"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond
the remote monitoring systems of a prior generation. Three key features differentiate cloud-based
predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine
learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically
what types of value these systems can drive, IDC discusses them at some length in this white paper."
Download this white paper to find out how you could augment your fraud management with Decision Manager machine learning insights from more than 68 billion annually processed Visa and CyberSource transactions – matched with flexible rules-based fraud strategies.
• Detect fraud more accurately with robust data and insights on ever-changing fraud patterns
• Protect your bottom line by reducing fraud and chargebacks
• Increase acceptance rates with the only fraud solution that uses machine learning to generate and test new rules-based strategies from your historic data
The Future of Work: 10 Essentials for Winning Employee Development
Your go-to guide for thriving in the changing face of work
Employee development looks a lot different today than it did just a few years ago. This ebook details 10 trends that are crucial for keeping up with the ever-changing future of work.
The modern workforce is a place where baby boomers, Gen X, millennials and now Gen Z all share the same Nespresso machine. That’s four distinct generations with different views, expectations and priorities. Companies will have to adopt new methods for just about everything—from recruitment and benefits to employee development and career planning.
While there are several key differences between each generation in the modern workforce, how companies should treat them can be summarised in one word: individually.
This ebook is designed to help HR and L&D professionals who want to turn their organisation into a learning environment well-equipped for the workplace of tomorrow, do ex
NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
Have you ever wished for an army of clones to do all your thankless
tasks and chores? Well, that fantasy is becoming a reality—at least
on the Internet. And while they may not be actual clones, bots have
begun doing lots of digital dirty work.
Managing your relationship with bots—good and bad—has become an inherent part of doing business in a
connected world. With more than half of online traffic initiated by autonomous programs, it’s clear that bots
are a driving force of technological change, and they’re here to stay.
As bot technology, machine learning, and AI continue to evolve, so will the threats they pose. And while
some bots are good, many are malicious—and the cybercriminals behind them are targeting your apps.
Preparing your organization to deal with the impact of bots on your business is essential to developing a
sustainable strategy that will enable you to grow as you adapt to the new bot-enabled world.
What impact will the cloud-enabled workplace have on your cybersecurity strategy? This year’s research shows that organisations are navigating a myriad of both old and new cybersecurity challenges to bring the cloud into scope.
Read this to discover:
• how growing cloud dependency has created distinctive challenges around cyber security
• what the biggest cyber challenges are for organisations in this context
• how intelligent automation and machine learning is being used to overcome operational obstacles hampering cloud security
• a set of cybersecurity considerations for modern IT environments.
High-volume administrative tasks are a feature of every business. We helped a global bank develop a machine learning algorithm to help with the task of reviewing over 100,000 ‘sanctions alerts’ every day.
Read this story to find out:
• what other benefits AI can deliver beyond cost savings
• how AI tools achieve greater accuracy than human reviewers
• what it takes to apply AI and Machine Learning successfully in a regulated sector.
New Techniques That Will Drive Revenue in 2019
If you’re ready to move beyond simple calculations and realize the vast potential of data driven selling, you’re ready to explore the next generation of SPM platforms.
Download the report to learn how the modern technologies like Artificial Intelligence and Machine Learning, can give your sales reps a roadmap to better performance and give sales management insights that will enable them to achieve more profitable sales.
Did you know that organizations with advanced finance teams are more likely to have a compelling digital customer experience? The driver behind this trend? A digital, customer-first way of working with greater investment in talent, innovation, and advanced technologies such as artificial intelligence (AI) and machine learning (ML).
While finance has long taken advantage of technology to help drive productivity and collaboration, the goalposts have recently moved. Today’s organizations must adopt an agile finance operating model— powered by emerging digital technologies and skillsets—to better support the demands of an economy driven by continuous innovation.
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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
The bar for success is rising in higher education. University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
Artificial Intelligence (AI) has already begun to improve targeting, segmentation, media buying and planning in the advertising industry. AI algorithms can extract complex patterns from vast numbers of data points, and in so doing, are able to self-correct and learn patterns. The revenue potential that improved personalization, segmentation and targeting that AI provides to marketers is huge.
At HERE Technologies, we are placing AI and machine learning at the center of our products and services. We see the opportunity in automated machine learning to enrich the targeting and effectiveness of mobile advertising campaigns in real time. But the outcome of implementing such technology depends on the quality of data being fed into it from the outset. AI wouldn’t be as helpful if it’s being used alongside questionable location data or audience data.
HERE’s location data provides a strong thread that can be woven throughout every stage of the media buying process, offering more context and
Published By: Cisco EMEA
Published Date: Nov 13, 2017
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.
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates.
? Optimal application performance and delivery is difficult to achieve in complex environments.
? Many IT infrastructure and operations teams are stretched to the breaking point.
? Predictive analytics and machine learning can be applied to great effect
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.”
"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"
Published By: Dell EMC
Published Date: Oct 13, 2016
Flexibility is important, since many future initiatives—big data, machine learning, emerging technologies, and new business directions—will be built on this cloud structure.
No matter what shape your cloud infrastructure takes, Dell EMC converged and hyper-converged platforms and innovations like Dell EMC VscaleTM Architecture, powered by Intel® Xeon® processors, deliver the pathways to scale-up and scale-out, today and tomorrow.
Published By: Genesys
Published Date: Jun 06, 2017
In this ebook, learn:
- Five trends will have the biggest impact on customer experience
- How to use machine learning to detect patterns and trends to deliver the next great customer experiences
- How to future-proof your contact center and adapt to changing customer needs
Every week InfoSight analyzes more than a trillion data points from
more than 9,000 customers. How does this translate into true
business value? By reducing your business risk with over Six-Nines
of measured availability. By providing you with an infrastructure
that gets “smarter” every single day. By empowering IT staff to
focus on business priorities instead of mundane maintenance.
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally.
Learn more about key findings, including:
Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics.
Return on investment for analytics stems from the governing and sharing of data throughout the organization.
Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.