There can be no doubt that the architecture for analytics has evolved
over its 25-30 year history. Many recent innovations have had significant
impacts on this architecture since the simple concept of a single
repository of data called a data warehouse. First, the data warehouse
appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the
traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had
a substantial effect on the analytical architecture.
Many business leaders know that Artificial Intelligence (AI) and Machine Learning (ML) are critical to their future but don’t know where to start. Those who do have an AI/ML strategy struggle to find qualified data scientists; and once they find them, even advanced data scientists need a lot of time—even months—to build and deploy ML models. These challenges put significant limits on the range and number of problems a business can solve.
In this webinar, learn how H2O Driverless AI on Amazon Web Services (AWS) automates the best practices of leading data scientists to create advanced machine learning models automatically. With these production-ready models, relative newcomers to AI/ML can generate reliable results and scale-up AI programs that anticipate and capitalize on trends, optimize supply chains, understand customer demand, match consumers with goods and services, and much more.
Download our webinar to learn
Implement ML successfully with minimal data science expertise.
Trupanion, a Seattle-based medical insurance provider for cats and dogs, needed to find data insights quickly. With only 1% of pet owners insured, the process of evaluating a claim to approve or deny payment was manual and time-consuming. Building accurate predictive models for decision-making required manpower, time, and technology that the small company simply did not have.
DataRobot Cloud, built on AWS, helped Trupanion create an automated method for building data models using machine learning that reduced the time required to process claims from minutes to seconds. Join our webinar to hear how Trupanion transformed itself into an AI-driven organization, with robust data analysis and data science project prototyping that empowered the company to make better decisions and optimize business processes in less time and at a reduced cost.
Join our webinar to learn:
Why you don’t need to be an expert in data science to create accurate predictive models.
How you can build and deploy pr
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
Published By: Uberflip
Published Date: Dec 20, 2018
In today’s world, marketers know that producing content isn’t enough. If they’re going to continue to make an investment in creating content, they need to do more to ensure it performs. We’ve long since known that combining content with a remarkable experience will allow it to reach its full potential, and allow marketers to see results. But as with any emerging category, content experience was not without its detractors. After all, what kind of results could you expect from an investment in the experience around that content? If you’ve ever wondered why you should care about content experience, and wanted something a little more concrete than a few anecdotes from marketers, or third-party stats, then look no further.
Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time.
AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance.
In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences.
Join this webinar to learn:
How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development.
How AWS supports BI solutions f
Marketing leaders are asking their analytics teams to provide better insights
into customers, prospects and journeys, and a more accurate assessment
of the impact of marketing tactics. Use this research to find a digital
marketing analytics tool to support your needs.
This Magic Quadrant is intended for chief marketing of?cers (CMOs), marketing analytics and data
science practitioners, and other digital marketing leaders involved in the selection of systems to
support marketing analytics requirements.
Last year at this time, we forecast a bumpy ride for infosec through 2017, as ransomware continued to wreak havoc and
new threats emerged to target a burgeoning Internet of Things (IoT) landscape. ‘New IT’ concepts – from DevOps to various
manifestations of the impact of cloud – seemed poised to both revolutionize and disrupt not only the implementation of
security technology, but also the expertise required of security professionals as well.
Our expectations for the coming year seem comparatively much more harmonious, as disruptive trends of prior years
consolidate their gains. At center stage is the visibility wrought by advances in data science, which has given new life to threat
detection and prevention – to the extent that we expect analytics to become a pervasive aspect of offerings throughout the
security market in 2018. This visibility has unleashed the potential for automation to become more widely adopted, and not
a moment too soon, given the scale and complexity of the thre
Join Oracle’s CX and Marketing Strategy Director, Wendy Hogan, and Senior Vice President Oracle Marketing, Shashi Seth, as they tell how AI, machine learning and data science can engage customers, automate tasks and build ROI. Reaching the right customers on the right channel at the right time, brings rewards for CMOs who embrace these innovations, including engaged customers and increased ROI. Be inspired by the new-generation AI, machine learning and data science and take your marketing to the next level.
In a panel discussion at the 12th annual SAS Health Analytics
Executive Forum in May 2015, leaders from Dignity Health,
Horizon Blue Cross Blue Shield of New Jersey, Janssen
Pharmaceuticals and SAS shared what they have done to prove
the value of analytics to their business leaders – and what has
worked for them as they developed an analytic culture in their
organizations and put analytic insights to work.
In our latest survey report, we explore the growth challenges facing businesses and HR leaders in a rapidly changing landscape.
We surveyed over 500 HR leaders in leading organisations to explore their views on these challenges, and to find out how they are supporting people and leveraging people data to help them achieve their growth goals.
The survey revealed that:
• It’s the war for talent, again. The greatest challenges for growing companies are winning the war for talent, growing productivity and improving workforce visibility.
• Fast-growth companies share common traits in the way they manage and engage their people—we call this being a People Company.
• There’s a disconnect between managers and employees in terms of what being a People Company means.
• Becoming a People Company is a journey, with many organisations some way from embracing all aspects.
• People Science is a thing: there’s an appetite to leverage people data and analytics, but there are blockers in the way.
Published By: Tenable
Published Date: Feb 27, 2019
"Overwhelmed by the number of vulnerabilities your team faces? Uncertain which cyber threats pose the greatest risk to your business? You’re not alone. Cybersecurity leaders have been grappling with these challenges for years – and the problem keeps getting worse.
On average, enterprises find 870 vulnerabilities per day across 960 IT assets. There just isn’t enough time or resources to fix them all. More than ever, it’s essential to know where to prioritize based on risk.
Download the new whitepaper “Predictive Prioritization: How to Focus on the Vulnerabilities That Matter Most” to:
-Learn how to focus on the 3% of vulnerabilities that have been – or will likely be – exploited
-Uncover why CVSS is an insufficient metric for prioritization – and the key criteria you need to consider
-Understand the Predictive Prioritization process, which uses machine learning to help you differentiate between real and theoretical risks
Ensure you’re prioritizing the right vulnerabilities for your t