What is Anomaly Detection and its Role in Preventative Analytics

DataRPM

Equipment downtime is a multi-billion-dollar problem which will only continue to grow with exploding sensor data. According to IDC, by 2018 a third of industrial companies will be disrupted by “Industrial IoT enabled competitors.” So how can companies monetize their IoT investments for higher operational efficiencies and productivity? Anomaly Detection and Prediction is the silver bullet that companies need to maximize their machine uptime and performance. Watch the on-demand webinar featuring the Dean of Big Data, Bill Schmarzo, Chief Technology Officer, Big Data at Dell EMC and Seth Page, General Manager and Head of Partnerships at Progress DataRPM, to learn how zero factory downtime can be a reality.
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Spotlight

Since the dawn of business intelligence, BI systems have been implemented using an exhaustive and exhausting requirements planning process. Each step of the process – requirements gathering, design, implementation, verification, and maintenance – was completed before the next began. These old-school “waterfall” processes developed in the 1950s changed little in the half-century that followed. There’s a better way. Agile Business Intelligence is a new way to think about the process of building and managing BI systems. In the last five years, technologies and practices have matured, so that it is now possible to deliver business intelligence systems faster, at lower cost, and with greater control by end users.

OTHER ON-DEMAND WEBINARS

Implementing Oracle Database-as-a-Service for Cloud-Like Agility

Robin Systems, Inc

A growing number of organizations are turning to Docker containers to help solve really big application requirements. Among the biggest out there are those imposed by Oracle and Oracle RAC. What if you could deploy Oracle or Oracle RAC as a stateless cloud-native workload in your environment? Transform a complex process into one with an App Store-like experience.
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Choosing the Right Database for Time Series Data

MemSQL

In this webinar, MemSQL Product Marketing Manager Mike Boyarski describes the growth in popularity of time series data and talks about the best options for a time series database, including a live Q&A. You can view the webinar and download the slides here. Here at MemSQL, we’ve had a lot of interest in our blog posts on time series data and choosing a time series database, as well as our O’Reilly time series ebook download. However, this webinar does a particularly good job of explaining what you would want in a time series database, and how that fits with MemSQL. We encourage you to read this blog post, then view the webinar.
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UNDERSTANDING BIG DATA & ARTIFICIAL INTELLIGENCE

Yoh

Still feeling a bit in the dark about Big Data or terrified by the term Artificial Intelligence? Many organizations have been embracing both of these concepts and capitalizing on their insights for years. Now it’s your turn to truly get on board with how you can use Big Data and Artificial Intelligence to shape your Talent Acquisition strategy. And when better to learn more about these than at the beginning of a new year? Hear from a panel of visionaries and learn the ins and outs of Big Data and Artificial Intelligence, from providing in-depth explanations to leadership, to identifying their pitfalls and opportunities, who should be spear-heading these initiatives within your organization and how to implement.
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Visualizing Geospatial Data at Scale

Arcadiadata

Geospatial data is everywhere today. Your mapping capabilities need to handle the growing volumes of “big data” to deliver location-based insights at any level. Large-scale mapping use cases require a scalable and real-time visualization platform that enables self-service analysis. End users need a fast, interactive system that can immediately display any view of their data on demand.
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Spotlight

Since the dawn of business intelligence, BI systems have been implemented using an exhaustive and exhausting requirements planning process. Each step of the process – requirements gathering, design, implementation, verification, and maintenance – was completed before the next began. These old-school “waterfall” processes developed in the 1950s changed little in the half-century that followed. There’s a better way. Agile Business Intelligence is a new way to think about the process of building and managing BI systems. In the last five years, technologies and practices have matured, so that it is now possible to deliver business intelligence systems faster, at lower cost, and with greater control by end users.

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