Career As a Data Scientist: Job Roles and Other Important Details

Dell EMC allows an associate certification in data science. The exam focuses on the practice of data analytics, the part of a data scientist, Data Analytics lifecycle, analyzing and exploring data with R, statistics for model building and evaluation, theory and techniques of advanced analytics and statistical modeling, technology and tools that can be used for advanced analytics, operationalizing an analytics project, and data visualization techniques.

These certifications are delivered by Dell EMC, the official certifications. Dell EMC certification equips you with various enterprise data storage skills and enhances your VNX Storage and development knowledge. Amongst all others, the Dell EMC certification requirements suite comprises Symmetrix Business Continuity Management, Symmetrix Configuration Management with FAST VP, Dell EMC Avamar Administration, Installation and Configuration, Dell EMC Data Domain System Administration, Dell EMC NetWorker Administration for UNIX and Microsoft Windows, VNX Unified Storage Deployment and Management, Data Science and Big Data Analytics and much more. The Dell EMC requirements at Koenig are mapped to several famous Dell EMC certifications.

Why Learn Data Science?

With the amount of data generated and the evolution in analytics, Data Science has become a necessity for companies. To make the most out of their data, companies from all domains, be it Finance, Marketing, Retail, IT, or Bank. All are looking for Data Scientists. This has led to a massive demand for Data Scientists all over the globe. With the kind of salary that a company offers and IBM is declaring it a trending job of the 21st century, it is a lucrative job for many. This field is such that anyone from any background can make a career as a Data Scientist.

The program needs no prior knowledge of coding in Python, R, or SQL and begins from fundamentals. By the end of the program, the candidates will have a deep understanding of statistical techniques critical to data analysis. They can create Analytical models using real-life data to drive business impact.

Data science is the skill and technology that every industry is craving. Having a data science skillset in the current era means having an excellent demanding career option in your pocket.

Certifications are the best means of proving that you understand something in a particular field. Data Science and Analysis career paths and certifications are directly proportional to each other. These certificates are in high demand in the industry. It will add a striking star to your profile and will certainly pay off.

What Do Data Scientists Do?

The data scientist is an individual who can give tremendous value by tackling more open-ended questions and leveraging their understanding of advanced statistics and algorithms. If the analyst focuses on intelligence data from the past and present perspectives, the scientist focuses on producing good predictions for the future.

The data scientist will uncover deep insights by leveraging both supervised approaches toward their machine learning models. They are training mathematical models that will allow them to identify patterns better and derive accurate predictions.

The tracking is examples of work performed by data scientists:

• Evaluating statistical models to determine the legality of analyses.
• Using machine learning to build better imminent algorithms.
• Testing and continuously improving the effectiveness of machine learning models.
• Building data visualizations to compile the conclusion of advanced analysis.

Data scientists bring an entirely new path and perspective to understanding data. While an analyst may describe trends and translate those results into business terms, the scientist will raise further questions and build models to make predictions based on new data.

How Much Money Do Data Scientists Make?

Data science salaries can differ quite a lot since the role itself differs from company to company. According to Indeed.com, as of April 2021, the average data scientist in the United States receives $121,050.

Experienced data scientists at top companies can make significantly more senior data analysts at companies such as reported salaries of around $178,000 as of April 2021.

Data scientists who concentrate on building machine learning skills can also look at machine learning engineer roles, which require an average yearly salary of $149,924 in the United States as of April 2021.

Summary

Finally, the data scientist will likely build upon the analyst’s initial decisions and research to obtain deeper insights. Whether by training machine learning models or by continuing advanced statistical analyses, the data scientist will provide a brand new prospect into not just what has occurred in the past but what may be possible for the near future.

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Driving Innovations in Genome Sequencing

One of the greatest challenges for innovative organizations wanting to stay on the leading edge is, frankly put, to get out of their own way.

Consider the Wellcome Sanger Institute, a British genomics and genetics research organization. The Sanger Institute assists companies leading scientific discovery and innovation around the world by providing reliable and performant access to biomedical research data.

Biomedical research data is some of the most complex data on the planet. For example, sequencing human DNA requires tracking more than 6.4 billion base pairs. The human genome was first sequenced in 2003. Sequencing the genome was just the tip of the iceberg as numerous discoveries made possible by genomics research have fundamentally changed the quality of life across the planet. A method of sequencing known as next-generation sequencing (NGS), enables new research and applications that have never before been possible. Researchers are able to accelerate drug discoveries, as we have recently seen with COVID-19 vaccine research. In the long term, clinical genomics will become more common place enabling the practice of precision medicine.

Gene sequencing and other biomedical research is a large-scale processing challenge. The problem is that many organizations continue to implement technology and architectures that they are familiar with. To stay at the leading edge, however, requires letting go of “the way things are done.” By its definition, innovation means thinking in new ways that supersede existing models and paradigms. In short, next-generation applications need next-generation technology.

And that’s what Sanger delivers to its partners.

The Problem of Large-Scale, Unstructured Data

Gene sequencing is similar to other applications that need to process large-scale, unstructured data. With sequencing, a common workflow is the analysis and identification of variants associated with a specific trait or population. Captured data is encoded into a FASTQ file. The FASTQ format was originally developed at the Sanger Institute and has since become the de facto standard for storing the output of high-throughput sequencing systems such as the Illumina Genome Analyzer.

A large-scale, unstructured data application like gene sequencing analyzes data in several stages. At each stage, data needs to be mapped and aligned so the varying workflows can access the data quickly and efficiently.

Secondary analysis is then performed for mapping, alignment, and variant calling. In the tertiary analysis, researchers then directly apply biological, clinical, and lab data to stored genome sequencing data.

The overall challenge researchers face when working with large-scale, unstructured data is enabling rapid analysis at all stages of the process. Three common ways to improve analysis speed are to add more processing cores, rewrite analysis software to be more efficient, and utilize hardware acceleration. The Sanger Institute implemented cloud and on-premise GPU-based hardware accelerators for higher performance computing during initial analysis of genome data while the implementation of high performance computing clusters sped operations for running the entire analysis chain.

Core to being able to deliver rapid analysis is the fast and efficient management of petabytes of data in a cost-effective manner. The data life cycle for sequencing is to generate the data, analyze it, and then archive it. For the highest efficiency, managing the data life cycle needs to be as seamless and hands-off as possible.

Unstructured Data Solutions Powered by High-performance, Scale-Out Storage

To address varying storage performance requirements, Dell Technologies offers All-Flash arrays like the Dell EMC PowerScale F600 and F200 All-Flash systems for fast access and high reliability. This is while hybrid arrays like Dell EMC Isilon H4500/H500/H5600/H600 and A200/A2000 are typically utilized as cost-effective storage and archiving. These devices offer performance, scalability, and high throughput, so they are never a bottleneck in a sequencing environment. PowerScale also features innovative OneFS technology, a software-defined architecture that enhances development agility, provides use case flexibility, and accelerates innovation.

With PowerScale, the Wellcome Sanger Institute has been able to scale and upgrade its storage without sacrificing simplicity. The migration-free design of PowerScale with its auto-discover capabilities means new nodes can be added in literally a minute while legacy nodes can be decommissioned with no downtime. Auto balancing ensures that as storage scales out, there are no “hot spots” that can create processing constriction. In this way, the Sanger Institute is able to introduce next-generation storage technology as it becomes available. In turn, its partners can immediately leverage higher levels of efficiency in their research.

PowerScale’s native support of the S3 protocol greatly simplifies management of petabytes of data. Sanger can access cluster file-based data as objects so that traditional NAS and emerging object storage can be used together transparently. The result is a cost-effective unstructured data storage solution with enhanced data-lake capabilities that enable file and object access on the same platform. Features include bucket and object operations, security implementations, and a single integrated management interface. In this way, all data can be simultaneously read and written through any protocol. Efficiency is improved through inline data reduction capabilities, as well as by eliminating the need to migrate and copy data to/from a secondary source.

There are many other benefits for the Wellcome Sanger Institute beyond higher performance and simplified data management. For example, flexible file and object access, combined with a software-defined architecture, means that data is available everywhere it needs to be in the analysis chain, extending from the edge to the cloud. Storage is also DevOps ready, meaning developers can utilize new Ansible and Kubernetes integrations when they are available. PowerScale is resilient as well: A system can sustain multiple node failures without disrupting operations, thus eliminating downtime.

Continuous Improvement

Especially important for driving forward efficiency is the ability of PowerScale to provide intelligent insights into data, infrastructure, and operations. Dell Technology’s CloudIQ combines machine intelligence and human intelligence to give administrators the insights they need to be able to efficiently manage their Dell EMC infrastructure. In addition, CloudIQ provides alerts to potential issues so IT can take quick action and minimize any disruption to service.

DataIQ is another important technology for maximizing efficiency when working with large-scale, unstructured data. Improving efficiency is an ongoing process. By providing a unified file system view of PowerScale, ECS, third-party platforms, and the cloud, DataIQ makes it possible to draw unique insights into how data is used and overall storage system health. DataIQ also empowers users to identity, classify, and move data between heterogeneous storage systems and the cloud on demand.

The Wellcome Sanger Institute is helping to change the world. And they’ve achieved this by changing how they manage their data. PowerScale has enabled Sanger Institute to unlock the potential within their partners’ research. True multiprotocol support allows them to access any data, anywhere from the edge to the cloud. Simple non-disruptive scaling allows them to optimize for ever-changing efficiency, bandwidth, and capacity needs. And intelligent insights into infrastructure and data enable them to continuously improve their operations.

Source: delltechnologies.com

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Keeping Culture and Innovation Alive in Our Hometown

Thirty-seven years ago, Michael Dell founded Dell Technologies in a small University of Texas at Austin dorm room. Big dreams led to even bigger realities and over the years, we’re fortunate to have seen the city grow right alongside our business. Austin’s unique culture has also come into its own, making it a melting pot for artists, creative, and technology innovators alike.

It comes as no surprise then that Forbes recently ranked Austin as the number one “boomtown” in the U.S. Just this past year, 154 companies announced plans to relocate or expand their presence in the area. We’re beyond thrilled to welcome our new neighbors and peers to our hometown and see Austin become the top destination to live and work.

But with all this growth comes a responsibility to do what we can to collectively preserve the unique spirit and culture that make Austin such a special place. No, I’m not just talking about the love of the outdoors or our sincere adoration for queso – I’m talking about our commitment to evolving and growing the best that the greater Austin area has to offer – our collective innovative spirit. At the end of the day, what sets Austin apart is our never-ending desire to innovate – from tech, to music, to entertainment, to sports. It’s that innovative spirit that we need to proactively cultivate in the years to come, especially as we work to overcome the impacts 2020 has had on our city.

Today, we’re excited to announce Dell Technologies will be the Premier Founding Partner of the new Moody Center, a multi-purpose, state-of-the-art venue which will replace the 42-year-old Frank C. Erwin Jr. Center at The University of Texas. The venue promises to bring together the best in Austin culture, arts, entertainment, and sports – serving as the new homecourt of the Texas Longhorns women’s and men’s basketball teams and becoming a premier concert venue in our city.

To us, this is so much more than just a sponsorship – our involvement is a symbol of our commitment to our community and our mission to not just preserve – but evolve and grow – the very things that have made Austin, Austin.

A few other reasons we’re excited about the Moody Center and its impact on the city:

◉ A Space for All: Equity is fundamental to the building’s infrastructure with seats on all concourses lending itself to a great experience. Additionally, the newly built exterior Dell Technologies Plaza will become an entertainment destination of its own hosting post-game shows and community events year-round.

◉ Engaging the Next Generation of austenite's: Austin’s future is only as promising as today’s youth. In an effort to keep the next generation of sports enthusiasts engaged in college athletics, Dell will be donating tickets to Longhorns basketball games for the 2022 season to the Boys & Girls Club of the Austin Area – giving the leaders of tomorrow the ability to experience the magic and fun first-hand.

◉ Green is Gold at Moody: Preserving our environment is a key shared priority for both Dell Technologies and the city of Austin. As we celebrate Earth Day today, I’m happy to share the Moody Center has been designed and developed with sustainability in mind and is on track to receive a LEED Gold certification.

◉ Helping Live Music Thrive: Maintaining Austin’s status as the Live Music Capital of the World, the Moody Center will be home to top concert tours and international music shows from some of the world’s biggest artists.

So, who’s going to help us continue this momentum? We’re happy to share that Chris Ogbonnaya has recently joined our team to manage the partnership. Chris played college football at the University of Texas before heading to the NFL, then heading back to Longhorn country to earn his MBA. We’re excited to have someone with deep Texas roots help bring our long-term vision for our Moody Center partnership to life.

Propelling Austin into the future deserves a shared commitment from leaders across the city. Later today, I’ll be leading a discussion with key individuals with deep Austin roots – Matthew McConaughey; Emmanuel Acho; Charles Attal, Partner C3 Presents; Jody Conradt, special assistant and former UT Women’s Basketball Coach; and Chris Del Conte, UT Vice President and Director of Athletics – to discuss the city’s future and how we come together to drive progress.

There’s no slowing down the growth we’re experiencing here in Austin. What we can do is come together as a community to collectively preserve the very things we love about Austin while helping to drive new ideas and lead the city into its next chapter. As we do so, let’s remember to keep Austin weird…and innovative!

Source: delltechnologies.com

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OEMs – Preview the Future at Dell Technologies World

I wrote about how OEM Solutions enable human progress and how we work together, supported by partners like Intel, to change our world for the better. OEMs are visionaries and pioneers in embracing key technologies and adapting to emerging trends, which is precisely why you should sign up now to attend the premier event of the year — Dell Technologies World.

Join us at Dell Technologies World

Taking place on May 5th and 6th, this free, virtual event is accessible from anywhere. For our OEM customers and partners, this event will showcase emerging technologies, the latest product announcements, a multitude of topical breakout sessions, special guests, keynotes, guru sessions, interactive demos, lab sessions, and live Q&As with industry experts. Plus, we have some amazing entertainment in store!

Edge and OEM content

OEMs are at the forefront in using edge computing to drive digital transformation, which is helping to redefine many industries, opening up new business models and driving innovation. This transformation is generating a host of business opportunities with IDC predicting that the Edge computing market will reach $250.6 billion by 2024.

Recognizing the critical importance of the edge, there are a number of sessions you won’t want to miss. In particular, a dedicated OEM session, featuring John Green, our Global VP of OEM Sales Engineering and Alan Brumley, our Global OEM CTO on the topic of Designing Industry-grade Platforms for Performance and Remote Management at the Edge.

This session is one of many that we think you’ll find relevant to your solution development. In addition, we’ve also setup an OEM specific landing page that links to edge and OEM content as well as a curated list of product and technology topics, which will bring you the latest on servers, storage, AI and more.

APEX – the game-changer

I also encourage you to learn more about Project APEX, another transformative technology and business game changer. APEX unites all Dell Technologies as-a-service and cloud strategies, technology offerings, and go-to-market efforts to provide a consistent experience, wherever a workload runs, including on-premises, at the edge or in public clouds.

According to IDC, by 2024, more than 75 percent of infrastructure at the edge and over 50 percent of all data center infrastructure will be consumed as a service. APEX will simplify digital transformation, making it easier for customers and partners to access Dell technology on-demand – across storage, servers, networking, hyperconverged, and broader solutions.

Moving forward together

Increasing edge computing and as-a-service demands will accelerate the need for the right compute, connectivity and storage as well as more flexible hardware and software platforms for our OEM customers and partners. Dell Technologies World will prepare you to harness the transformative power of today’s technology – and be ready for whatever comes next. Discover the latest products and solutions that enable real digital transformation. Don’t miss it!

Source: delltechnologies.com

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AI Market Forces, Data Strategy and Data Governance

Artificial Intelligence is taking over the world, changing our lives and pushing boundaries. AI is indeed now smarter and embedded in more and more devices, such as toothbrushes, refrigerators, and thermostats, than ever before. But what’s next? How about a smart toilet that provides a rapid, daily health check and screening readout! Now, this may sound like an extreme example of TMI (too much information) but consider the positive implications.

In a way, it makes total sense, as using the toilet daily is something that we humans all have in common. And it happens to result in a great deal of available data that AI could use to improve healthcare outcomes while empowering us to make better, healthier choices in the way we live and the food we eat. A perfect and unique example of AI technology helping humanity at scale. So no, your toilet will not read the newspaper to you, but it may become an even more integral part of your daily healthy living regimens.

Data Strategy

In addition to new, enhanced compute, storage and networking technologies, many significant advances in AI are made possible by data. The more data created, the more needed, resulting in a virtuous loop of asset creation. Data just keeps coming and you need to act on it methodically with a data strategy.

Data strategies follow business strategies. If your business strategy is solid, then developing a data strategy is the next logical step in adopting AI. But how do you treat data as the strategic asset that really drives the business, that sets you on the path to capitalize on it?

First, don’t just start AI pilots in search of quick outcomes: think strategically of possible use cases. How do we use data to deliver new customer value propositions and new innovations? How do we use it to make smarter products and services? Next, consider using AI and Data Analytics to drive efficiencies in operations and business processes, thus streamlining your organization for the future. This dual-pronged approach is an effective way to get started.

Moving Beyond Pilots

Of course, businesses exist to create value and drive profits, so AI initiatives must move quickly and effectively beyond pilots to profitability. Therefore, it’s crucial to align business strategy with data strategy, not only to streamline the business, but also to set up for the delivery of smart products and services. At this point in the digital transformation of society, all businesses must ultimately deliver smarter offerings, or they will end up in the dustbin of history.

We’ve touched on how applying a data strategy can wield significant benefits, both in new, smarter products and services development, as well as in streamlining operations. However, it’s not an all or nothing proposition. AI can deliver incremental steps in the journey to your smarter products and/or services.

Think for instance of the future vision of self-driving cars. We’re not there yet, but the safety measures brought by work in the autonomous driving space are already here and standard on most new vehicles. Consider features such as lane keeping assist, or automatic braking for collision avoidance. These safety enhancements are significant and serve to prepare us all for the day that our cars will automatically and safely drive us anywhere without us touching a steering wheel!

The Importance of Data Governance: Doing Good

Competitiveness and delivering an enhanced customer experience using AI is just the tip of the iceberg. The emergence and broader adoption of AI is arguably the most important technological advance of this generation, thanks in large part to the increasing power of the compute, storage and networking systems underlying it, not to mention the billions of smart devices and IoT sensors proliferating around the globe, leading to amassing swells of data. But caution is in order.

Doing good for humanity is a key altruistic underpinning of historical technology advances. Therefore, data strategy goes hand in hand with data governance. All organizations need to adhere to numerous data privacy and security frameworks, so it’s critical to have a clear ethical stance when it comes to AI: the data used for, and generated, by it. Lack of clear standards here can result in penalties and fines, but also in the loss of customer trust.

And it can have serious ripple effects across entire industries. Retaining clear ethical standards in the use of AI, having ethics integrated into processes, is the best way to avoid issues such as bias.

We need to be as cognizant of these societal ramifications as we are of those for business. We will need more focus on ethics, reducing biases and making AI decisions more explainable. Therefore, keeping humans in the loop, via ethics panels, stronger regulatory frameworks, and real-time monitoring, will be critical for the continued positive adoption of AI. And the good of our society and planet.

Source: delltechnologies.com

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Dell Technologies Making Open RAN Happen

True innovation is never an individual achievement. Imagine, for example, if no one had followed Henry Ford into the automotive industry.

No, innovation is an evolution fueled by competitive forces and multiple perspectives. 5G will be no exception. 5G service providers can’t wait for one or two companies to solve the challenges of tomorrow, whether it’s building out 5G radio access networks (RAN) or creating the next generation of mobile services such as virtual reality gaming or autonomous vehicles. In recognition of this, the telecommunications industry is “opening up” the traditionally closed RAN world. Virtualization, clouds, and containers have brought a new world of innovation to the mobile core network. Now that innovation is extending to the network edge, multi-access edge computing (MEC), and Open RAN.

Open RAN is a highly flexible, highly scalable architecture that allows mobile operators to deploy RAN and edge infrastructure using virtualized and decentralized components. Open RAN solutions completely change the economics and the time to innovation for 5G network services. Open RAN solutions enable mobile operators to choose which vendors to deploy in their network while providing more options to scale-out RAN resources where they are needed and in precisely the right amounts.

Open RAN Opens Up New Possibilities

Open RAN brings game-changing benefits to MNOs as they look to build out their 5G networks and create new revenue-generating services:

1. Supplier Choice

Open RAN solutions should be just that, open, whether it’s supporting open standards or being open to innovative ideas from visionary partners. Open architectures provide operators with options to choose whom they want to work with for the various RAN functions. It gives operators choice and flexibility and provides an attractive path to deploying best-of-breed solutions offered by many innovative RAN players, small or big.

2. Service differentiation

Time-to-market for new services is critical to 5G revenue generation, but what happens if your RAN vendor can’t support the new services you have planned? In effect, the RAN vendor now becomes the chokepoint for innovation, limiting what can be done and when. Open RAN solutions bring a world of innovation to the table beyond traditional telecommunications vendors, allowing MNOs to tap into automation, AI, big data, cloud computing, and more. 

3. Flexible deployment options

Virtualizing the RAN enables new centralized and decentralized deployment models that provide operators with flexibility regarding where to deploy the distributed unit (DU) and centralized unit (CU). This allows operators to determine the most cost-effective and scalable deployment models.

4. A more secure supply chain

Telcos have long understood the value of a failsafe architecture, but what about a failsafe supply chain? If your proprietary RAN vendor experiences a supply chain issue or, worse, goes out of business, the alternative isn’t as simple as turning to another proprietary RAN vendor.  With an Open RAN architecture, MNOs have more choices and can buy RAN solutions from a wide field of vendors much as they do for compute or storage, which brings us to the supply chain.

Open RAN Solutions from Dell Technologies

The telecom industry has been discussing the above challenges and Open RAN’s value for some time now. Few companies understand the importance of being open as well as Dell Technologies. No one partner can solve every problem, but they can help you find solutions. At Dell, that means bringing the right partners together to create a unique solution, aiding in the deployment of new RAN equipment, or providing turnkey services so that operators can focus on their customers.

Dell Technologies is stepping up to fill that gap in the industry by joining forces with other leading technology vendors to deliver Open RAN solutions to MNOs worldwide. As part of our commitment to drive rapid adoption of 5G, we’ve put our resources and relationships to work to improve the total cost of ownership of RAN equipment, accelerate RAN innovation through automation and cloudification, and support the creation of exciting new 5G services. We are committed to new telco-grade servers and solutions that address the need for an open, scalable, flexible, and rapidly deployable RAN in a wide variety of environments.

Source: delltechnologies.com

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Unlocking the Power of AI

At VMworld 2020, NVIDIA and VMware shared their vision to work together to democratize and unleash AI for every enterprise. And that’s the case today as the companies roll out a jointly engineered solution that optimizes the latest update to VMware vSphere 7 — for AI applications with the NVIDIA AI Enterprise software suite on Dell Technologies.

The combination of technologies from these world-class companies makes it easier to access a rich menu of accelerated parallel-computing applications, AI frameworks, models and software development kits (SDKs). It gives AI researchers, data scientists and developers the software they need to deliver successful AI projects, while arming IT professionals with the ability to support AI using the tools they’re most familiar with for managing data centers and hybrid cloud environments.

Democratizing AI with VMware

VMware vSphere 7 Update 2 delivers powerful support for the latest NVIDIA A100 and new A30 GPUs, including enhancements to performance-boosting GPUDirect communications and new multi-instance GPU (MIG) partitioning. vSphere also delivers enterprise virtualization for GPU-powered AI workloads. And, vSphere is the only virtualization platform that enables vMotion for NVIDIA vGPU powered VMs, simplifying infrastructure maintenance while powering VMware Distributed Resource Scheduler for automatic initial workload placement for AI infrastructure at scale.

Boosting efficiency with NVIDIA AI Enterprise

NVIDIA AI Enterprise encompasses a suite of enterprise-grade AI applications and models that are designed to optimize business processes and boost efficiency for AI use cases across industries — from manufacturing and logistics to financial services, retail, healthcare and more. It gives users easy access to NVIDIA tools that power AI development across projects as diverse as smart factories, healthcare diagnostics and fraud detection.

And forget about AI silos. With NVIDIA AI Enterprise running on vSphere, organizations can avoid silos of AI-specific systems that create management headaches and security risks. With this combination of technologies, organizations can overcome the challenges that stem from deploying individual AI applications, as well as the potential failures that can result from having to manually provision and manage different applications and infrastructure software.

It’s Suite and Certified

Using the NVIDIA AI Enterprise suite and NVIDIA’s most advanced GPUs and data processing units (DPUs) in accelerated servers, enterprises using  vSphere for server virtualization can now more easily run accelerated AI workloads alongside existing enterprise applications on Dell Technologies-NVIDIA Certified Systems, with near-bare-metal performance.

Harnessing the power of AI with Dell Technologies

At Dell Technologies, we’re excited to see the rollout of NVIDIA AI Enterprise for vSphere on Dell EMC PowerEdge servers with NVIDIA A100 Tensor Core GPUs. That’s a point that is apparent in a comment from Caitlin Gordon, vice president, product management, Dell Technologies Infrastructure Solutions, in a VMware launch news release.

“Dell Technologies is focused on helping customers harness the power of AI by providing solutions that make it easier to adopt and use,” she notes. “Today’s news certifying NVIDIA AI Enterprise with VMware vSphere supports our efforts with both companies to provide NVIDIA A100-powered Dell systems that enable customers to benefit from AI anywhere, with continuous insights at scale, to help reach their business goals.”

It was this same spirit that led to Dell Technologies becoming the first IT company to embrace innovation that helps businesses run powerful AI workloads in VMware environments, via easy-to-deploy Dell EMC Ready Solutions. As noted in a Dell Technologies news release, new Dell EMC Ready Solutions based on VMware Cloud Foundation help companies gain AI insights with the combination of Dell EMC systems and features of VMware vSphere to enable GPU virtualization.

Key takeaways

As organizations work to capitalize on the massive amounts of data they collect every day, AI is emerging as one of the most important enterprise applications — if not the most important application. It’s an essential ingredient to digital transformation and the move to the data-driven enterprise.

To enable this shift, organizations are using VMware to maintain consistent operations and governance for their multi-cloud environments, while providing automation capabilities to modernize their applications. For AI, teams previously had to use a different set of tools, however, now, AI applications can be easily managed with the same VMware flexibility as their other applications. The result: It’s easier than ever to develop, deploy and manage diverse AI workloads anywhere.

Source: delltechnologies.com

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Making Smarter, Faster Trades with AI and HPC

In the new digital economy, data and the IT solutions used to harness it are often a financial services company’s primary source of competitive advantage. This is especially true for algorithmic trading, a highly automated investment process where humans train powerful software applications to select investments and implement trades automatically.

Also Read: DEA-2TT3: Cloud Infrastructure and Services Version 3 Exam (DECA-CIS)

The ultimate evolution of algorithmic trading is high‑frequency trading, where the algorithms make split‑second trading decisions designed to maximize financial returns. Automating trading and removing humans from the hands-on process has several advantages, including reduced costs, greater speed and improved accuracy.

High‑frequency trading platforms deliver competitive advantage through their ability to place thousands of trades before the market can react. Given this new reality for the industry, high‑frequency trading has led to competition in computational speed, automated decision making, and even connectivity to the execution venue to shave off microseconds and beat other traders to opportunities.

In light of these compelling business benefits, it’s no surprise that algorithmic trading is becoming more the norm than the exception for financial trading firms.

Developing the algorithms

To develop trading algorithms, financial firms typically leverage a proprietary mix of data science, statistics, risk analysis capabilities and DevOps processes. Then the algorithm is tested against historical data and refined until it produces the desired profits. The algorithm is then put into production, making trades in real time on behalf of the firm. The real‑world yields produced by the algorithm generate even more data, which is used to continually train the algorithm and improve its performance.

This training feedback loop is a data‑intensive process that often includes machine learning, a subset of artificial intelligence. Developers leverage machine learning techniques to improve predictive capabilities, using deep neural networks to find trends that trigger buy or sell decisions.

This is a never-ending cyclical process. Financial trading firms are continually developing, implementing and perfecting algorithmic trading strategies to stay a step ahead of the competition. This puts significant stress on infrastructure because the algorithm must continuously adapt to new input to remain relevant. As such, the back‑end infrastructure must make accommodations for live‑data feeds and the quick processing of large amounts of data. Databases, in turn, must be able to feed the compute engine in real or near‑real time to update the algorithm.

The data‑intensive training requirements and the need for high speed and low latency mean that these sophisticated algorithms are typically trained and run on high performance computing systems to provide the speed and accuracy required to dominate the market. An HPC system that supports algorithmic trading should be able to accommodate current workloads seamlessly and provide the flexibility, performance and scaling needed to continually train and update algorithms to help firms stay ahead of the market.

The power of partnerships

The realities of today’s algorithmic trading processes, including model development, dictate that financial firms form close partnerships with technology providers who have the breadth of products and the technical expertise to build systems that span from the edge to the cloud to the core data center.

Working together, Dell Technologies and NVIDIA provide integrated and successful builds for GPU‑enabled solutions for the financial services industry. These jointly engineered solutions leverage NVIDIA GPUs, which are the accelerator of choice for algorithmic trading since they have obvious logic for parallelizing computing streams with straightforward code development and mature numerical libraries.

For a quick route forward, NVIDIA GPUs are available in solutions based on the Dell EMC HPC Ready Solution for AI and Data Analytics. This system provides high-level guidance for building a converged architecture that allows organizations to run HPC, AI, and data analytics workloads on a single infrastructure.

And for firms that are looking to gain experience with new AI and HPC solutions, Dell Technologies offers the resources of its HPC & AI Innovation Lab in Austin, Texas. This 13,000 square foot data center houses thousands of servers, a TOP500 cluster, and a wide range of storage and network systems. The lab offers products from NVIDIA, Intel, AMD and other technology leaders to allow IT teams to test applications and gain hands-on experience with the latest and greatest technologies.

Source: delltechnologies.com

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The PowerEdge XE7100 Significantly Improves Scalability and Efficiency

Nothing seems to grow faster than the need for storage. With IoT, image, and video objects feeding “big data” analytics systems, that growth curve can be steep as new systems are placed online. Dell Technologies has engineered its latest storage server with a focus on high-density, high-capacity storage customers.

Recently, Dell Technologies commissioned Tolly to study the specifications and characteristics of its Dell EMC PowerEdge XE7100 and provide analysis and context as to where the device sits in terms of advancing the industry.

Tolly found that the Dell EMC PowerEdge XE7100 Storage Server provides significant scalability and efficiency benefits both compared to prior generation systems and compared to current generation systems of a leading competitor. Significantly, the unit provides module server sled options that allow for high-performance optimization for specific application focus areas such storage/archival, intelligent video analysis (IVA), and media streaming.

Our analysis contrasted the Dell EMC PowerEdge with the specifications of a leading competitor. As you shall see, the Dell EMC PowerEdge XE7100 showed significant scalability benefits as well as significant efficiency advantages. As we say in the report, “More is more… and less is more” – the benefits are manifold.

Scalability

Let’s start with scalability. The Dell EMC XE7100 supports 100 disks in total. It is top-loading with rows of mostly 15 disks per row. That capacity is 67% greater than a leading competitor. Filling a 42U rack with eight of the 5U Dell EMC PowerEdge XE7100 units gives you 800 disk drives in a single, STANDARD-size rack.  Some storage providers require racks with unusual dimensions.  Such racks can cause complexity in the data center and reduce physical space available between rows of racks.

So, it is important to note that using a standard-size rack, the number of drives supported per rack with the Dell EMC PowerEdge XE7100 is 33% greater than a leading competitor.  The units now support 18TB drives and this provides for a massive 14.4 Petabytes of storage in a single rack.

Efficiency

Now on to efficiency… Where many storage servers are 4U, the fact that the Dell EMC PowerEdge XE7100 is 5U provides additional efficiency at the rack level. That is, eight units of the Dell EMC PowerEdge XE7100 fill a 42U rack where it would require 10 units of a 4U storage server to fill the rack.

And the efficiency of the Dell EMC XE7100 extends to its power and cabling requirements as well. Dell Technologies has optimized power supplies and the cabling that goes along with power. And, because fewer units are required to fill a rack, that benefits of that optimization extend beyond the unit to the rack overall.

Where a leading competitor requires four 1600W power supplies per unit, the Dell EMC PowerEdge XE7100 requires only two 2400W power supplies which reduces cabling complexity, allows the user to optimize expensive infrastructure items like power distribution units (PDUs) and reduces energy consumption.

At the unit level, that is a 50% reduction in power supplies required that, at a rack level, is a 60% reduction in power cables. Dell EMC provisions 25% less power per unit and 40% lower total power per rack. Reducing cabling needs reduces overall complexity of data center and rack management.

Data centers are “forever” – and, thus, optimizing operational costs can cast a long shadow and provide “forever” benefits. There is an increasing focus on “sustainable” data centers. Power consumption and energy efficiency are at the core of providing that kind of sustainability. Reductions of 25% power per unit and 40% per rack can provide far reaching benefits with respect to better power efficiency and these benefits only increase as more existing units are replaced by the Dell EMC PowerEdge XE7100.

Flexibility

Not all storage deployments are identical. The type of data and the activities planned can warrant different processing options. The Dell EMC solution offers two different server sled options each of which can be further customized for a particular storage application. The PowerEdgeXE7100, powered by 2nd generation Intel® Xeon® Scalable processors, can be deployed with a single XE7440 full-width sled or up to two XE7420 half-width sleds with various options available for each.

Source: delltechnologies.com

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Designing Products with Purpose

Sustainability is a journey, and if we are being honest, it isn’t an easy one. Whether you’re trying to remember to separate your recyclables from your trash or designing the most innovative technology, sustainability requires commitment and diligence.

Here at Dell Technologies, we have gone all-in on our commitment to sustainability. Just take a look at our bold 2030 goals. In line with our Progress Made Real social impact plan, our designers and engineers focused on supporting our moonshot goal that by the year 2030, for every product sold, we will recycle or reuse an equivalent product and 100% of our packaging and half of our product portfolio will be made from recycled or renewable materials. And we know we can’t achieve this goal on our own – collaboration will be key. It’s why we have also joined the recently announced Circular Electronics Partnership (CEP) alongside the biggest names in tech, consumer goods and waste management, committing to work together to accelerate the circular economy.

Today our work was recognized by the Environmental Protection Agency (EPA) during its 2020 SMM Electronics Challenge Awards. We were given the Champion Award for the Dell Latitude 7300 Anniversary Edition. This is our seventh year in a row to win a Gold Award or Champions Award for recycling. It’s exciting for me because it recognizes the behind-the-scenes innovation happening every day at our company, and it showcases the great work other companies are doing.

Sustainable Design

When we began designing the Latitude 7300 Anniversary Edition several years ago, we knew we wanted to bring more reclaimed materials into our products than ever before. After experimenting with more than 200 different materials, we developed a non-woven carbon fiber fabric, sourced from the aerospace industry, to use in the device. This made it more durable, while also reducing its weight (which is very important for PCs! A true win/win!). Now, three years later, we have expanded our use of reclaimed carbon fiber into even more of our products which has resulted in over two million pounds of carbon fiber diverted from landfills.

But it was about more than that. It was about the entire device lifecycle – from the sustainable materials we sourced and using recycled content in our packaging to selecting waterborne paints which reduce VOC emissions, designing long lifecycle batteries, and shipping by ocean – and finally, taking the device back from you when you need a new one.

And we’re not stopping there. We took the concepts from the Latitude 7300 Anniversary Edition and applied them not only to other Latitude devices, but to other products in the broader Dell portfolio.

We’re also looking at other reclaimed materials for our devices. This past January we announced our new Latitude 5000 series and Precision 3560, which are the first PCs made from bioplastic from tree waste. Produced using a by-product of a paper-making process called ‘tall oil,’ these devices feature lids containing 21% bioplastic content. A great example of a renewable material, our bioplastics are blended with recycled carbon fiber and other plastics for a total of 71% recycled or renewable materials in the lid of the Latitude 5000 series and Precision 3560. By focusing on the second heaviest part of the device – the lid – Dell can make a larger sustainability impact, reducing the product’s carbon, water and energy footprint, while maintaining Dell’s high reliability, durability and performance standards.

Conscientious Choices for a Sustainable Future

Many of us are shopping for much more than just thin and light innovative devices. We’re considering how the technology we use is sourced and produced and we’re conscious of the impact it has on the environment. We want you to feel good about these factors when you choose any Dell product, which is why we have been focused on our sustainability journey for nearly two decades. And while 2030 sounds like the finish line for us to sprint across, the truth is that this journey will never end. So let’s keep on running, shall we?

Source: delltechnologies.com

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A.I. Powered Chatbots in the Enterprise

The world is moving faster than ever with technology increasing that rate of speed. And now your customers want answers in real time. Using AI to enable chat features on your website gives you a direct line of communication with these customers. For many, waiting is not an option and it’s so easy to click over to your competitor’s page.

Here’s a real-life example. I recently ordered a running vest for an upcoming ultramarathon. I had been waiting a couple weeks for the vest to arrive and began thinking something was wrong with my order. So, I opened the vendor’s page to check on it. I was clicking through the support section of it when in the lower right-hand corner, a familiar animation appeared.

It was a chat feature!

Through my interaction with the chat feature, I was able to explain the issue and walk through the steps to correct my order. It was a great customer experience from my end. And an expedient one for the vendor. My issue was handled in a quick and frictionless manner, creating a happy customer for them. This is one of the reasons why the chat feature makes real-time customer service a game changer for the customer experience.

How much of that conservation was with a person or an AI-enabled Chatbot? To me, it didn’t matter. 

What is a Chatbot?

Chances are you have interacted with a Chatbot while searching for help on a website or mobile application. Have you ever thought about how much of that interaction was with a human or machine?

A chatbot is a software application used to engage with humans mostly through text. We’re all proficient at this technology, through our smartphones or through instant messaging as on Slack, Teams, Skype, or if you are as old as me, AOL Messenger. The difference is that instead of your co-worker or a friend on the other end, it is an application.

Now we’ve stated that this conversation mostly happens through text. The focus here, however as AI- enabled voice technology continues to grow, these conversations will happen more through text-to-speech in the future. With the understanding that Chatbot technology is a software application mimicking human conversation, let’s look at the surprisingly long history of chatbots.

The Long History of Chatbots

Did you know the history of Chatbots goes back as early as the 1950s? Alan Turing, the pioneering British WWII Enigma codebreaker, also considered to be the father of computer science, published a paper on what is now termed the “Turing Test” in 1950. Turing proposed to answer the question “can machines think” as tested by having a machine interact with a human — without a human knowing it is interacting with a machine. The publication of this landmark paper kicked off the technology that we now see used in modern day Chatbots. And just recently, it was announced that a new U.K currency will honor Alan Turing for his amazing work.

◉ 1961 – The IBM Shoebox was a computer that could recognize 16 spoken words

◉ 1966 – ELIZA was created in the MIT AI lab and it could demonstrate very basic communication

◉ 1996 – Clippy was an early incarnation of a Chatbot in Microsoft’s office products

◉ 2000s – The 2000’s marked a great feat again with IBM introducing Watson to the world on Jeopardy

◉ 2010s – Voice assistants like Siri and Alexa emerged with the ability to answer questions through voice technology

To this day, software engineers and computer scientists use the Turing test to evaluate their “thinking machines.” There is controversy as to whether we have yet passed the Turing test, but I’ll leave it for others to debate. The most important point for us to take away is that not only do Chatbots have a long history in artificial intelligence, but they also play a foundational role in how AI is changing nearly every industry, with increasing adoption of chatbots and other real-time human to machine interactions.

Dell Technologies for Chatbot Architectures  

At Dell Technologies, we have been working with AI technologies such as chatbots and the underlying systems that power them, including machine learning (ML) and deep learning (DL), for many years. We understand their complexities. And we also work closely with our technology ecosystem partners, including NVIDIA, to accelerate AI adoption. Together, we provide the essential architectural building blocks required for the rigors of data science.

Source: delltechnologies.com

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Driving the Future with AI, HPC and Data

For years, forward-looking people in the automotive industry have focused on the development of self-driving vehicles — and for good reason. Autonomous driving (AD) vehicles, as they are known in the industry, hold the promise of safer, more comfortable and more efficient transportation for all of us.

Unlike road-weary drivers, AD vehicles have no trouble staying alert behind the wheel, even in the darkest hours of night. They can be trained to not only drive the vehicle under normal conditions, but to recognize and react to unlikely scenarios in the roadway. And they will make for a much more pleasant mobility experience for drivers, who can use their time in transit for more interesting activities than staring at the road ahead and the vehicles in it. AD vehicles will even bring us more efficient roadways, as they coordinate their actions with each other and with traffic management systems.

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That’s all the easy part. The hard part is getting there. While the destination is clear, the road to self-driving vehicles comes with some big technical barriers that have to be overcome before we enter this brave new world of vehicles that do the driving for us.

The barriers in the road to AD

The road to self-driving vehicles is like a cross-country trip with important milestones along the way, each of which brings us closer to the ultimate destination. These milestones, established by the Society of Automotive Engineers, include two levels of driver support focused on steering and/or braking and accelerating assistance, two levels in which the car drives itself under limited conditions, and the ultimate level in which the car drives itself everywhere under all conditions.

Each of the milestones in the road to AD vehicles brings its own set of challenges. As each new level is reached, moving to the next requires extensive development, test driving and scenario development, with corresponding data processing and storage requirements growing exponentially at each level. In fact, the highest level of AD will likely require collecting, processing and analyzing exabytes of data. This reality makes data the defining characteristic of AD development — in terms of both the sheer volume and the uncertainty about its growth. Success in this realm is all about innovating with data.

To handle the large data volumes, high performance computing (HPC) systems, supported by artificial intelligence (AI) solutions, must provide high throughput to power many parallel streams of data analysis, simulation and correlation to deliver high‑end simulations. This means that automotive manufacturers and suppliers on the road to AD need to roll out IT infrastructure capable of supporting these steep requirements at every level of the ADAS/AD hierarchy.

And this is where things get even harder. The IT infrastructure needed to support ADAS and AD development is both large and complex, often consisting of thousands of servers and several software stacks. There is also no one-size-fits-all approach for ADAS and AD architectures because each car manufacturer or parts supplier has its own requirements, approach and development roadmap.

That said, there are some universal requirements here. The infrastructure needs to be performant, efficient, cost‑effective and robust enough to span the development cycle for one level, and scalable enough to span ongoing development levels. All the while, the IT architecture should have the flexibility to incorporate new hardware and software as new insights emerge, new tools are developed, and new regulations come into place.

How Dell Technologies helps

To meet these steep requirements, and to overcome the enormous complexities of designing and building AD vehicles, manufacturers need to work closely with technology partners who have the breadth of products and technical expertise to cover the diverse requirements of designing and building self-driving vehicles.

Dell Technologies covers the entire ADAS/AD development chain, and can provide supporting high performance computing and artificial intelligence solutions both for car manufacturers that own the complete chain and for organizations that focus on a subset of components in the chain. Dell Technologies has decades of experience designing cost‑effective systems for HPC and AI, and delivering them in a simplified and customizable building block models.

Dell Technologies also has the partnerships necessary to deliver AD/ADAS solutions with the latest technologies. For example, Dell Technologies and NVIDIA work together closely to deliver AI, HPC and data analytics solutions for data- and compute-intensive challenges. In the case of Dell Technologies solutions for ADAS and AD, multiple AI deep neural networks and algorithms for computer vision, localization and path planning run on a combination of integrated NVIDIA GPUs, CPUs, deep learning accelerators and programmable vision accelerators. Solutions like these wouldn’t be possible without close partnerships among technology leaders.

For a deeper dive into this topic, see the Dell Technologies white paper “The ADAS/AD Architecture,” published as part of the Dell Technologies HPC & AI Innovation Exchange series. This paper provides an in‑depth technical analysis of a range of solutions for manufacturing and automotive companies working to develop ADAS and AD vehicles and their components. It also dives down into various options available for specific use cases and workloads, including remote site and data center infrastructure, software, services, and infrastructure design.

Source: delltechnologies.com

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Be Ready for Anything With Dell Technologies and Intel

There are a lot of lessons to be learned from the past year. One that really stands out, however, is that organizations need to be ready for anything.

The global pandemic forced many to expedite digital transformation initiatives in order to support a sudden shift to remote work, and some were even required to change their entire business model to adapt.

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If that wasn’t enough on its own, organizations today continue to feel the weight of ever-increasing volumes of data being generated. And more and more of that data is being generated outside of traditional data center or cloud.

All of these enormous demands on organizations’ IT require an agile, efficient and secure platform that can quickly respond to shifting requirements. At the same time, IT decision-makers and business professionals need to reduce complexity and costs, while ensuring a secure environment across their entire infrastructure—from the edge to the hybrid cloud.

By harnessing the power of adaptive compute, autonomous compute infrastructure and proactive resilience, Dell Technologies and Intel are giving you the flexibility to meet any challenge, derive data insights from any environment, free IT to focus on innovation, and better protect your business against cyber threats.

Today marks the next milestone in our long-standing partnership with Intel. The balanced architecture of the 3rd generation Intel® Xeon® Scalable processors, with built-in acceleration and advanced security capabilities, deliver a host of advanced technologies that power our portfolio. PowerEdge servers with Intel processors enable emerging capabilities like artificial intelligence (AI), predictive analytics and automation to drive business innovation.

Today, the PowerEdge server portfolio is designed to optimize the workload you want to run on it.

Our new PowerEdge servers fueled by 3rd Gen Intel Xeon Scalable processors are engineered for advanced and emerging workloads, as well as traditional workloads needing high performance, such as virtual desktop infrastructure (VDI) and database analytics. In recent testing, the Dell EMC PowerEdge R750, with 3rd Generation Intel Scalable processors, delivered 43-percent better performance compared to the previous generation R740.

The powerful combination of Dell Technologies and Intel powerhouse gives you an IT foundation that can act as an innovation engine: ready to drive your business forward at top speed today and shift gears quickly when market forces demand.

And if you need even more agility, payment solutions for PowerEdge servers include Flex on Demand, a pay-per-use consumption model that enables customers to scale capacity up or down, with payments that rise and fall accordingly. This gives customers immediate access to buffer capacity as needed, while only paying for the technology they use.

Source: delltechnologies.com

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Going to the Cloud in a Decentralized World

The cloud evolution has now dominated IT industry conversations for more than a decade. Today, when combining the rapid explosion of data and the increasingly decentralized nature of computing, the cloud has become the central focal point for service creators hoping to achieve the new digital outcomes they desire.

And if operating through the COVID-19 pandemic has taught the IT industry anything, it’s that organizations that have embraced digitization were more resilient. They maintained stronger business continuity, and overall fared better through disruption compared to those that self-identified as digital laggards.

What remains true for both leaders and laggards is that the cloud is, and will continue to be, central to digital transformation—especially as the majority enterprise data moves out of the traditional data and to the edge. So, as we evolve in our increasingly cloudified, distributed world, let’s look at five observations to help inform your organization’s cloud strategy.

1. At Dell Technologies, our mantra is that cloud is an operating model—not a destination. Regardless of location, asset ownership or business strategy, cloud operating models are applicable anywhere and must stretch to place technology everywhere.

In fact, we are seeing the traditional hyperscale public cloud vendors acknowledge that the Cloud is not a destination. Dell Technologies has for years tailored solutions for the multi-cloud like the Dell Technologies Cloud Platform, to serve our customers in a private cloud, on-prem market slated to grow 57% by 2024.

2. We have reached the apex of centralization. Hyperscale datacenters have created hundreds of locations with hundreds of thousands of systems, but the pendulum is about to swing in the other direction where we will be managing hundreds of systems in millions of locations at the edge. Combining this new compute environment with the accelerated use of containers and microservices, the hybrid cloud future best positions developers and IT operators to manage, secure, and deploy their data when, where, and how they desire.

3. Unless we solve what Einstein called the “spooky action at a distance,” that is, to conquer zero latency networking through quantum entanglement, we will always face problems of latency.

Point of fact, it’s latency driving the growth of edge deployment. Consider the latency incurred when communicating with a central datacenter at a distance. Imagine an air traffic control system that uses visual inferencing to optimize traffic flows through intelligent signaling. A whole lot can happen on an airfield in those 100 to 200 milliseconds round trip time for a single packet to get from a local camera to a distance centralized public cloud datacenter. Reducing latency to its operational minimum should be the goal.

4. The future will operate in real time, and latency is the enemy of real time. Advanced inferencing systems must operate with such little latency that we talk about latency in picoseconds and nanoseconds.

Proximity is critical to operate real-time, digital experiences. Today, we already see examples of this in no-checkout retail stories, where in-store, real-time automation of digital promotions is delivered to our phones and sensors measure theft prevention…all processed on site. Now just imagine the experiences that are to come in entertainment, transportation, manufacturing, all in real-time, all requiring powerful computing within feet not across continents.

5. We are amid the largest application architectural shift in decades. According to IDC, by 2022 90% of new enterprise applications will be delivered via cloud-native solutions. By 2024, 500 million new applications will be built with cloud-native technologies. To realize our digital future, we will require massive amounts of software. As a result, we need to drive exponential increase in developer productivity. At Dell Technologies, we turned to VMware Tanzu to drive developer productivity and massively accelerate the beat rate of application innovation. The results have been impressive.

For example, our Dell Digital organization deployed 7,500 microservices running in production across six data centers providing 24×7 availability. The infrastructure incorporates VMware vSphere, 71,000 VMware Tanzu application containers and 28,000 Kubernetes pods. It’s enabled developers to build microservices by provisioning cloud services, containers, and virtual machines on their own. With a few clicks, developers provision resources, select cloud features on demand or move applications across on-premises and public clouds without porting. These automated, orchestrated capabilities have reduced development time from typically six months to a few weeks or less — an 85% improvement.

Our distributed future—from the edge to core to cloud—has enormous potential. But to attain it, we must harmonize our operating environments across clouds. Our Dell Technologies Cloud Platform, and VMware Tanzu enable consistent operations across locations and ready customers for this evolving world; to shift the focus from scaling systems within data centers to scaling to tens of thousands of locations with a single company. This new challenge will be a journey, but one we will embark on with our customers and partners toward the future of IT.

Source: delltechnologies.com

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