IT Executive news

• BrandPost: Revving Up AI Workloads with HPC under the Hood

  25-04-2019 23:24
  In enterprise environments, the need for speed has never been greater. Business competitiveness increasingly hinges on products and services driven by artificial intelligence (AI) systems that generate instantaneous insights and take autonomous actions in real time.To deliver this blazing speed, AI needs a lot of computational horsepower under the hood, along with an architecture designed for lightning-fast processing, bottleneck-free I/O and the capacity to handle huge datasets. To get there,
  
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• BrandPost: CIOs are Overestimating DevOps Maturity

  25-04-2019 18:43
  Forrester recently completed an interesting new research project exploring what separates DevOps leaders from DevOps laggards. After analyzing data collected from 603 global enterprise respondents responsible for their firms’ DevOps strategies, Forrester learned that firms with the most mature DevOps practices do several key things differently:
  Allocate proper testing budgets and focus on upgrading their testing skills
  Implement Continuous Testing to meet the demands of release frequency
  
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• IDG Contributor Network: Don’t become a digital transformation horror story: Implement solid risk management

  25-04-2019 15:51
  Over the last two decades the road to business process transformation has been cluttered with IT enabled transformation disasters. In the last few years, these are some that we’ve analyzed:
  MillerCoors Sues HCL for $100M for Breach of Contract and is Countersued by HCL
  Bridgestone Sues IBM for $600M in Damages
  National Grid Sues Wipro Stating Costs Exceeded $1B for a Program Initially Budgeted for $290M
  Co-Op Insurance Sues IBM for $100M in Damages
  The State of Oregon and Oracle File Duel
  
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• IDG Contributor Network: 5 cybersecurity jobs with the highest salaries in 2019

  25-04-2019 14:46
  As our reliance on data continues to expand, so does the prevalence and likelihood of more advanced, successful cyberattacks. One look at Bloomberg News’ recent analysis of over 200 major breaches portrays the severity of what’s at risk for businesses, especially those in the Technology sector. The weaponization of AI by hackers will only increase the effectiveness and frequency of attacks, which is why companies across all industries are hiring for high-end cybersecurity talent now
  
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• IDG Contributor Network: Is it time for consumer data go mainstream in healthcare?

  25-04-2019 14:29
  A recent survey of over 300 CEOs across the globe by consulting firm PwC indicates that 2019 is the year enterprises expect to extract value from data. The data that enterprises value most? Consumer data, which includes demographic, lifestyle, and health data.Traditionally, consumer data has been in the purview of major established firms in the space, such as Experian and Acxiom, who have built vast data repositories by aggregating, organizing and monetizing data from a large number of public a
  
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• Making the shift to a startup mentality

  25-04-2019 12:00
  Startups and enterprises think differently — and for good reason. A business with 10 employees can move much more quickly than one with 10,000. Enterprises often support vast troves of legacy systems and have an existing client base to serve. And though they typically have more money at their disposal, they get a bad rap for being rigid, less innovative, and prime for disruption.To read this article in full, please click here(Insider Story)
  
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• 4 critical roles for agile success

  25-04-2019 12:00
  Agile development and delivery methodologies can help organizations improve product quality, accelerate time-to-market and increase customer satisfaction. In fact, making the switch to agile can provide a significant competitive advantage in the digital age.To read this article in full, please click here(Insider Story)
  
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• BrandPost: Enterprise AI: Diving into Machine Learning

  25-04-2019 02:25
  In the first article in this series, we highlighted some of the motivations for using artificial intelligence in the enterprise to better understand the present and predict the future.1 In the second article, we provided descriptions of data analytics, data science, machine learning and deep learning.2 In this article, we continue with a practical description of machine learning and, in our follow-on article, we will do the same for deep learning, a subset of machine learning.To read this artic
  
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