Big Data Analytics White Papers
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Among 18 vendors, Dell Statistica tied for second place with IBM and SAS. See the detailed comparisons in this easy-to-read buyers' guide.
Sponsored By Dell Software
Hadoop enables organizations to extract valuable insight from large volumes of structured, unstructured, and semi-structured data. The need for large, up-front investments and concerns about flexibility, coupled with special challenges involved in evaluating the technology and developing Hadoop skills, often prevent organizations from adopting and deploying Hadoop across the enterprise. It also becomes impractical to use Hadoop on an occasional basis for high-impact projects that do not have a need for continuous processing. There is good news, though. You can overcome these capital requirements barriers through cloud computing.
Sponsored By IBM
Big data exploration addresses the needs of organizations at multiple points in their big data journeys. In the initial stages it enables them to gain secure access to all of their data and develop a full awareness of the available data and potential value across many different silos and locations. Using IBM Watson Explorer, organizations can discover and tag relevant data and understand key relationships within the data, and develop hypotheses for further analysis. In addition, this solution forms the foundation for applications that connect employees with all of the data and analytics they need at the point of impact, to improve customer engagement and accelerate innovation.
Sponsored By IBM
Big data is often portrayed as a big-ticket IT endeavor within reach of only the largest enterprises. However, tools have come to market that can substantially reduce costs, and organizations have also identified that big data can lead to direct benefits such as reduced data warehouse costs. While examining the data landscape, this white paper argues that these obstacles can be overcome and a sound business case for big data adoption be built.
Sponsored By Talend
As data extraction, transformation, and loading (ETL) becomes increasingly costly and difficult to scale, you'll need a lower cost alternative that can scale to manage increasing data volumes while maximizing investments in existing technologies.
Sponsored By MapR
Enterprises can gain serious traction by taking advantage of the scalability, processing power, and lower costs that Hadoop 2.0/YARN offers. YARN closes the functionality gap by opening Hadoop to mature enterprise-class data management capabilities. With a lot of data quality functionality left outside of Hadoop 1, and a lot of data inside HDFS originating outside the enterprise, the quality of the data residing in the Hadoop cluster is sometimes poor.
Sponsored By RedPoint Global
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.
Sponsored By Cloudera
Analysts are working with more and bigger data sets than ever before. In addition, the amount of data sources they need to access continues to expand. While Microsoft Excel readily solves many ad hoc needs, it does not fit the data blending and advanced analytic capabilities that analysts require today.
Sponsored By Alteryx