UNLEASH THE POWER OF BIG DATA WITH HADOOP® NATIVE SQL

Join us for an exploration of how Hadoop Native SQL unleashes the power of Apache™ Hadoop® for business insights and predictive analytics. We will demonstrate how Pivotal HDB, powered by Apache HAWQ (incubating) allows near-real-time execution of ad-hoc queries at scale. Complete analytics tasks faster – in seconds or minutes, not hours or days, using in-database analytics from Apache MAD lib (incubating).
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OTHER ON-DEMAND WEBINARS

Webinar: Enterprise Cybersecurity - The Business of Keeping Business Safe

In today’s high-stakes world of enterprise data security, you need to think like a hacker and act like a Chief Information Security Officer (CISO). Join two seasoned security experts, who once stood on opposites sides of the data-security wall, as they discuss the vital role of data protection in the battle against cyberthreats
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Leverage your QlikView Investment to Modernize your BI Experience

Your business is evolving and it’s critical to understand data in a deeper way than ever before. Thousands of customers like you are finding their organizations demand more than guided analytics apps and dashboards, so now is the ideal time to modernize your BI platform with Qlik.
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Gain Context, Insight and Value from Big Content

OpenText

The Internet of Things, social media and enterprise content all have one thing in common: they generate vast quantities of data — ever-faster. So much so that picking out relevant information and assembling it into meaningful patterns is a tall order. These new data sources also present another challenge. They generate unstructured data - such as text and emojis - that don’t fit neatly into traditional database structures. This data can however hold valuable insights on important and hard-to-quantify concepts such as social sentiment.
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Better Data Means Better Business Decisions

focusvision

We all strive for great data and insights to feed into decisions that propel business’ forward. In today’s fast-spinning world we need to do that ever more quickly and cost-effectively. But when moving quickly, the research participant and their needs can be forgotten, and this can have negative consequences for data quality.
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