Data Quality refers to the quality of data. Data are of high quality "if they are fit for their intended uses in operations, decision making and planning" (J.M. Juran). Alternatively, the data are deemed of high quality if they correctly represent the real-world construct to which they refer. These two views can often be in disagreement, even about the same set of data used for the same purpose.
This national children's hospital relies on a big data platform to better understand its patients, their conditions, and the quality of care they receive in support of its mission: to make kids better today and healthier tomorrow.
The most direct path to making Big Data -- and Hadoop -- a first-class citizen will be through an "embrace and extend" approach that not only maps to existing skill sets, data center policies and practices, and business use cases, but also extends them.
For an implementation of its size, Western Union anticipated going from “zero to Hadoop” in about a year. Exceeding expectations, “We had our first production-ready Cloudera system up within just five months,” commented Saraf. “We were actually leveraging it for some of our transactional processing, and saw immediate value.”
Cloudera has been included as a Challenger in Gartner's 2015 Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics, following last year’s debut as the only included pure-play Hadoop distribution vendor.
Dell has teamed with Intel to create innovative solutions that can accelerate the research, diagnosis and treatment of diseases through personalized medicine. The combination of leading-edge Intel® processors and the systems and storage expertise from Dell create a state-of-the-art solution that is easy to install, manage and expand as required. Download to learn more.
Server virtualization is revolutionizing the datacenter by making applications mobile, increasing application uptime, and allowing IT admins to allocate computing resources more efficiently. The technology has been deployed widely enough that the role of the computer server has evolved from directly hosting operating systems and applications to hosting fully virtualized environments. Server that can support more virtualized machines (VMs - complete application stacks) allow their users to gain higher return on their IT investments. Private Cloud can extend the virtualization benefits in ways that broaden the benefits of virtualization to all parts of the organization. In this white paper, you will learn how Corporate IT uses these tools to meet the increasing demand for IT services.
By now, much has been written about the advantages server virtualization brings to an enterprise. In the June 2013 survey, 63% of all companies and 100% of large enterprises reported having a server virtualization program. However, when you
segment the virtualization rates, you find a trend that indicates that large enterprises in particular are not gaining all of the advantages that server virtualization has to offer.
What is more difficult and remains a challenge, particularly for large enterprises, is virtualizing Tier 1 applications. These are large, mission-critical enterprise applications such as email, customer relationship management (CRM), or enterprise resource planning (ERP). These applications tend to be very large,
consume the entire capacity of a current generation server, and require high application uptimes. As shown in Figure 1, the virtualization rates for these applications are far lower than Tier 2 apps. In this eBook, you’ll learn how the NEC enterprise server provides a platform that now gives customers the right platform to virtualize their Tier 1 apps.
As executives witness data’s proven impact on performance and innovation and recognize its strategic significance, they also realize the growing need for a leader whose primary role is to understand and advocate on behalf of data: The Chief Data Officer.
While collecting marketing data is easy, that data is not cast in stone. Securing a marketing data management plan that you can rely on is imperative. This guide provides actionable steps to clean up your data and increase conversions.
The solution to operationalizing analytic s involves the effective combination of a Decision Management approach with a robust, modern analytic technology platform. This paper discusses both how to use a focus on decisions to ensure the right problem gets solved and what such an analytic technology platform looks like.