Streaming Data - Time is Money

**** Looking BACK to 2012 ****

Streaming data is rapidly becoming an important piece of the big data puzzle. It encompasses data events produced over short time intervals that live or have value for an even shorter period of time. Typically maximum return is realized before the next event occurs. Streaming analysis turns this information into instantaneous actions that often provides feedback into the analytic algorithm itself.

Streaming Example

Consider a stock market trading system that evaluates the risk of each transaction from several points of view. Different market players have a different perspective on each transaction:

• Regulators need to monitor the number of sell versus buy orders to ensure liquidity. They also need to watch trading block size, historic activity and price spreads to avoid what is now called a flash crash. 
• Traders need to do their job and execute transactions rapidly. At the same time, their brokerages  must guard against human error, system failures and the occasional rogue trader.
• Banks and financial institutions must also execute rapid trades while maintaining absolute compliance with regulations like reserve requirements. 

In all of the above cases - and many more - time is a crucial element in the value equation. The time to execute or stop a trade is now. Even one minute is too long to wait for a result.  The value of analysis at the moment a transaction is made cannot be overstated. The cost of fixing bad trades often rises exponentially with time.

Next Time: How can a typical business benefit from this type of analysis?