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Best Practices Report: The Power of Operationalized Analytics

The pace of business continues to increase. And the power of big data and analytics is growing. But it’s not enough to just analyze this data anymore. According to a new TDWI Best Practices Report, sponsored by SAS, businesses also need to take action on this data. Read on to find out how businesses can better operationalize their analytics and derive value from their data. 

Business Analytics are Helping Companies Push the Envelope & Drive Innovation

These days, data and business analytics are the catalysts allowing many companies to push the envelope. A new MITSloan Management Review Research Report, sponsored by SAS, explores analytics as a source of business innovation, as well as how this increased ability to innovate is benefitting a spectrum of industries.

New SAS® Data Preparation Gets Big Data Ready for Analysis

With 2.5 quintillion bytes of data being created every day, organizations need better ways to prepare it for analysis. Analytics leader SAS is now offering SAS® Data Preparation to provide analytics professionals and business users an interactive, real-time self-service application that will ease the burden of readying data for analysis.

Operationalizing and Embedding Analytics for Action

As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Download a new TDWI Best Practices Report from SAS that focuses on how organizations can and are operationalizing and embedding analytics to derive business value.

5 Ways Interaction Analytics Can Improve Customer Experience

In this special guest feature, Aviad Abiri, Vice President of Portfolio Sales Enablement at NICE, provides 5 ways interaction analytics can improve customer experience. Interaction analytics helps to improve the overall customer service experience, and can also assist companies in advancing their bottom line.

Every Retailers’ Nightmare Before Christmas

In this contributed article, David Drai, Co-founder & CEO for Anodot, offers a number of important steps for how to say goodbye to the “glitch-grinch” based on the benefits of a data-rich, e-commerce ecosystem where the key to effectively avoiding the glitch is automation and technology.

Unmasking Privileged Identity Thieves with User Behavior Analytics

In this special guest feature, Csaba Krasznay, Security Evangelist at Balabit, discusses how applying advanced statistical techniques to IT users’ digital behaviors, security professionals can then recognize and escalate unusual activity that could be related to identity theft.

AtScale Brings its Universal Semantic Layer to the AWS Cloud

AtScale announced the preview availability of its universal semantic platform for business intelligence (BI) on Amazon Redshift. With this offer, enterprises will gain faster time to insight by deploying Big Data Analytics on the Amazon Cloud and benefit from an enhanced ROI by running production-ready workloads on the cost-effective Amazon cloud platform.

Big Bang of Intelligence – New Algorithms, Parallel Systems and Big Data Unlocking Oportunities

Everybody’s talking about big data. In a new report “AI, Analytics and the Future of Your Enterprise,” Pure Storage points out how huge promises have been made about its role in driving enterprises forward. But few organizations are realizing its true benefits. For those able to put data to good use, there’s much to be excited about. Data is transforming not only businesses, but entire industries, and the world as we know it.

Cambridge Semantics Announces Semantic Layer for Multi-Cloud Environments

Cambridge Semantics, a leading provider of a universal semantic layer for data management and connected data analytics solutions, announced multi-cloud support for Anzo Smart Data Lake (SDL) 4.0, its flagship product that brings business meaning to all enterprise data.