8. ”Big data is a relative term. Every
organisation will eventually reach a point
where the volume, velocity and variety
of their data will be something that they
have to address."
In my role as a search technology specialist at funnelback I often find myself face to face with prospects and existing clients. We have a diverse client base ranging form the large corporates to the small charities.
Whereas larger enterprises often have knowledge of big data and at least an outline of a data strategy, the SMEs often find themselves lost in the sea of buzzwords and examples.
This quote emphasises the stress on size when big data is mentioned in popular press.
These three aspects are called the 3 Vs of Big Data. Any set of data which, in one or more of these aspects, is becoming an issue for an organisation to deal with is considered to be said organisation’s Big Data.
Some SMEs find themselves befuddled by the extreme examples out there
PseudoquotingMark Troester from SAS, who puts Big Data in a different light, it is a relative concept that applies to 3 important aspects of data. Volume, Velocity and Variety.
SMEs need something that is flexible, fast, performant but most of all affordable. I will show you over the next few slides why a modern search engine can meet these requirements.
A modern enterprise and web search engine can deliver all these requirements to an SME.
To make the offering more affordable the combination of a SaaS approach with a private cloud backing and a measured approach to license packages can make all the difference.
A small intro slide to introduce one of our big data examples (out of many more )
The situation: The client needed to present a very complex set of analytics over dozens of funds, over dozens of years, with 100’s of millions of data points across the set. Funnelback was used with custom workflows to define the rules to generate the analytics and quickly bring them to the front-end user. This project meant a sales consultant could approach a prospect with a single ipad and show data interactively instead of with a suitcase full of paperwork (quite literally).
The solution involved transforming the CSV to XML using Funnelback’s data transformation toolset. The data was then run through a workflow engine to create the appropriate graph sets over the date periods. Once the graph data was assembled it was then indexed and presented through a responsive designed search.
This is a screenshot (with some confidential information blurred) of thefront-end interface. Around 40 graphs are powered by Funnelback data sets both pre-generated at index time and generated on the fly. With this site, the turn-around time for new data is a matter of minutes, sales staff can take an iphone rather than a suitcase of paperwork and the CEO always has his reports handy!