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A new angle on analytics architectures

Consequent of the surpluses of data an average analytics-driven business in the modern age absorbs and stores - a singular data warehouse is no longer sufficient.

The data warehouse isn’t dead - but it does need a more extensive architecture in order to rival other analytics methods.

Read this white paper to learn how an extended data warehouse architecture can combine with a modern data warehouse appliance to achieve real-time analytics results you desire.

These are also closely related to: "Advances in Data Warehouse Performance"

  • Adapting the cloud for new data and analytics demands

    56% of large and midsize organizations in the US have at least one data warehouse or data mart deployed in the cloud, according to an IDC survey.

    If that includes your organization, then you’re likely assessing cloud as a deployment option for analytic databases – including relational data warehouses.

    Before determining if a cloud data warehouse is appropriate, though, read this white paper to learn why cloud deployment is a great way to approach these current juggernaut business strategies.

  • How are you handling operational data?

    Many organizations incorporate both operational data stores and data warehouses in their analytics architectures – but in order to get the most out of both, you need to understand their distinct differences. When it comes to operational data, one cannot be used without the other.

    This is why we’ve created a complimentary guide for you, Expert Guide: Storing Operational Data, where our executive editor Craig Stedman breaks down the differences between data stores, data warehouses and even data marts.
    In addition, this guide breaks down the leading operational DBMS options, including IBM, Microsoft and Oracle.

    This guide is ready to download, but first we ask that you complete a data management survey for us, so we can continue to grow as experts in the industry.

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