High-Performance Analytics in the Cloud

Teradata

Almost 90 percent of companies surveyed agree that the best place to run analytics is in the cloud – and with Teradata, you can have both cloud elasticity and industrial strength analytics. In fact, some customers have moved their entire on-premises Teradata systems into the cloud in just a few weeks – with zero changes to their applications. These are large systems with hundreds of terabytes, millions of queries, and thousands of users. Teradata’s self-service management console makes it easy to elastically adjust the size, power, and cost of your system. Simply click and go to scale up, scale out, stop your system, or modify security and backup parameters. Watch the video to see for yourself.
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Spotlight

Big data, referring broadly to, “the ability of society to harness information in novel ways to produce useful insights or goods and services of significant value” (Mayer-Schönberger and Cukier, 2013, 9), has been heralded as, “the next frontier for innovation, competition, and productivity” (McKinsey Global Institute, 2011, 1). Despite these claims, a review of literature that highlights big data’s revolutionising effects across sectors and industries revealed that environmental sustainability is largely not yet part of the popular lexicon of big data in action. This study addresses this gap. By interviewing 14 organisations across sectors, I examine how big data is perceived, employed, hindered, and enabled. I conclude that while big data adoption has broadly been slow to coalesce with sustainability efforts, emerging factors such as collaborative partnerships and business model innovation are positioning big data to become an integral element of environmental sustainability and vice versa.


OTHER ON-DEMAND WEBINARS

Apache Apex Introduction part 2

DataTorrent

Join us at Capital One Office in San Francisco, where the DataTorrent lead architects will present and introduce you to Project Apex, the industry’s only enterprise grade, fault tolerant batch and stream processing engine.
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Big Data and Analytics Right Now

SAS

In a wide-ranging conversation, Erik Brynjolfsson and Thomas H. Davenport explore what’s different about today’s analytics, the role of the data scientist, the types of skills necessary to do this work and how achieving the potential of analytics may require change management. The two experts finish with advice and an action plan for what to do now, and in the future, to be successful in using big data.
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Deliver Big Data and Databases as-a-Service on Kubernetes

Robin Systems, Inc

You need greater efficiency, agility, scalability, and cost-effectiveness from your IT infrastructure. Legacy storage solutions just aren’t cutting it anymore! What many IT Organizations don’t know is that there are many different solutions available to solve these IT challenges! The one thing that all businesses have in common is that they want and need IT solutions to make their lives easier, more efficient, and more affordable, particularly as digital transformation efforts take center stage. Converged, hyperconverged, composable, and other integrated platforms (collectively, integrated systems) all have the potential to accomplish these goals which can allow the IT organization to focus their efforts more on business outcomes rather than hardware.
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IOT Ingestion & Analytics Using Apache Apex - A Native Hadoop Platform

DataTorrent

Internet of Things (IoT) devices are becoming more ubiquitous in consumer, business and industrial landscapes. They are being widely used in applications ranging from home automation to the industrial internet.
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Spotlight

Big data, referring broadly to, “the ability of society to harness information in novel ways to produce useful insights or goods and services of significant value” (Mayer-Schönberger and Cukier, 2013, 9), has been heralded as, “the next frontier for innovation, competition, and productivity” (McKinsey Global Institute, 2011, 1). Despite these claims, a review of literature that highlights big data’s revolutionising effects across sectors and industries revealed that environmental sustainability is largely not yet part of the popular lexicon of big data in action. This study addresses this gap. By interviewing 14 organisations across sectors, I examine how big data is perceived, employed, hindered, and enabled. I conclude that while big data adoption has broadly been slow to coalesce with sustainability efforts, emerging factors such as collaborative partnerships and business model innovation are positioning big data to become an integral element of environmental sustainability and vice versa.

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