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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.

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.

Big Data Analytics as a Source of Business Innovation

Competitive advantage from data analytics is changing, and for the better. Big data analytics are increasingly the start and source of business innovation, which is producing a surge of benefits across industries. Download a new report from SAS to lean more about how recent headway in data analytics is pushing business innovation.

Five big data challenges And how to overcome them with visual analytics

Big data is set to offer companies tremendous insight. Data visualization is becoming an increasingly important component of analytics in the age of big data. access to information in a form they can easily understand and share with others. This begs the question: How do you present big data in a way that business leaders can quickly understand and use? Learn more by reading this white paper.

How to Use Hadoop as a Piece of the Big Data Puzzle

Organizations are embracing Hadoop for several notable merits:

• Hadoop is distributed. Bringing a high-tech twist to the adage, “Many hands make light work,” data is stored on local disks of a distributed cluster of servers.
• Hadoop runs on commodity hardware. Based on the average cost per terabyte of compute capacity of a prepackaged system, Hadoop is easily 10 times cheaper for comparable computing capacity compared to higher-cost specialized hardware.
• Hadoop is fault-tolerant. Hardware failure is expected and is mitigated by data replication and speculative processing. If capacity is available, Hadoop runs multiple copies of the same task, accepting the results from the task that finishes first. To learn more read this white paper.