"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out:
Top 5 causes of downtime and poor performance across the infrastructure stack
How machine learning and predictive analytics can prevent issues
Steps you can take to boost performance and availability"
Today’s smart computers can beat board game champions, master video games, and learn to recognize cats. No wonder artificial intelligence has captured the imaginations of business and IT leaders. And indeed, AI is starting to transform processes in established industries, from retail to financial services to manufacturing. Read this guide from Google Cloud and learn how you can unlock the transformational power of information and get useful insights from a vast and complex landscape of data.
If you’re relying on manual processes for testing applications, artificial and automated intelligence (AI) and machine learning (ML) can help you build more efficient continuous frameworks for quality delivery.
In this on-demand webinar, “Continuous Intelligent Testing: Applying AI and ML to Your Testing Practices,” you’ll learn how to:
Use AI and ML as the new, necessary approach for testing intelligent applications.
Strategically apply AI and ML to your testing practices.
Identify the tangible benefits of continuous intelligent testing.
Reduce risk while driving test efficiency and improvement.
This webinar offers practical steps to applying AI and ML to your app testing.
The speaker, Jeff Scheaffer, is senior vice president and general manager of the Continuous Delivery Business Unit at CA Technologies. His specialties include DevOps, Mobility, Software as a Service (SaaS) and Continuous Delivery (CDCI).
You’re ideating while executing. With funding in hand, you must deliver. Patience? Well, it’s nonexistent. If this sounds familiar, you’re likely one of many energetic companies vying to grab the best talent possible to deliver on your mission. How well your workforce executes will depend on the quality of your onboarding and employee development.
By building an eLearning program on a Learning Management System (LMS), you’ll get newbies up to speed and free your team to focus on the heavy brain work. Here’s how the right LMS will pay off bigtime ROI.
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.
Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable.
Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust.
Watch this webinar to learn:
• How you can more effectively communicate with data.
• What constitutes an intuitive and highly navigable report
• How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time.
• Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
Businesses are struggling with numerous variables to determine what their stance should be
regarding artificial intelligence (AI) applications that deliver new insights using deep learning.
The business opportunities are exceptionally promising. Not acting could potentially be a
business disaster as competitors gain a wealth of previously unavailable data to grow their
customer base. Most organizations are aware of the challenge, and their lines of business
(LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
IDC believes that this emerging environment is to date still highly undefined, even as
businesses must make critical decisions. Should businesses develop in-house or use VARs,
systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some
hybrid form? Can they use existing infrastructure, or do AI applications and deep learning
require new servers with new capabilities? We believe that many of these questions can be
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively.
Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies.
Download this solution brief to learn more.
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. You’ll then be ready to experiment with these methods in SAS
Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
The focus on employee engagement as a driver of better business results has gotten so much traction it’s spawned an entire category of solutions within the HCM universe. But if you’re a SumTotal client, you already own a tool that has incredible — but often-overlooked — potential for creating an environment in which engagement can not only flourish, but actually be sustained.
It’s all about having content that strategically positions your company, is easy to find, and truly engages your employees to seek opportunities to make a difference and to grow professionally.
To really shape your SumTotal LMS into the effective piece of technology you know it can be — to see it achieve the results you and your leadership team expect it to deliver — you need to be a content architect and have a great content strategy.
Now you can learn the process Bluewater has developed through years of experience helping clients worldwide maximize their SumTotal LMS to drive higher engagement and better business results:
• Mapping out a plan for engagement success
• Understanding the negative effects when you don’t have a content strategy that makes strategic sense for your organization — on employees, leaders, LMS owners, and learning practitioners
• Architecting content for engagement today — and for the road ahead
• Building the framework for a rich content ecosystem where learners feel at home
• Focusing on people, processes, and technology: an approach to content strategy that supports a culture of engagement
It’s all about being ridiculously happy with your SumTotal LMS.
Published By: Genesys
Published Date: Jun 11, 2018
When you can anticipate customer needs, you can provide a customer experience that reduces frustration, increases satisfaction and creates better business results.
Genesys Altocloud uses live analytics, powered by machine learning, to give you real-time insight into the customer experience. You can anticipate customer behavior, personalize journeys and use feedback to continuously tune your analytics to achieve desired business outcomes.
Download the white paper and learn how to make better use of your analytics:
• Automate responses that optimize the journey
• identify and engage with customers before they contact you
• Use predictive analytics and machine learning to drive outcomes
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics.
Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set:
• Enterprise-class relational database query and management system
• Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools
• Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
When augmenting the benefits package
for your organization, it’s natural to focus
on traditional perks that employees have come to
expect: PTO, health insurance, and maybe a tuition
assistance credit here or there. But if you’re looking
for creative and effective ways to stimulate
employee engagement while also driving business
results, you’ll want to consider the powerful impact
of offering language-learning opportunities.
Why language learning? It offers immediate and
long-term benefits to both employees and employers.
Research shows that organizations that offer access
to language learning see an increase in employee
engagement factors like loyalty, morale, and
productivity, which in turn boosts business performance
factors such as customer satisfaction
and internal communications.
Where’s the connection? And how can you reproduce
these benefits within your organization? This
playbook offers a deeper look at why language
learning has such a positive influence on employee
Published By: Tenable
Published Date: Apr 30, 2018
When it comes to IT infrastructure, it’s fair to say the perimeter has left the premises. Whether it’s discovering short-lived assets (e.g., containers), assessing cloud environments or maintaining web application security, today’s attack surface presents a growing challenge to CISOs looking to understand and reduce their cyber risk. To combat this issue, a discipline called Cyber Exposure is emerging to help organizations manage and measure this risk. This ebook provides insights on how CISOs are addressing the modern attack surface.
Published By: Cylance
Published Date: Jul 02, 2018
The information security world is rich with information. From reviewing logs to analyzing malware, information is everywhere and in vast quantities, more than the workforce can cover. Artificial intelligence (AI) is a field of study that is adept at applying intelligence to vast amounts of data and deriving meaningful results. In this book, we will cover machine learning techniques in practical situations to improve your ability to thrive in a data driven world. With clustering, we will explore grouping items and identifying anomalies. With classification, we’ll cover how to train a model to distinguish between classes of inputs. In probability, we’ll answer the question “What are the odds?” and make use of the results. With deep learning, we’ll dive into the powerful biology inspired realms of AI that power some of the most effective methods in machine learning today. Learn more about AI in this eBook.
Published By: Cylance
Published Date: Jul 02, 2018
Artificial intelligence (AI) technologies are rapidly moving beyond the realms of academia and speculative fiction to enter the commercial mainstream, with innovative products that utilize AI transforming how we access and leverage information. AI is also becoming strategically important to national defense and in securing our critical financial, energy, intelligence, and communications infrastructures against state-sponsored cyberattacks. According to an October 2016 report issued by the federal government’s National Science and Technology Council Committee on Technology (NSTCC), “AI has important applications in cybersecurity, and is expected to play an increasing role for both defensive and offensive cyber measures.” Based on this projection, the NSTCC has issued a National Artificial Intelligence Research and Development Strategic Plan to guide federally-funded research and development. The era of AI has most definitely arrived, but many still don’t understand the basics of this im
Published By: Cylance
Published Date: Jul 02, 2018
The 21st century marks the rise of artificial intelligence (AI) and machine learning capabilities for mass consumption. A staggering surge of machine learning has been applied for myriad of uses — from self-driving cars to curing cancer. AI and machine learning have only recently entered the world of cybersecurity, but it’s occurring just in time. According to Gartner Research, the total market for all security will surpass $100B in 2019. Companies are looking to spend on innovation to secure against cyberthreats. As a result, more tech startups today tout AI to secure funding; and more established vendors now claim to embed machine learning in their products. Yet, the hype around AI and machine learning — what they are and how they work — has created confusion in the marketplace. How do you make sense of the claims? Can you test for yourself to know the truth? Cylance leads the cybersecurity world of AI. The company spearheaded an innovation revolution by replacing legacy antivirus software with predictive, preventative solutions and services that protect the endpoint — and the organization. Cylance stops zero-day threats and the most sophisticated known and unknown attacks. Read more in this analytical white paper.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
• Facing a myriad of challenges from digital transformation, business today are making big bets on the best collaboration tools they need on hand to meet those challenges. From employee buy-in, to machine-learning capabilities, to security, it's important to select a service with the right capabilities to further your business goals. The challenge, however, is that with so many services to choose from it can be difficult to figure out which one is the right fit for your business.
• This eBook, 5 Considerations in Choosing a Collaboration Platform in the Digital Age, will walk you through the ins and outs of what to keep in mind as you choose the best collaboration platform for you.
Business users expect immediate access to data, all the
time and without interruption. But reality does not always
meet expectations. IT leaders must constantly perform
intricate forensic work to unravel the maze of issues that
impact data delivery to applications. This performance
gap between the data and the application creates a
bottleneck that impacts productivity and ultimately
damages a business’ ability to operate effectively.
We term this the “app-data gap.”