Ask people on the street what mental image they associate with the words “stock exchange,” and you’ll likely hear about a large imposing building in the middle of New York or Chicago. Inside the building there is a huge space crowded with traders in multicolored jackets screaming and gesticulating to each other.
Until ten years ago, that would have been a pretty accurate description of a stock exchange. Today, however, almost all trading is done by algorithms firing digital commands traveling near the speed of light to rows upon rows of computer servers sitting in nondescript suburban warehouses.
The transition from human to electronic trading came with the promise of using faster and cheaper technology to drastically lower the costs of trading shares and to make it much easier to determine the most up-to-date prices for all market participants (commonly known as price discovery).
We are at the beginning of the Big Data era, and there is widespread anticipation that this will be a huge benefit to companies. I’ve been attending the World Economic Forum in Davos and in my `Data to Decisions’ panel we heard CEOs tell how Big Data can reinvent everything from CRM to internal processes to product design.
We also heard that there are significant challenges in data sourcing, permission agreements, data quality and of course privacy concerns, as most Big Data is personal data about customers. Fortunately these challenges can be addressed by conventional business practices.