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
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
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
Big data promises valuable insights that are enticing organizations to invest in analytics and BI tools. Yet many overlook the need for a DBMS that can stand up to the strain big data places on the underlying infrastructure. This ePaper explores the DBMS characteristics of most importance in a big data setting.
You need a database designed to control both the infrastructure and personnel costs that form the IT budget. The next generation of IBM DB2 helps organizations get more value from their big data to improve their IT economics. Major innovations provide out-of-the-box performance gains that go beyond the limitations of in-memory-only systems to support decision making at the speed of business.
Today’s data-driven organizations are faced with magnified urgency around data volume, user needs, and compressed decision time frames. In order to address these challenges while maintaining an effective analytical culture, many organizations are exploring cloud-based environments coupled with powerful business intelligence (BI) and analytical technology to accelerate decisions and enhance business performance.
Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of big data. Learn more about how big data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs.
This Aberdeen research report examines the decision-making benefits of real-time visualization and explores the technologies that help live data drive superior performance.
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