SNIA will again sponsor the Persistent Memory and Computational Storage Track sessions at Flash Memory Summit, and the SNIA Compute, Memory, and Storage Initiative will have a mainstage presentation and a “virtual booth” featuring SNIA technical work activities.  Details on the conference are at www.flashmemorysummit.com

The pandemic has taught data professionals one essential thing. Data is like water when it escapes; it reaches every aspect of the community it inhabits. This fact becomes apparent when the general public has access to statistics, assessments, analysis and even medical journals related to the pandemic, at a scale never seen before.

Insight understands information in context to the degree that you can gain an understanding beyond just the facts presented and instead make reasonable predictions and suppositions about new instances of that data.

RAID on CPU is an enterprise RAID solution specifically designed for NVMe-based solid state drives (SSDs). This innovative technology provides the ability to directly connect NVMe-based SSD’s to PCIe lanes and make RAID arrays using those SSD’s without the need for a RAID Host Bus Adapter (HBA). As a result, customers gain NVMe SSD performance and data availability without the need of a traditional RAID HBA.

Electronic payments, once the purview of a few companies, have expanded to include a variety of financial and technology companies. Internet of Payment (IoP) enables payment processing over many kinds of IoT devices and has also led to the emergence of the micro-transaction. The growth of independent payment services offering e-commerce solutions, such as Square, and the entry of new ways to pay, such as Apple Pay mean that a variety of devices and technologies also have come into wide use.

The storage industry has many applications that rely on storing data as objects. In fact, it’s the most popular way that unstructured data is accessed. At the drive level, however, the devil is in the details. Normally, storage devices store information as blocks, not objects. This means that there is some translation that goes on between the data as it is consumed (i.e., objects) and the data that is stored (i.e., blocks).

Organizations inevitably store multiple copies of the same data. Users and applications store the same files over and over, intentionally or inadvertently. Developers, testers and analysts keep many similar copies of the same data. And backup programs copy the same or similar files daily, often to multiple locations or storage devices. It’s not unusual to end up with some data replicated thousands of times.

So how do we stop the duplication madness? Join this webcast where we’ll discuss how to reduce the number of copies of data that get stored, mirrored, or backed up.

The broad adoption of 5G, Internet of things (IoT) and edge computing will reshape the nature and role of enterprise and cloud storage over the next several years. What building blocks, capabilities and integration methods are needed to make this happen?

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Whether traveling by car, plane or train, it is critical to get from here to there safely and securely. Just like you, your data must be safe and sound as it makes its journey across an internal network or to an external cloud storage device. In this webcast, we'll cover what the threats are to your data as it's transmitted, how attackers can interfere with data along its journey, and methods of putting effective protection measures in place for data in transit.

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The In-Memory Computing Summit 2020, which will be held virtually October 28-29, enables developers, decision makers, and visionaries to network and learn about technologies, solutions and real-world use cases for in-memory computing. The conference features keynotes, breakout sessions, online interactions, an exhibition area, and more.

In modern analytics deployments, latency is the fatal flaw that limits the efficacy of the overall system. Solutions move at the speed of decision, and microseconds could mean the difference between success and failure against competitive offerings. Artificial Intelligence, Machine Learning, and In-Memory Analytics solutions have significantly reduced latency, but the sheer volume of data and its potential broad distribution across the globe prevents a single analytics node from efficiently harvesting and processing data.