Jiang also went on to say that he isn't even sure what Deutsche Bank is looking for from the data it is collecting, but he is sure that it will provide important insight.
"I think if the underlying data is relational and you do traditional business intelligence, you know what you are looking for. If your underlying data store is big, unstructured, raw data, you will be able to find something that you don't know what you are looking for," said Jiang.
"It will provide a high level of pure intelligence."
However, he is sure that once Deutsche Bank's system begin undertaking intelligent big data analytics, much of the other data processing will become less significant.
"If you take every little bit of data in, it will give you something that you didn't know you were looking for. That's what I'm interested in. I would argue that with any bank 80 percent of the computing is a waste of time," he said.
"If you think about what is being processed, what they are actually doing is just moving data around. With that the data gets worse and worse as you go, and then lots of subsequent people are hired in India to try and improve data quality."
He added: "But, if you have a correct way of looking at data from a data point of view, these efforts become completely meaningless and time wasting."
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