Findings from Big Data Summit conferences.

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Aster Data have disclosed the results of research conducted among attendees at the Company's Big Data Summit conferences. The Summits have drawn over 800 attendees and were held in major US cities including New York, Chicago, San Francisco, Dallas, and Washington DC over the past year.

The Company hosted the next event--rebranded as the "Data Analytics Summit", to reflect the increased focus on both advanced analytics as well as big data management, in New York City on November 18. The opportunity that harnessing big data presents, the data challenges facing companies, and the advanced analytical techniques brought by Aster Data's solution were outlined by Summit participants and attendees including industry leaders, partners, and analysts from the data warehousing, business intelligence, and analytics markets.

Attendees surveyed during the Summits pointed to several important business opportunities resulting from big data analytics:

* Discover New Market Opportunities: Nearly 30% of respondents thought that exploratory analysis of big data to find "the next big business insight" was a huge business opportunity. This supports the notion that massive data exploration, and the role of data scientists is key for today's data-driven organizations.

* Behavioral Targeting/Advertising: 16% surveyed called out the importance of establishing links between purchasing behavior and areas like advertising spend to better tailor budgets and tailor promotional campaigns.

* Social Network Analysis (SNA): 15% of those surveyed responded mat using social network analysis techniques, including graph-based analytics, to build a more complete profile of their customer base and identifying patterns in the customer base is a key business opportunity. SNA has become critical to identifying user behavior, key influencers and behavioral differences between micro-segments, opening up opportunities for better customer marketing and targeting.

* Monetizing Data: 15% of respondents say monetizing data is a key issue for organizations seeking to unlock the hidden value within previously untapped assets, such as improved ad optimization and improving "purchase to abandonment" ratios

* Fraud Reduction and Risk Profiling: Distinguishing good customers from higher risk customers, for fraud reduction (10%) and risk profiling (10%), was identified as critical for financial services institutions.

While the opportunities big data management and advanced analytics present are promising, the...

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