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    The Hadoop Challenge for Business Intelligence and Analytics Users

    Traditional data management and business analytics tools and technologies are straining under the added weight of Big Data, but new approaches are emerging to help enterprises gain actionable insights from Big Data. More and more organizations are looking to deploy Hadoop with aspirations for great success. However, business intelligence and application users who are not Hadoop specialists may find their lack of knowledge and tools initially limit them from achieving the full potential of Hadoop. Overcoming these hurdles is critical if Hadoop is to evolve from a pilot project to mainstream adoption.

    This slideshow, from Zettaset, is intended to provide answers to the concerns that business intelligence and analytics users may have when considering Hadoop. It will also discuss the advantages and disadvantages of using Hadoop as a data store, and how the disadvantages will be mitigated as new technologies emerge to assist the enterprise with Big Data initiatives.

    The Hadoop Challenge for Business Intelligence and Analytics Users - slide 1

    Click through for more on Hadoop challenges and how businesses can overcome them, as identified by Zettaset.

    The Hadoop Challenge for Business Intelligence and Analytics Users - slide 2

    Big Data’s challenge and promise       

    Eighty percent of today’s accumulated data is unstructured. The influx of Big Data and the need to move this information throughout an organization and distill value from it has created a massive opportunity. This will not be an easy task for enterprises. However, those organizations that take what was once considered unusable data can glean critical insights for the business that were previously unattainable.

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    The Hadoop cluster

    Hadoop users access unstructured and semi-structured data from multiple sources including log files, social media feeds, sensors and internal data stores. Instead of storing this Big Data on one centralized database management system, Hadoop distributes the data across multiple machines arranged into a cluster. The cluster consists of commodity servers, which makes Hadoop relatively inexpensive to scale to Petabyte levels when compared to traditional database technologies.

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    The benefits of the Hadoop cluster

    Because a Hadoop cluster is optimized for data that is highly distributed, loosely structured, and increasingly large in volume, it is ideal for processing Big Data. Organizations that undertake the task and embrace Big Data as the foundation of their business analytics practices stand to gain significant competitive advantage over their rivals.

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    Why faster time-to-value is a factor

    As with any emerging technology, implementing and managing Hadoop clusters and performing advanced analytics on large volumes of unstructured data requires significant expertise. The good news is that innovative technology vendors are working to offer commercial, enterprise-ready Hadoop tools and applications that help automate deployment in a production environment. The faster you can deploy, the faster you can derive value from the data.

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    The access control hurdle

    Business intelligence users looking to access data from the cluster may be doing so while breaking the rules. For instance, in some cases specific data cannot be accessed without first having permission to the information and users could be unknowingly violating such terms.

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    The learning curve

    One of the most pressing barriers of adoption for Big Data in the enterprise is the lack of skills around Hadoop administration and Big Data analytics skills, or data science. Fortunately, specialized vendors are developing easy-to-use Big Data administration and analytic tools and technologies that reduce complexity and automate routine tasks, and lower the barrier to entry for business intelligence professionals.

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    The security conundrum

    Incumbent data security vendors believe that Hadoop and distributed cluster security can be adequately addressed with traditional perimeter security solutions such as firewalls and intrusion detection/prevention technologies. However, these approaches lack effectiveness in Hadoop’s distributed architecture. Simply bypassing perimeter security enables open access to cluster data. For this reason, security should be integrated into the Hadoop cluster environment.

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    Addressing the security, reliability, and usability gaps

    The potential benefits of using Hadoop far outweigh the challenges that IT and business intelligence professionals now face. Big Data and the insights gained from it are becoming the new definitive source of competitive advantage across all industries. Vendors that can help enterprises address Hadoop’s security, reliability, and useability gaps are building software to do just that, positioning 2014 as a breakout year for Hadoop in the enterprise.

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