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How to escape the legacy storage bottleneck

Data-intensive sectors such as financial services, healthcare, and manufacturing require efficient data storage for informed decision-making and streamline business operations.

But traditional systems often lack agility, leading to resource and availability issues. Further, they don't work with 'as-a-service' models. They also can't support advanced data transformation.

Discover in this product overview how Pure Storage offers a solution to the data storage bottleneck with Evergreen//One, transforming your storage ecosystem into a highly efficient, subscription-based service.

These are also closely related to: "10 reasons to leverage FlashStack"

  • How to avoid the need to add new data center capacity

    As data continues to grow at 30% to 40% per year for most enterprises, more purchasing decisions will be biased towards efficient IT infrastructure that requires less hardware and uses less energy.

    Expanding beyond the floor space of existing facilities may be as easy as moving some workloads to the cloud and/or retiring others to make room for more critical workloads. But if neither of these options are feasible or they cannot clear enough space for critical new projects, then it is a very expensive step-function to acquire new data center capacity.

    Discover in this white paper the secrets to addressing data center power and space limitations while building towards more energy-efficient IT infrastructure.

  • Beyond the hype: How big data projects are delivering

    Big data is starting to look a bit dowdy, compared with gaudily dressed artificial intelligence/machine learning. And AI itself has been in and out of fashion for decades.

    However, whether they are in Gartner’s famous “plateau of productivity” phase or not, big data projects have been delivering business value, and many are now beyond hype.

    This Computer Weekly e-guide collates a group of examples of big data technologies in use.

    The lead article describes how Nesta, a charity set up by the government which supports public-sector innovation, has been working with the Greater London Authority and London boroughs to predict which properties might be HMOs (Houses in Multiple Occupation), to help council inspectors work more efficiently. This is a good case of data science, in the form of predictive data analytics, put to public use.

    The Met Office is home to some of the world’s biggest supercomputers, and handles a mind-boggling volume of data. Met Office Informatics Lab is using Amazon Web Services’ Snowball data transport appliance to store data that they then do data science work on, using the Jupyter Notebooks open source environment and Dask – a third-party parallel computing library for analytics.

    This e-guide also looks at how data analytics could help Mercedes-AMG Petronas Motorsport team gain an edge on rival Ferrari during Grand Prix season. And at how the Path health organisation is fuelling its anti-malaria programme in Zambia, and other African countries, with data analytics from Alteryx, Tableau, and others.

    It also examines how organisations are, concretely, managing their big data operations and their data analytics programmes and teams.

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