock the cause and effect drivers hidden in the data.
In essence, we identify what causes what. This takes you beyond correlations which can be extremely misleading.
Once you know the Cause, you can begin to remedy and predict the Effect. This is a very powerful tool for any organisation. It operates in a similar function to Google's search engine. BDC ingests the data set and performs a causal search which then provides all the causal relationships from within. Performing this function finds the "known causal knowns", however, the real value is often in unlocking the hidden "unknowns" within a data set. Identifying these can provide groundbreaking insights and lead to increased profits, safety outcomes and system efficiencies in general.

CMAP

CMAP is BDC’s causal consulting service whereby we work alongside the client’s and their team to develop and incorporate “causal structuring”.

What is Causal Structuring and Why is it so important moving into the future?

If you think of the construction of the Great Pyramids, their base needed to be solid and formed correctly to build upon. BDC’s CMAP is the base from which you can add or build your data analytic solutions from. By utilizing BDC’s causal structuring and CMAP capability, an entity can put in place a validated base to their data analytics from a cause-and-effect perspective which will allow it to glean far greater value from its data set and always be building from a true causal approach rather than potentially spurious correlations. Incorporating CMAP is a wise approach to adding validation and real proof to any existing data analytic solutions. This allows more definitive and informed business decisions and maximises value from the data set. CMAP sets a watermark to move forward from into the future using true causation.