News

News

• September 01, 2016 01 Sep'16

  Data science industry eyes machine learning, recommendation engines

  Data scientists need to add new tech skills and business savvy to their bags of tricks. Next up are machine learning and recommendation engines.

• August 30, 2016 30 Aug'16

  Low-code integration application melds data from disparate SaaS apps

  When customers wanted to track their accounts via a mobile app, New York's IDB Bank responded with a low-code integration application that didn't change a thing.

• August 22, 2016 22 Aug'16

  Combine data science education with curiosity and business savvy

  There's more to a good data scientist than just data science education. It takes curiosity, persistence, business savvy and a good working partnership with app developers.

• August 10, 2016 10 Aug'16

  Digital migration ultimatum advises the time for change is now

  In its 'digital ultimatum,' Progress Software advises executives and IT to work together in planning for enterprise digital migration jointly or risk falling behind.

• July 27, 2016 27 Jul'16

  Event planner simplifies operations with low-code development tools

  Staging arena events means coordinating thousands of tasks and several budgets. Solomon Group ousts piecemeal systems for a single service build with low-code development tools.

• Sponsored News

  • Cloud Governance Doesn’t Have to Be a Resource Drain: The Benefits of Automated Policy Management

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  • Removing Barriers to Moving Mission-Critical Apps to Public Cloud

    Sponsored by IBM - Enterprise IT decision-makers predict that more than 40% of their workloads will be running on public cloud platforms by 2020. The question is not whether to move apps to the public cloud; it is more about which apps to move and how to move them without risk. See More

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• July 11, 2016 11 Jul'16

  Providing a common language for dev and ops

  At Red Hat Summit, Ansible playbooks look to find common ground between dev and ops teams.

• July 06, 2016 06 Jul'16

  Best practices for private cloud deployment

  Find out how the world's largest betting site, Paddy Power Betfair, leveraged a private cloud to accelerate application delivery.

• July 06, 2016 06 Jul'16

  What EA learned about building successful mobile app infrastructure

  Find out what Electronic Arts learned from a failed effort and one successful strategy for deploying cloud infrastructure for mobile apps.

• July 06, 2016 06 Jul'16

  Multiple screen sizes create mobile app challenges

  In nine years, app downloads went from zero to 225 billion. Yet, multiple device types, screen sizes and operating systems still spark lingering mobile app challenges.

• June 27, 2016 27 Jun'16

  Red Hat explains its acquisition of API management tools maker 3scale

  Enterprise-class API management tools are central to cloud application development and integration. Red Hat is acquiring 3scale to fill a glaring gap in its product line.

• June 24, 2016 24 Jun'16

  What 3D integration means for the enterprise

  Autodesk has rearchitected its core technologies for design to work in the cloud. Learn what 3D integration means for the future of enterprises.

• June 23, 2016 23 Jun'16

  How 3D data integration can streamline the supply chain

  Learn how enterprises can leverage 3D data integration in the cloud to improve communication across supply chains and improve sales.

• June 22, 2016 22 Jun'16

  Scalable systems monitoring helps developers build better apps faster

  Developers want to create better apps faster. Static clouds are giving way to scalable systems, with dynamic resource allocation and application monitoring.

• June 17, 2016 17 Jun'16

  Best practices for moving big data apps into production

  What's the best way to prepare big data apps to be production-ready? Amazon engineer Marvin Theimer had the answer at Spark Summit. Expert George Lawton discusses this further.

• June 16, 2016 16 Jun'16

  Data currency demands differing storage strategies

  Storage strategies should handle data differently, depending on its age, a phenomenon known as data currency. Know when your data transitions from new and hot to old and cold.