Data growth curve: Terabytes -> Petabytes -> Exabytes -> Zettabytes -> Yottabytes -> Brontobytes -> Geopbytes. It is getting more interesting.
Consider this:
- Online firms–including Facebook, Visa, Zynga–use Big Data technologies like Hadoop to analyze massive amounts of business transaction data and application data.
- Wall street investment banks, hedge funds, algorithmic and low latency traders are leveraging data appliances such as EMC Greenplum hardware with Hadoop software to do advanced analytics in a “massively scalable” architecture
- Retailers use HP Vertica or Cloudera analyze massive amounts of data simply, quickly and reliably, resulting in “just-in-time” business intelligence.
- New public and private “data cloud” software startups capable of handling petascale problems are emerging to create a new category – Cloudera, Northscale, Splunk, Palantir, Factual, Datameer, Aster Data, TellApart.
Why are some companies in retail, insurance, financial services and healthcare racing to position themselves in Big Data, data clouds and others don’t seem to care?
A new form of business problems are being targeted that were hard to solve before – Modeling true risk, customer churn analysis, flexible supply chains, loyalty pricing, recommendation engines, ad targeting, precision targeting, PoS transaction analysis, threat analysis, trade surveillance, search quality fine tuning, and mashups such as location + ad targeting.