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The Customer Experience Has Evolved Thanks to IoT – The Time is Now for Contact Centers to Take Charge

In this special guest feature Jack Nichols, Director of Product Management at Genesys, discusses IoT and how with all this data available in near real-time, businesses must determine how to leverage it in a way that equally serves themselves and their customers.

Radius Data Stewardship Removes Obstacles Between Data and Revenue

Radius, a leading business-to-business predictive marketing platform, announced the addition of Radius Data Stewardship to its solutions. With Radius Data Stewardship, marketers have access to the highest quality data for deriving precise insights that expand visibility into new and existing markets, effectively informing decisions for campaign planning and more accurately predicting and driving pipeline growth.

IoT Analytics – Part 6

This is the sixth and final article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this segment, we’ll provide a series of “best practices” and “lessons learned” for what companies are seeking from deploying IoT analytics.

Five Ways Data Analytics Will Storm the Stage in 2017

It is becoming more and more apparent how data analysis is driving e-commerce revenues. And this growing importance has forced e-tailers and e-commerce firms to hire more data scientists in order to better understand how customer engagement impacts revenue and sales. This assessment comes from SOASTA, the leader in performance analytics, who reveals that data analytics is important in all aspects of the organization – from digital transformation to digital performance management.
SOASTA offers five ways data analytics will storm the stage in 2017.

The Business Value of Deep Text Analytics at Massive Document Scale

In this special guest feature, Dr. Brian Sager, CEO and co-founder of Omnity.io, provides 5 examples in support of the business value of deep text analytics at massive document scale. The examples are drawn from use cases within R&D, competitive strategy, patent law, and knowledge management, as well as M&A and post merger integration.

Kinetica Delivers Advanced In-Database Analytics, Opening the Way for Converged AI and BI Workloads Accelerated by GPUs

Kinetica, provider of the fast, in-memory database accelerated by GPUs, announced the availability of in-database analytics via user-defined functions (UDFs). This capability makes the parallel processing power of the GPU accessible to custom analytics functions deployed within Kinetica.

From Small to Big Data, Adopting the Advanced Analytics Mindset

In this special technology white paper, From Small to Big Data, Adopting the Advanced Analytics Mindset, you’ll learn how to help data teams — analysts, scientists, and managers — to collaborate on data projects. One of the key success factors for these teams is to allow analysts to work on Big Data as easily as they do on smaller data with Excel, as well as to help them find new use cases specific to the data available and the tools at hand.

In Fantasy Football, as in Business, Speed-to-Action is a Competitive Advantage

In this special guest feature, Dan Wilmot, Sr. Architect at Pyramid Analytics, explores how to unlock opportunities previously hidden within the depths Fantasy Football data.

Qlik Sense Cloud Business Now Available for Immediate Web-based Visual Analytics

Qlik®, a leader in visual analytics, announced that Qlik Sense® Cloud Business, its SaaS-based visual analytics solution is now available for SMBs, groups, and teams to create, manage, and share analytics in the cloud. Powered by the patented QIX Associative Indexing Engine, Qlik Sense Cloud Business provides the scalability and performance of the industry-proven Qlik visual analytics platform in a complete cloud environment.

IoT Analytics – Part 5

This is the fifth article in a series focusing on a technology that is rising in importance to enterprise use of big data – IoT Analytics, or the analytical component of the Internet-of-Things. In this segment, we’ll talk about the challenges of deploying IoT analytics.