Unlocking the potential of data
ASIA many folks thought : ‘ Well , IBM is out of business , they ’ ve sold their business ,’ and yet PCs were just one small part of the business , and just as IBM did with time clocks , punch card machines , and the Selectric typewriter , it divested the old to transition to the new ,” Schnatterly remarks .
“ We ’ re an enterprise company and as such we have transformed into higher value systems , software and services , delivered via the cloud and targeted at extracting insights from data . My team is focused on the infrastructure that supports the full continuum of cloud delivery models , and designed for analysing mass volumes of data .”
Unlocking the potential of data
Data – said to be the oil of the digital age – is something that IBM wants to help its clients exploit . “ Our strategy is to help clients transform into cognitive enterprises and that means that they need to make better use of the data that they have ,” advises Schnatterly . “ There ’ s statistics that estimate that 80 % of the data out there is what they call ‘ dark data ’ – it ’ s not visible to search engines and sits trapped behind firewalls and within the confines of datacentres around the globe . For the most part , this resource goes untapped which means we are gaining no insight from it .
“ What IBM is trying to do with our clients is to help them unlock the potential of the data that they have and to combine this with other data sources , to extract insight and differentiation . Historically , clients have done this through business intelligence programs and queries that they ’ ve created . They would build a data warehouse and they would have algorithms , big elaborate queries and reports that they run against the data , trying to use the results to make better business decisions ,” details Schnatterly .
Creating rule-based programs to support the making of decisions is the old method . Now , companies are converting these rule-based algorithms into machine learning algorithms . With cognitive-based systems , the machine learns as it goes . “ The whole idea is to use algorithms that learn from data on the fly , thus allowing
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