Reports

  • Gartner: Liberate Applications for Migration by Disentangling Data

    Data and analytics leader often struggle to guide cloud migration — "It is because isolated application design or insular business process approaches fail to recognize the mutable and highly mobile nature of data."Local design decisions build up over time. Gradually their associated data becomes increasingly "entangled" and accumulates "technical debt" as data management principles fail to adhere to broader governance and design demands — so it is important to mitigate data entanglement as systems are integrated in hybrid cloud and on-premises environments.Read this Gartner report to:

    • Learn how data becomes entangled and why it’s crucial to resolve it
    • Enable data and application mobility by "disentangling" data, which involves overcoming "data gravity"
    • Get a better understanding of data gravity to gauge and prioritize data migration efforts

  • O’Reilly: The culture of big data

    The Culture of Big Data describes the cultural challenges that accompany efforts to create and sustain big data initiatives in an evolving world rooted firmly in data warehouse architectures.

  • Think Big: Britain's Data Opportunity

    Every organization cares about minimizing risk and maximizing opportunity – and financial services providers are no exception to this rule. We believe financial services firms that use Big Data analytics efficiently and effectively will thrive in uncertain and fluctuating markets, while those who resist are likely to flounder.

  • Forrester research: the total economic impact of WANdisco SVN multisite

    A Forrester Total Economic Impact (TEI) report revealed a 357% ROI and payback period of 9 Months for WANdisco's Subversion MultiSite. The Forrester TEI report highlights significant benefits and cost-savings for companies deploying Subversion MultiSite.

  • Gigaom Research: Selecting a platform for Big Data

    This report cuts out all the noise about Hadoop and presents a minimum viable product (MVP) for building an enterprise Hadoop cluster. This approach gets the cluster up and running fast and will ensure that it scales and performs to the enterprise's needs. On-prem and cloud deployment options are covered.