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
While many organizations are guarding the front door with yesterday’s signature-based antivirus (AV) solutions, today’s unknown malware walks out the back door with all their data. What’s the answer? A new white paper, “The Rise of Machine Learning in Cybersecurity,” explains machine learning (ML) technology —what it is, how it works and why it offers better protection against the sophisticated attacks that bypass standard security measures. You’ll also learn about CrowdStrike’s exclusive ML technology and how, as part of the Falcon platform’s next-gen AV solution,it dramatically increases your ability to detect attacks that use unknown malware.
Download this white paper to learn:?How different types of ML are applied in various industries and why it’s such an effective tool against unknown malware?Why ML technologies differ and what factors can increase the accuracy and effectiveness of ML ?How CrowdStrike’s ML-based technology works as part of the Falcon platform’s next-generation AV
DevOps cuts deep and wide through industries, company sizes, and technology environments. Yet, DevOps is never done — it’s about continual learning and improvement rather than an end state.
Puppet is here to help. We draw on the success stories and lessons learned at organizations that are already driving improved performance and better business outcomes with their DevOps initiatives.
This handbook captures five essential phases for mapping out a DevOps journey:
1. Build the business case for DevOps.
2. Address the biggest challenges to DevOps success.
3. Develop a performance-driven team structure.
4. Choose the right Tools and processes.
5. Plan your key implementation phases.
Effective metrics and measurements are critical to running a high performance business. Properly applied, they lead you to better insights, better decisions and better business outcomes. They provide feedback to spark improvement and create learning opportunities. They help you identify the right outcomes that drive you toward your business goals. Unfortunately, many businesses misuse these powerful tools in ways that actively destroy the agility they seek to create. In this paper, we highlight nine mistakes organizations make involving agile measurement at enterprise scale—and how to do it right.
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.
AI, machine learning and predictive analytics are already driving big performance gains for CFOs and their teams. The ability for cognitive tools to learn at speed helps Finance progressively improve company intelligence and efficiency, including proactive identification of late- and non-paying customers. Get up to speed on the potential of cognitive, with Finance thought-leaders from Oracle and AICPA (American Institute of Certified Public Accountants).
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.
Today's Human Resources (HR), talent and learning executives face strategic challenges, organizational challenges, economic challenges, and a plethora of tactical issues each day. Read this whitepaper to learn how to get the right tools to drive decision making.
Published By: Fujitsu
Published Date: Feb 26, 2018
As schools look to blended learning as a solution to personalize and positively impact student achievement, the need to train and support teachers has become blatantly clear. Thus, districts and schools have allocated scarce resources to the process of onboarding and supporting teachers as new tools and platforms are introduced. However, school leaders and teachers often fail to recognize the need to similarly onboard and support students into new digital environments, instead trusting the inherent technological competencies of the “digital native” student.
Intel, the Intel logo, Intel Core, Intel vPro, Core Inside and vPro Inside are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries
Web conferencing can be used in many meeting scenarios, from internal collaboration to presentations, training and large events. IT leaders must examine the use cases that will drive their requirements for a portfolio of online meeting technologies.
Machine learning is proving its power across virtually every industry in ways that add actionable insight and efficiency. But one can look at the rise of this transformative paradigm with a more focused lens to see AI technologies as a business tool of the highest order, one that improves processes and inspires new models. AI, in other words, has a big role to play on the balance sheet.
Two leading brands in very different spaces — Capital One in financial services, John Deere in agriculture — are seeing efforts that stretch back decades come to fruition with the launch of cloud-based AI platforms. Capital One is developing digital products and experiences using machine learning to help millions of customers with their financial lives; John Deere’s Precision Agriculture solution helps farmers gain precise information about their machines and crops. In both instances, AI and a cloud platform combine to enable transformation.
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
Published By: BMC ASEAN
Published Date: Dec 18, 2018
Digital transformation encompasses both technological and human components. While many initiatives focus on ensuring that a company’s multi-cloud infrastructure is agile enough to meet changing demands around cloud mobile, Internet of Things (IoT), and big data, it’s equally important to empower business workers with the modern digital tools they need to be successful today. Artificial intelligence and machine learning can play a vital role on both of these fronts. In fact, 78 percent of CIOs and senior IT leaders are already looking to AI to address complexity,1 and by 2019, 30 percent of IT service desks will utilize machine learning to free up support capacity.2
The magnitude of change has forced companies to take stock of the experience they offer employees. As digital natives3 enter and advance in the workforce, talent retention is now a top priority. These workers expect to have the best tools; 93 percent of millennials cited modern and up-to-date technology as one of the most
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
Providing an effective teaching and learning environment is the primary goal of all educational institutions.
Traditionally, administrators concentrated on providing faculty with the tools to properly deliver the curriculum and structuring the learning process to sufficiently engage students. But, violent incidents over the past decade along with government regulations have put pressure on administrators to focus on the physical security and safety of staff, faculty, and students.
To find out more download this whitepaper today.
Higher education has come under increasing scrutiny as never before due to rising costs, changes in future job requirements, and new forms of learning opportunities offered by non-traditional companies and institutions. Students and parents are rightfully questioning the value of higher education based on perceived outcomes as well as staggering student loans that in some cases could take a lifetime to pay back. While the value equation debate rages on, there is another phenomenon taking place. It is nothing short of a revolution regarding the advances in technology and how institutions of higher learning along with nontraditional organizations are utilizing these powerful new tools. These new tools include new mobile devices, enhanced and feature-rich learning management systems, data-feeding sensors, 3D printers, smart classrooms, smart buildings, and collaboration tools allowing students and faculty to collaborate just about anywhere face-to-face, virtually.
Machine learning offers the depth, creative problem-solving capabilities, and automation to help security organizations gain significant ground against attackers. It’s a powerful tool for processing massive amounts of data for the purpose of malware classification and analysis, especially for unknown threats. Through supervised learning, human researchers can continually develop new training models that expand the understanding and competency of machine learning systems.
Published By: Tribridge
Published Date: Feb 09, 2015
Delivering great content is often the biggest stumbling block to effective learning in many organizations. A sensible content strategy can help any organization jump-start, rebuild, or enhance its learning initiatives.
Financial organizations are deploying artificial intelligence and machine learning in the fight against financial crimes. David Stewart, Director of Pre-Sales for the Global Security Intelligence Practice at SAS, offers tips to help separate fact from market hype when reviewing new data analytics tools. You’ll learn about:
• The new industry intrigue with artificial intelligence and machine learning.
• How these emerging solutions can benefit financial institutions.
• The SAS approach of “crawl, walk, run” when it comes to adopting new analytics tools.
While many organizations are guarding the front door with yesterday’s signature-based antivirus (AV) solutions, today’s unknown malware walks out the back door with all their data. What’s the answer?
This white paper, “The Rise of Machine Learning in Cybersecurity,” explains machine learning (ML) technology — what it is, how it works and why it offers better protection against the sophisticated attacks that bypass standard security measures. You’ll also learn about CrowdStrike’s exclusive ML technology and how, as part of the Falcon platform’s next-gen AV solution, it dramatically increases your ability to detect attacks that use unknown malware.
Download this white paper to learn:
• How different types of ML are applied in various industries and why it’s such an effective tool against unknown malware
• Why ML technologies differ and what factors can increase the accuracy and effectiveness of ML
• How CrowdStrike’s ML-based technology works as part of the Falcon platform’s next-gene
Published By: Skillsoft
Published Date: Mar 03, 2015
This paper offers a set of best practices for identifying learning needs that support business priorities, align a solution and measure results. It is a consolidated set of ideas, tips and techniques collected from the experiences of Skillsoft customers.
Why It’s Time to Retire Your Traditional L&D Strategy (and Your Social One, Too) You’ve heard it a hundred times. Continuous learning is critical to your talent management strategy—and your organization’s bottom line. To that end, you’ve invested in a powerful learning management system (LMS) and social tools, not to mention great content.
DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Our portfolio of live events, online and print publishing, business intelligence and professional development brands are centred on the complexities of technology convergence. Operating in 42 different countries, we have developed a unique global knowledge and networking platform, which is trusted by over 30,000 ICT, engineering and technology professionals.
Data Centre Dynamics Ltd.
102-108 Clifton Street
London EC2A 4HW