The Intersection of Big Data and Analytics
Type:
On-Demand Webinar
Length:
54:21 The term “big data” has arisen in recent years to describe multi-terabyte datasets. Big data certainly has its challenges, relative to scalability and data management. But it’s also useful for business intelligence purposes. In particular, the massive datasets of big data provide substantial data samples for various forms of analytics, especially advanced forms that are discovery oriented.
In a related trend, many organizations are stepping up their use of analytics, as a way of understanding a relentlessly changing business and economic environment. Whether you’re trying to discover the root cause of the latest customer churn or the hidden costs that are eroding the bottom line, you need discovery oriented analytic tools and techniques that work well with big data. That’s why big data and analytics have come together in recent years, thereby causing substantial changes in tools and best practices for analytics.
You Will Learn:
- Why businesses and other organizations need analytics more than ever
- Why analytics that taps into big data has become a common practice
- How to select an approach to analytics from the many available
- New tools, platforms and practices designed to provide analytics with big data
- Big data’s intersections (both challenging and useful) with analytics, plus related disciplines like visualization, business intelligence, and data warehousing
Featured Speaker(s):
Philip Russom
Senior Manager, TDWI Research
Philip Russom is the senior manager of research and services at The Data Warehousing Institute (TDWI), where he oversees many of TDWI’s research-oriented publications, services, and events. Prior to joining TDWI in 2005, Russom was an industry analyst covering BI at Forrester Research, Giga Information Group, and Hurwitz Group, as well as a contributing editor with Intelligent Enterprise and DM Review magazines.