Name: How Machine Learning Helps Predict Equipment Failure
Start: 2017-04-13T08:00:00Z
End: 2017-04-13T08:22:15.000Z
Location: BrightTALK

You've got data. It's time to manage it. Find information here on everything from data governance and data quality, to master and metadata management, data architecture, and the thing that was just invented ten seconds ago.

Advertisers and marketers have used cookies for tracking and personalization purposes for more than two decades. But with Google’s third-party cookie ban looming, businesses need to explore alternative methods to get the right content in front of the right people. In just a few minutes, TechTarget’s Social Media Specialist, Katie Donegan, will explore some alternatives to consider.

Speed Learning: 4 Alternatives for the Cookieless Future

The pandemic accelerated technological changes in the mission critical industry which is breaking new grounds at an unprecedented scale. 

The question is, what does the next generation evolve into when considering how homo sapiens will interact with this technology? Are we ready for human-enhancing innovations such as AI, machine learning, robotics, and AR/VR?

This webinar will illustrate how the next generation mission critical engineer and intelligent business powering technology will bridge the gap as the industry doubles in size and loses half its wisdom in this decade.

The audience will take away the following from this webinar:

- Discuss how modernizing data centers is critical for proactive business success and seamless scaling as AI continues to be introduced. 
- Learn how technological innovations can help transform the operations and energy consumption in critical environments. 
- Learn how IoT makes a data center flexible, agile, cost-effective, secure and intelligent. 
- Discuss common problems, smarter solutions and their end results.

AI, & Machines for Critical Infrastructures

Digital transformation is pushing for consolidated, denser and more intelligent data centers. At the same time, explosive growth of data driven by mobility, smart devices, IoT, 5G and digital services is driving trends like edge computing and micro-data centers. These data centers are more compute and data intensive with far more network traffic and higher need for embedded instrumentation for monitoring. 

The next-gen data centers employ new architectures and design techniques that make monitoring tricky as traditional tools and techniques go obsolete.  

Attend this session to learn: 
•	What the next-gen data center architecture looks like from edge to the core 
•	How the combination of high-performance fabrics with overlay SDx technologies and intelligent controls influences the network traffic patterns and processing  
•	How to monitor the above network architectures effectively to turn network data into actionable information

Network Monitoring for the Next-Gen Data Center

Fundamentally, data storage needs to innovate to become more useful to enterprise strategy.
On the first day of the Summit - Oct. 20th, at 1pm (EDT) daregraphic will lead a panel discussion that will review some of the conclusions of the report and invites panelists to discuss their own experiences with clients struggling with unstructured data stored on ever-expanding devices.  The panel will also discuss innovative ways to help these clients federate this data and realize its true value for their organizations.
Panelists from Quantum, North Shore Automation and DataIntell will join daregraphic’s CEO for the conference.  

Participants will learn:
•	What is considered unstructured data
•	How this data is wasted rather than leveraged for enterprise value
•	What are some of the ways to federate this data to extract value
•	What types of strategic contribution this data can ultimately bring to organizations

Pierre Couture, CEO, Daregraphic
Noemi Greyzdorf, Head of Product and Solution Marketing, Quantum
Bryson Jones, Co-Founder & CIO, North Shore Automation 
Olivier Rivard, Head of Developpement, DataIntell

Managing Unstructured Data to Unlock Enterprise Value

NVMe over Fabrics technology is gaining momentum and getting more tractions in data centers, but there are three kinds of Ethernet based NVMe over Fabrics transports: iWARP, RoCEv2 and TCP. How do we optimize NVMe over Fabrics performance with different Ethernet transports?
 
Setting aside the consideration of network infrastructure, scalability, security requirement and complete solution stack, this webcast will explore the performance of different Ethernet-based transport for NVMe over Fabrics at micro benchmark level. We will show three key performance indicators: IOPs, Throughput, and Latency with different workloads including: Sequential Read/Write, Random Read/Write, 70%Read/30%Write, with different data size. We will compare the result of three Ethernet based transports: iWARP, RoCEv2 and TCP.
 
Further, we will dig a little bit deeper to talk about the variables that will impact the performance of different Ethernet transports. There are a lot of variables that you can tune but these variables will impact the performance of each transport to different extents. We will cover the variables:
1.How many CPU cores are needed (I’m willing to give)?
2.Optane SSD or 3D NAND SSD?
3.How deep should the Q-Depth be?
4.Why do I need to care about MTU?
 
This discussion won’t tell you which transport is the best. Instead we unfold the performance of each transport and tell you what it would take for each transport to get the best performance, so that you can make the best choice for your transport for NVMe over Fabrics solutions.

After you watch the presentation, check out the Q&A blog: https://bit.ly/36A44AU

Optimizing NVMe-oF Performance with Different Ethernet Transports: Host Factors

In this webcast, SNIA experts will discuss what composable infrastructure is, what prompted its development, solutions, enabling technologies, standards/products and how computational storage fits in.

Composable Infrastructure and Computational Storage

Everyone knows data volumes are exploding faster than IT budgets.  And customers are increasingly moving to flash storage, which is faster and easier to use than hard drives, but still more expensive. To cope with this conundrum and squeeze more efficiency from storage, storage vendors and customers can turn to data reduction techniques such as compression, deduplication, thin provisioning and snapshots. This webcast will specifically focus on data compression, which can be done at different times, at stages in the storage process, and using different techniques. We’ll discuss:
 
•Where compression can be done: at the client, on the network, on the storage controller, or within the storage devices
•What types of data should be compressed
•When to compress: real-time compression vs. post-process compression
•Different compression techniques
•How compression affects performance
 
Tune in to this compact and informative SNIA webcast, which packs in copious content .

After you watch the webcast, check out the Q&A blog: https://sniansfblog.org/data-compression-qa/

Compression: Putting the Squeeze on Storage

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).

Naturally, being efficient means that there are performance boosts, and simplicity means that there are fewer things that can go wrong. Moving towards storing key value pairs that get away from the traditional block storage paradigm make it easier and simpler to access objects. 

Both The NVM Express™ group and SNIA have done quite a bit of work in standardizing this approach:

•NVM Express™ has completed standardization of the Key Value Command Set
•SNIA has standardized a Key Value API
•Spoiler alert: these two work very well together!

What does this mean? And why should you care? That’s what this webinar is going to cover! This presentation will discuss the benefits of Key Value storage, present the major features of the NVMe-KV Command Set and how it interacts with the NVMe standards. It will also cover the SNIA KV-API and open source work that is available to take advantage of Key Value storage.

We’ll be going deep under the covers to discuss:
•How this approach is different than traditional block-based storage
•Why doing this makes sense for certain types of data (and, of course, why doing this may not make sense for certain types of data)
•How this simplifies the storage stack
•Who should care about this, why they should care about this, and whether or not you are in that group

After you watch the webcast, check out the Q&A blog at https://bit.ly/2JSFcez

The Key to Value: Understanding the NVMe Key-Value Standard

Protection against cyber threats is recognized as a necessary component of an effective risk management approach, typically based on a well-known cybersecurity framework. A growing area to further mitigate risks and provide organizations with the high level of protection they need is cyber insurance. However, it’s not as simple as buying a pre-packaged policy.

This webcast will provide an overview of how cyber insurance fits in a risk management program. It will identify key terms and conditions that should be understood and carefully negotiated. Cyber insurance policies may not cover all types of losses, so it is critical to identify what risks and conditions are excluded from a cyber insurance policy before you buy.

Join this webcast to learn:
•General threat tactics, risk management approaches, cybersecurity frameworks
•How cyber insurance fits within an enterprise data security strategy
•Nuances of cyber insurance – exclusions, exemption, triggers, deductibles and payouts
•Challenges associated with data stored in the cloud

After you watch the webcast, check out the Q&A blog: https://bit.ly/36ijYzI

Does Your Storage Need a Cyber Insurance Tune-Up?

Everyone knows data volumes are growing rapidly, far faster than IT budgets, which range from flat to minimal annual growth. One of the drivers of such rapid data growth is storing multiple copies of the same data. Developers copy data for testing and analysis. Users email and store multiple copies of the same files. Administrators typically back up the same data over and over, often with minimal to no changes. 

To avoid a budget crisis and paying more than once to store the same data, storage vendors and customers want to use data reduction techniques such as deduplication, compression, thin provisioning and snapshots.  

This webcast will specifically focus on the fundamentals of data reduction, which can be performed in different places and at different stages of the data lifecycle. Like most technologies, there are related means to do this, but with enough difference to cause confusion. For that reason, we’re going to be looking at:
 
•How companies end up with so many copies of the same data
•Difference between deduplication and compression – when should you use one vs. the other?
•Where to reduce data: application-level, networked storage, backups, and during data movement
•When to collapse the copies: real-time vs. post-process deduplication
•Performance considerations
 
Tune in to this efficient and educational SNIA webcast, which covers valuable concepts with minimal repetition or redundancy.

After you watch the presentation, check out the Q&A blog at: https://bit.ly/34m949E

Everything You Wanted to Know...But Were Too Proud to Ask: Data Reduction

The rapid growth in infrastructure to support the real time and continuous collection and sharing of data to make better business decisions has led to an age of unprecedented information access and storage. This proliferation of data sources and of high-density data storage has put volumes of data at one’s fingertips. While the collection of large amounts of data has increased knowledge and efficiencies for businesses, it has also made attacks upon that information—theft, modification, or holding it for ransom--more tempting and easier. Cryptography is often used to protect valuable data.

This webcast will present an overview of applied cryptography techniques for the most popular use cases. We will discuss ways of securing data, the factors and trade-offs that must be considered, as well as some of the general risks that need to be mitigated, including:

•Encryption techniques for authenticating users  
•Encrypting data—either at rest or in motion 
•Using hashes to authenticate/ Information coding and data transfer methodologies 
•Cryptography for Blockchain

Storage Networking Security Series: Applied Cryptography

The Enterprise and Data Center SSD Form Factor (EDSFF) is designed natively for data center NVMe SSDs to improve thermal, power, performance, and capacity scaling. EDSFF has different variants for flexible and scalable performance, dense storage configurations, general purpose servers, and improved data center TCO.  At the 2020 Open Compute Virtual Summit OEMs, cloud service providers, hyperscale data center, and SSD vendors showcased products and their vision for how this new family of SSD form factors solves real data challenges.

Join this SNIA Compute Memory and Storage Initiative webcast where expert panelists from companies that have been involved in EDSFF since the beginning discuss how they will use the EDSFF form factor. OEMs will discuss their goals for E3 and the new updated version of the E3 specification! (SFF-TA-1008)  Hyperscale data center and cloud service providers will discuss how E1.S (SFF-TA-1006) helps solve performance scalability, serviceability, capacity, and thermal challenges for future NVMe SSDs and persistent memory in 1U servers.

Enterprise and Data Center SSD Form Factor - the end of the 2.5-inch disk era?

Worldwide, regulations are being promulgated and aggressively enforced with the intention of protecting personal data. These regulatory actions are being taken to help mitigate exploitation of this data by cybercriminals and other opportunistic groups who have turned this into a profitable enterprise. Failure to meet these data protection requirements puts individuals at risk (e.g., identity theft, fraud, etc.), as well as subjecting organizations to significant harm (e.g., legal penalties).

This webcast highlights common privacy principles and themes within key privacy regulations. In addition, the related cybersecurity implications are explored. Lastly, the session will probe a few of the recent regulations/laws to outline interesting challenges due to over and under-specification of data protection requirements (e.g., “reasonable” security).

After viewing this webcast, attendees should understand:
•How privacy and security is characterized
•Data retention and deletion requirements
•Core data protection requirements of sample privacy regulations from around the globe
•The role that security plays with key privacy regulations
•Data breach implications and consequences

After you watch the webcast, check out the Q&A blog: https://bit.ly/2FXnB3p

Storage Networking Security Series: Security & Privacy Regulations

Tools for speeding your implementation of the next-generation storage management standard

The SNIA Swordfish™ specification for the management of storage systems and data services is an extension of the DMTF Redfish® specification. Together, these specifications provide a unified approach for the management of servers and storage in converged, hyper-converged, hyperscale and cloud infrastructure environments.

To help speed your Swordfish development efforts, SNIA has produced open source storage management tools available now on GitHub for your use. Join this session for an overview of these open source tools, which include a Swordfish API Emulator, a Swordfish Basic Web Client, an example Swordfish plugin for the Microsoft Power BI business analytics service, and an example Swordfish plugin for the Datadog monitoring service.

SNIA Swordfish™ Swims in Open Waters

When it comes to storage, a byte is a byte is a byte, isn’t it? One of the enduring truths about simplicity is that scale makes everything hard, and with that comes complexity. And when we’re not processing the data, how do we store it and access it?
 
In this webcast, we will compare three types of data access: file, block and object storage, and the access methods that support them. Each has its own set of use cases, and advantages and disadvantages. Each provides simple to sophisticated management of the data, and each makes different demands on storage devices and programming technologies.
 
Perhaps you’re comfortable with block and file, but are interested in investigating the more recent class of object storage and access. Perhaps you’re happy with your understanding of objects, but would really like to understand files a bit better, and what advantages or disadvantages they have compared to each other. Or perhaps you want to understand how file, block and object are implemented on the underlying storage systems – and how one can be made to look like the other, depending on how the storage is accessed. Join us as we discuss and debate:

Storage devices
•How different types of storage drive different management & access solutions

Block
•Where everything is in fixed-size chunks
•SCSI and SCSI-based protocols, and how FC and iSCSI fit in

Files
•When everything is a stream of bytes
•NFS and SMB

Objects
•When everything is a blob
•HTTP, key value and RESTful interfaces

Altogether
•When files, blocks and objects collide

File vs. Block vs. Object Storage

In the storage world, NVMe™ is arguably the hottest thing going right now. Go to any storage conference – either vendor- or vendor-neutral, and you’ll see NVMe as the latest and greatest innovation. It stands to reason, then, that when you want to run NVMe over a network, you need to understand NVMe over Fabrics (NVMe-oF).

TCP – the long-standing mainstay of networking – is the newest transport technology to be approved by the NVM Express organization. This can mean really good things for storage and storage networking – but what are the tradeoffs?

In this webinar, the lead author of the NVMe/TCP specification, Sagi Grimberg, and J Metz, member of the SNIA and NVMe Boards of Directors, will discuss:
•What is NVMe/TCP
•How NVMe/TCP works
•What are the trade-offs?
•What should network administrators know?
•What kind of expectations are realistic?
•What technologies can make NVMe/TCP work better?
•And more…

After the webcast, check out the Q&A blog http://sniaesfblog.org/author-of-nvme-tcp-spec-answers-your-questions/

What NVMe™/TCP Means for Networked Storage

Join SSSI members and respected analysts Tom Coughlin and Jim Handy for a look into their new Emerging Memory and Storage Technologies Report.  Tom and Jim will examine emerging memory technologies and their interaction with standard memories, how a new memory layer improves computer performance, and the technical advantages and economies of scale that contribute to the enthusiasm for emerging memories.  They will provide an outlook on market projections and enabling and driving applications.  The webcast is the perfect preparation for the 2019 SNIA Persistent Memory Summit January 24, 2019.

Emerging Memory Poised to Explode

If you’re a storage equipment vendor, management software vendor or end-user of the ISO approved SNIA Storage Management Initiative Specification (SMI-S), you won’t want to miss this presentation. Enterprise storage industry expert Mike Walker will provide an overview of new indications, methods, properties and profiles of SMI-S 1.7 and the newly introduced version, SMI-S 1.8. If you haven’t yet made the jump to SMI-S 1.7, Walker will explain why it’s important to go directly to SMI-S 1.8.

Take the Leap to SNIA’s Storage Management Initiative Specification 1.8

We are going to discuss a case study on a unified data lake for the oil industry -- it is a software architecture and a set of microservices that are used to get business values from the data that are generated during the oil production. Math models were developed to make failure prediction of rod pumps during the oil artificial lifting.

We used modern capabilities of Big Data Architecture, based on Apache Spark set of technologies, machine learning, archived data, and streaming data from wells to build a unified math model to predict failure of that kind of industrial equipment.

Join this webinar to learn: 
-- How machine learning can help to predict failure of industrial equipment

-- Architecture to handle near real-time data-flow from oil wells

How Machine Learning Helps Predict Equipment Failure

machine learning

big data

apache

spark

data

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How Machine Learning Helps Predict Equipment Failure

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