Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-fl ash storage infrastructure that is built specifically to work with high-powered analytics.
To stay relevant in today’s competitive, digitally disruptive market, and to stay ahead of your competition, you have to do more than just store, extract, and analyze your data — you have to draw the true business value out of it. Fail to evolve, and your organization might be left behind as companies ramp up and speed up their competitive, decision-making environments. This means deploying cost-effective, energy-efficient solutions that allow you to quickly mine and analyze your data for valuable information, patterns, and trends, which in turn can enable you to make faster ad-hoc decisions, reduce risk, and drive innovation.
Expanding analytic capabilities are critical to digitizing the business, optimizing costs, accelerating innovation, and surviving digital disruption
Historically, manufacturers were almost solely focused on reducing costs by applying automation and analytics to engineering, R&D, manufacturing operations, and quality organizations. Even though the strategies used within these areas are still needed, they are not sufficient to ensure business survival and continuity in the age of Industry 4.0 and the IoT.
Today, it is paramount that smart manufacturers broaden their scope because disruptive innovations in data acquisition, storage, and analytics technology have enabled an entirely new degree of automation and virtualization, promising a complete 360-degree high-fidelity virtual data-driven integrated views of all operations—from suppliers and supply chains, through equipment, processes, and manufacturing practices, to final product testing and customer satisfaction.
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Deep learning opens up new worlds of possibility in artifi cial intelligence, enabled
by advances in computational capacity, the explosion in data, and the advent of
deep neural networks. But data is evolving quickly and legacy storage systems
are not keeping up. Advanced AI applications require a modern all-fl ash storage
infrastructure that is built specifically to work with high-powered analytics.
Digital technology has arguably been the biggest disruptor for individuals and organisations in the last twenty years. It has changed how we communicate, how we shop, how we spend our time and how we develop and grow our businesses. For businesses, digital has not just created new products and services, but fundamentally shifted business models and the dynamic between business and customer, business and supplier, business and employee. It has become a significant force for value and revenue creation, but one that brings with it many challenges.
Over time, hybrid cloud will increasingly become the mainstream deployment model for IT infrastructure. Flash storage brings with it many benefits necessary in hybrid cloud environments, and IDC already views it as a requirement for enterprise workloads that have any performance sensitivity. This IDC white paper discusses the state of enterprise storage with respect to the evolving cloud storage market, explains why flash storage is needed in these environments, and then discusses what Pure Storage, a leading all-flash array vendor, brings to the table in this area. The document concludes with a short service provider case study.
Storing data is critical. Everyone stores data. Today, it’s all about how you use the data you’re storing and if you’re storing the right data. The right mix of data and the ability to analyze it against all data types is driving markets worldwide in what is known as digital transformation.
Digital transformation requires storing, accessing, and analyzing all types of data as fast and efficiently as possible. The end goal is to derive insights and gain a competitive advantage by using those insights to move faster and deliver smarter products and services than your competition.
Businesses that exploit Big Data to improve strategy and execution are distancing themselves from competitors. The Big Data solution from EMC provides market-leading, scale-outing storage, a unified analytics platform, and business process and application development tools. Together, these allow organizations to draw deeper insights and become a more predictive organization.
Forward-looking enterprises know there's more to big data than strong and managing large volumes of information. Big data presents an opportunity to leverage analytics and experiment with all available data to derive value never before possible with traditional business intelligence and data warehouse platforms. Through a modern, big data platform that facilitates self-service and collaborative analytics across all data, organizations become more agile and are able to innovate in new ways.
While the concept of big data is nothing new, the tools and technology and now in place for companies of all types and sizes to take full advantage. Enterprises in industries such as media, entertainment, and research and development have long been dealing with data in large volumes and unstructured formats - data that changes in near real time. However, extracting meaning from this data has been prohibitive, often requiring custom-built, expensive technology. Now, thanks to advancements in storage and analytics, all organizations can leverage big data to gain the insight needed to make their businesses more agile, innovative, and competitive.
Competitive enterprises that embark on big data strategies do so with the expectation that their businesses will transform. They don't just want answers from the data they collect and analyze, they want results. Be it with small, fledgling trials or large, cross-functional efforts, these enterprises want to see clearly how big data can make a difference - with their customers, their processes, their bottom lines and, most important, with growing the business.
Download this eBook to learn the steps you can take now to prepare for the all flash data center.
flash storage, SSD, all flash data centers, nimble storage, predictive flash platform, application perfomance, data velocity
Published By: Dell EMC
Published Date: May 15, 2015
This Wikibon research shows that flash will become the lowest cost media for almost all storage from 2016 and beyond, and that a shared data philosophy is required to maximize the potential from both storage cost and application functionality perspectives.
With the increasing mainstream adoption of big data infrastructure — highly distributed file storage and query tools — more businesses are taking a new look at what business intelligence and analytics can do to grow revenue, increase profits and ultimately develop strategic relationships with customers.
Published By: Cohesity
Published Date: Oct 02, 2018
The University of California, Santa Barbara (UCSB) is a public research university and one of the 10 campuses of the University of California system. Its secondary storage was a combination of multiple point solutions. The UI/setup and maintenance was complex. Maintaining multiple licensing and maintenance agreements negatively impacted the administrative cost. The skyrocketing cost for additional backup capacity limited the team’s ability to expand their backup protection to many critical systems. With Cohesity's unified hyperconverged secondary storage platform, the IT team provided a single solution for all 13 departments to consolidate their backups on one platform, and scale-out as required. Read the case study and get details on how UCSB consolidated everything from backup to recovery, analytics to
monitoring and alerting.
Today’s organizations are tasked with managing multiple data types, coming from a wide variety of sources. Faced with massive volumes and heterogeneous types of data, organizations are finding that in order to deliver insights in a timely manner, they need a data storage and analytics solution that offers more agility and flexibility than traditional data management systems.
Data Lakes are a new and increasingly popular way to store and analyse data that addresses many of these challenges. Data Lakes allow an organization to store all of their data, structured and unstructured, in one, centralized repository.
Published By: Teradata
Published Date: May 02, 2017
As companies consider incorporating enterprise-level cloud services offered by Amazon Web Services, Microsoft Azure, Teradata, and others, many challenges arise related to data security, integration into existing data architecture, and analytics activities themselves.
Download this article to understand these and other considerations for evaluating and adopting a cloud strategy for your enterprise, and what it means for analytics.
Apache® Spark™ has become a vital technology for
development teams looking to leverage an ultrafast
in-memory data engine for big data analytics. Spark
is a flexible open-source platform, letting developers
write applications in Java, Scala, Python or R. With
Spark, development teams can accelerate analytics
applications by orders of magnitude
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics.
For more than a decade, Oracle has developed and enhanced its ZFS Storage Appliance, giving its users a formidable unified and enterprise-grade storage offering. The latest release, ZS7-2, boasts upgraded hardware and software and is a timely reminder that more users might do well to evaluate this offering. It has a trifecta of advantages:
(1) It’s notable performance, price-performance, and flexibility are all improved in this new release
(2) There is a surprisingly inclusive set of functionalities, including excellent storage analytics that were developed even before analytics became a contemporary “must-have”
(3) There’s a compelling group of “better together” elements that make ZFS Storage Appliance a particularly attractive choice for both Oracle Database environments and users that want
to seamlessly integrate a cloud component into their IT infrastructure.
Given the proven abilities of Oracle’s prior models, it’s also safe to assume that the new ZS7-2 will outperform other m
ESG Whitepaper: New security risks and old security challenges often overwhelm legacy security controls and analytical tools. This ESG white paper discusses why today's approach to security management—that depends on up-to-the-minute situational awareness and real-time security intelligence—means organizations are entering the era of big data security analytics.
“Vestas is a global market leader in manufacturing and servicing wind turbines,” explains Sven Jesper Knudsen, Ph.D., senior data scientist. “Turbines provide a lot of data, and we analyze that data, adapt to changing needs, and work to create a best-in-class wind energy solution that provides the lowest cost of energy.
“To stay ahead, we have created huge stacks of technologies—massive amounts of data storage and technologies to transform data with analytics. That comes at a cost. It requires maintenance and highly skilled personnel, and we simply couldn’t keep up. The market had matured, and to stay ahead we needed a new platform.
“If we couldn’t deliver on time, we would let users and the whole business down, and start to lose a lot of money on service. For example, if we couldn’t deliver a risk report on time, decisions would be made without actually understanding the risk landscape.
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.