“Big data” and big-data analytics
Perhaps the biggest big-data challenge, summit attendees said, is how organizations can harness and make use of “other” data: information that historically hasn’t been manageable via traditional relational database approaches. That data includes categories such as Web activity logs and sensor data, and its characteristics typically include a combination of high volume, velocity, variety and variability – the “four V’s,” as Forrester Research Inc. calls them. Gartner Inc. has a similar take on the attributes of big data, substituting “complexity” for “variability.” Transactional data can fit those descriptions as well – but the other forms of big data are often being captured, stored and managed beyond the purview of IT and data warehousing teams, a situation that summit participants said could make it hard for companies to address and utilize the information in an organized way.
Throughout the summit, the consultants and vendors in attendance shared their insights on new technologies and approaches for managing big data, such as Hadoop, NoSQL databases and other schema-less technologies. But the big question on the table was about use cases – namely, how (and where) can companies get the most value from their big-data sets? In this series of video interviews, you’ll hear more about big-data technologies and use cases and get advice on how to get started with big-data analytics.
This was first published in August 2011