Much of the attention on big data has focused on the infrastructure—data warehouses, Hadoop, appliances—needed to support big data initiatives. However, because data is only useful if you can analyze and act on it, the question becomes: What does it mean to analyze data at scale?
This data might be arriving in streams in true real time; it could (should) be disparate in type; or it might be very high in volume. Traditional approaches weren’t really designed to analyze data at scale. However, analytics are evolving to support business needs that require analyzing big data.
Often vendors refactor their algorithms to run across new platforms. Some algorithmic approaches are new. The net result is that new features and approaches to help organizations analyze vast amounts of time-sensitive and disparate data are becoming available to the business user and expert alike. This is important because the capability to perform analytics at scale can provide unique opportunities to organizations.
This Webinar covers new approaches to analyzing data at scale and practical advice about getting started.
You will learn:
TDWI and IBM Content
Individual, Student, & Team memberships available.