How to Revolutionize Analytics with Next-Generation In-Memory Computing
August 25, 2014 Leave a comment
by Les King
Director, Big Data, Analytics and Database Solutions – Information Management, Software Group
We are now in the era of cognitive analytics. These are analytic processes that provide useful information with a timeliness which qualifies as “speed of thought”. More and more clients are leveraging the next generation of analytic computing to address business challenges which could never be handled before.
To understand this idea, here’s a fun video that explains this theory a little better and gives a real business example of exactly this: What do chicken dinners have to do with IBM?
As another example, just recently a few friends and I were looking for a coffee shop which had both WiFi and a table which was near a working power outlet. We were surprised to discover that a coffee shop in the area was analyzing the information from our mobile devices and was able to let us know that they had what we were looking for. Coffee shops are all over the place, but, that real time analytics and communication with us was what made the difference. The coffee shop doing this real-time analytics ended up getting our business.
What do the two business examples above have in common ? They both require the analysis of large volumes of information and to be able to take action on this information, very quickly. One of the key technologies allowing clients to accomplish this is in-memory computing. Hardware can handle an ever increasing volume of memory and processing power. There have also been amazing strides in the area of data compression. Vendors who provide the ability to analyze data, in memory, while compressed, will have a huge advantage with these analytic workloads.
An example of this would be IBM’s DB2 with BLU Acceleration. DB2 with BLU Acceleration provides an average of 10X ( 90% ) compression rates. This means 1 TB of data can be stored in about 100 GB of space. DB2 with BLU Acceleration stores data in memory in its compressed form, using less memory to store vast amounts of business data. More importantly, DB2 with BLU Acceleration can analyze this data while compressed. This combination of capabilities positions DB2 with BLU Acceleration as a key technology in the era of big data and cognitive analytics.
When you consider the business examples above, you can see the competitive advantage these companies will have. These next generation analytic infrastructures, which leverage in-memory computing, will allow these companies to grow their business and take clients from their competitors.
To hear another example of how this modernization of a company’s analytic infrastructure is helping solve real world business challenges, check out this upcoming webinar “How to Revolutionize Analytics with Next-Generation In-Memory Computing“, taking place on Sept 25 at 12:00 EDT .