Forbes recently referred to robotic process automation (RPA) as “a gateway drug to AI,” referencing its low barrier to entry compared to other technology choices within the AI realm. But while experts continue to tout the future of RPA, what can we expect of it in the short-term?
Jump into this resource to get a peek at how experts are predicting RPA’s 2019 will pan out, including notable market shifts, major technology disruptions, and entirely new RPA use cases.
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
Quality matters, but despite advances made in video streaming technology, delivering great quality live video over the
Internet is still not easy. There are challenges with predicting the scale and potential audience location; challenges with
managing complex encoder and origin technology; challenges of delivering video securely and reliably over the Internet;
and challenges of protecting live streams. Add to that the range of devices, the complexity of live event production, and
the demand for HD and 4K image quality and you get a scenario that is more complicated than ever before.
Supporting the needs of information workers requires the delivery of the latest, relevant information at the point of decision. Download this IDC Report to learn how to enable finance in a digital enterprise to plan, monitor, and predict.
Just after the turn of the decade researchers are predicting there will be somewhere north of 24 million subscriptions to next generation 5G networking services. Today most of those services are little more than pilot projects. But thanks to emerging network function virtualization (NFV) software running on Mobile Edge Computing (MEC) platforms enabled by Intel most of those 5G services should be in production before the end of the decade.
Come learn how MEC platforms are about to transform every corner of the networking world to not only drive the creation of a vast array of new IT services, but also make networks more agile and responsive than anyone ever thought possible.
Working out what consumers want – and why – is getting harder. Transactional data and traditional market research and demographic profiles no longer do the job. Our ‘Five Mys’ report proposes a radical new framework for navigating complex consumer decision-making.
Read the report to find out:
• what the ‘Five Mys’ are and how they affect spending decisions
• how to get better at predicting consumers’ changing needs
• where different generations are directing their spending
• how changing life patterns are creating new opportunities for businesses that can pick up on signals from consumers
Unexpected failure or performance erosion of production equipment can significantly impact productivity, product quality and maintenance expenses within any manufacturing organization. It’s also difficult to get operations ‘back on track’ after these failures occur. The good news is that, via the Internet of Things, intelligent use of sensor data, machine learning and optimization can help companies take a proactive approach to predicting failures and re-optimizing processes around them.
Data is the hottest topic in business today. In discussions that range from
understanding performance to predicting future outcomes, data is at the core.
However, data has a bad reputation. Because businesses have been collecting data for
decades, the amount that we must analyze can seem insurmountable. Simply saying
“data” is enough to conjure images of someone poring over a thick stack of
spreadsheets, manually going through row after row to identify performance, trends
and figure out what to do with them. This intimidating view is all too common.
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
Predicting the future is impossible and attempting it might seem like
folly. But as in most cases, it is the process – not the outcome – that
For hotel leaders, anticipating consumer trends and seeking
innovations that enhance guest experiences are vital exercises that
need to be practiced diligently. Now, more than ever – with the
coming wave of disruptive technologies – taking these steps helps
ensure success tomorrow.
Published By: BMC ESM
Published Date: Aug 19, 2009
Would you trust your network monitoring tools enough to know when something is truly halting a business service? While Mary Nugent won’t use this podcast to attempt to tell you technical details on the correct alarming thresholds, she will share some excellent stories about predicting a system’s behavior. Run Time: 11:30.
Digital transformation (DX) has progressed well beyond the abundant hype predicting it to where it is now an existential concern for many enterprises. We are at an inflection point as digital transformation efforts shift from "project" or "initiative" status to strategic business imperatives. Growing enterprises,
regardless of age or industry, are striving to become "digital native" in the way their executives and employees think, what they produce, and how they operate. IDC predicts that by 2021, at least 50% of global GDP will be digitized, with growth in every industry driven by digitally enhanced offerings, operations, and relationships, and that by 2020, investors will use platform/ecosystem, data value, and customer engagement metrics as valuation factors for all enterprises.
ECM can and should be applied across the enterprise as a whole. Focusing on ECM as described in this free white paper offers a disciplined, pragmatic approach to predicting and managing all types of change across an enterprise, while potentially delivering proven cost benefits and efficiency improvements throughout the organization. Learn more today!
Imagine getting into your car and saying, “Take me to work,” and then enjoying an automated
drive as you read the morning news. We are getting very close to that kind of
scenario, and companies like Ford expect to have production vehicles in the latter part
Driverless cars are just one popular example of machine learning. It’s also used in
countless applications such as predicting fraud, identifying terrorists, recommending
the right products to customers at the right time, and correctly identifying medical
symptoms to prescribe appropriate treatments.
The concept of machine learning has been around for decades. What’s new is that
it can now be applied to huge quantities of data. Cheaper data storage, distributed
processing, more powerful computers and new analytical opportunities have dramatically
increased interest in machine learning systems. Other reasons for the increased
momentum include: maturing capabilities with methods and algorithms refactored to
run in memory; the
Published By: Internap
Published Date: Dec 02, 2014
As organizations aim to increase business agility and streamline
costs, demand for public cloud services continues to grow exponentially, with Gartner predicting it will become the majority
of new IT spending by 2016.
This evolving application ecosystem with its intensive performance
demands is placing new pressures on traditional public
cloud services. Amid this shift, Internap surveyed nearly 250 Internet infrastructure decision makers to gain insight into cloud
adoption, requirements and challenges – including the differences in feedback between the cloud-wise, those using cloud services, and the cloud-wary, those with no near-term plans to use cloud services. The details of these findings are reflected in this Cloud Landscape Report.
Published By: Aternity
Published Date: Dec 30, 2011
Many enterprises have developed sophisticated Application Performance Management (APM) capabilities only to find that many of the techniques that work in the data center won't work in the cloud. The cloud turns the idea of locating and predicting performance problems across cloud applications on its head.
Current approaches for predicting with a high degree of confidence the application performance prior to implementation into production can be antiquated, expensive and time consuming. This document outlines a next-generation performance management approach using Service Virtualization and Application Performance Management being adopted by progressive organizations around the world.
Adopting a next-generation performance management approach can offer a range of benefits including efficiency gains in delivering applications, cost savings, improved agility and better performing applications. For organizations that increasingly rely on technology to provide value to stakeholders improving application delivery capability is critical to remaining competitive and relevant.