Oracle Autonomous Database - Keep Data More Secured, Eliminate Costly Data Breaches

Oracle

Data, the life blood of today's economy, is an attractive target for cyber attackers. Learn how a self-securing database provides security and peace of mind without relying on manual, error-prone processes allowing you to focus on innovation and not damage control.
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Spotlight

Data reduction techniques such as compression and deduplication within storage arrays have been indispensable to help reduce storage consumption. Unfortunately, due to the variability of data types stored within any given storage array, data reduction savings can greatly fluctuate between environments, making it difficult for administrators to estimate storage needs. This document explores potential savings using real-world data reduction ratios on a Dell EMC™ Unity array.

OTHER ON-DEMAND WEBINARS

How to Use Data Prep to Accelerate Cloud Data Lake Adoption

tdwi

What began as a trickle is now the mainstream: Organizations are moving to the cloud for data management. No longer is the cloud just a cheaper place to park data; it is key to supporting business-critical innovation in advanced analytics, data science, and AI as well as for end-user business intelligence, data exploration, and data visualization. Data lakes and data warehouses running on market-leading platforms such as AWS are growing fast, just as they are on the platforms of competing providers. However, as cloud-based workloads grow in number and size, organizations are facing difficult data preparation challenges. The flow of data raw, diverse, and frequently unstructured can quickly turn cloud data lakes into impenetrable swamps. Without good data preparation technologies and practices, users of all types are frustrated; their productivity and satisfaction suffer because it’s too hard to get accurate data that’s appropriately transformed and structured for their purposes.
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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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The Software-Defined Data Center: A Foundation for Digital Transformation

tierpoint

As reported in Forbes last year, 73% of companies are planning to move to a fully software-defined data center within two years. A software-defined data center is based on a virtualized environment of compute, storage, networking and security in conjunction with policy-based management and automation. The evolution from a traditional data center architecture to one that is software-defined can take months if not years but can yield immense benefits for the business. Join us for a discussion on the progress toward the fully software-defined data center, including benefits of infrastructure as code and overcoming challenges associated with traditional workflows.
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Top 7 Capabilities for Next-Gen Master Data Management

Reltio

This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.
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Spotlight

Data reduction techniques such as compression and deduplication within storage arrays have been indispensable to help reduce storage consumption. Unfortunately, due to the variability of data types stored within any given storage array, data reduction savings can greatly fluctuate between environments, making it difficult for administrators to estimate storage needs. This document explores potential savings using real-world data reduction ratios on a Dell EMC™ Unity array.

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