Big data, in my opinion, technically should be data that's atleast 5-10 TBs. But that hasn't stopped people from calling data that's an order of magnitude small

Big data, in my opinion, technically should be data that's atleast 5-10 TBs. But that hasn't stopped people from calling data that's an order of magnitude smaller to be "big data". Example of big data could involve transactions, logs, click stream, sales data, or even GPS data (say in telecom). If you're looking for some opportunities here, a good safe bet would be Hadoop and HBase. You can treat them as open source implementations of the original Google papers on Map Reduce and Big Table respectively. Today so many companies are realizing that they have data locked up in logs and other largely static databases that they can analyze using map reduce jobs. You can generate reports, trends, patterns and more from these analysis and can use them to guide business decisions.