Apache Hadoop News
May 12, 2017
Kafka is a linchpin in many on-premises data pipelines. Now, Confluent has a Kafka cloud service to ease this distributed system's ascent to cloud nirvana.
April 20, 2017
Corporate users are becoming more open to deploying big data systems with Apache Spark in the cloud, Databricks CEO Ali Ghodsi says in a Q&A on the open source processing platform.
April 19, 2017
It used to be the Hadoop Summit, but the strategic focus at Hortonworks the enterprise-ready open source Apache Hadoop provider, has evolved. So, this year it was renamed DataWorks Summit. The ...
March 31, 2017
Fitness company Beachbody set up a data lake system in the AWS cloud to support big data analytics applications after deciding an on-premises deployment would be too complicated.
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Big data analytics is the process of examining large and varied data sets -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. Continue Reading
The desire to accelerate operational decision-making processes is leading organizations looking for a competitive edge to deploy streaming analytics platforms fed by real-time data. Continue Reading
Big data architectures typically involve multiple processing platforms. In this essential guide, you'll find information and advice on managing Hadoop, Spark and other big data technologies. Continue Reading
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Real-time analytics applications typically involve multiple streams of data that need to be properly organized and coordinated, a job that calls for new message queuing technologies. Continue Reading
Gartner analyst Merv Adrian discusses why organizations often have trouble with deployments of Hadoop-based big data architectures, and how to avoid the challenges they pose. Continue Reading
Cloud had a big impact on big data management and analytics last year. Machine learning and streaming designs will contribute to change in 2017. Continue Reading
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Experienced users of machine learning tools share how their organizations are using the technology to solve a variety of analytics problems in their businesses and for customers. Continue Reading
The big data ecosystem has many twists and turns. A McKesson data manager saw Splice Machine's database as a means to straighten the path by putting analytics and operations data in one place. Continue Reading
Apache Mesos has become popular with major enterprises for its ability to scale linearly, reduce wasteful resource consumption and abstract storage, CPU and memory. Continue Reading
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Hadoop coding oversights can wreak havoc on big data projects. What Hadoop limitations should we be wary of with data input and output? Continue Reading
The challenges encountered in deriving business benefits from big data are huge, but so are the rewards. Hadoop and related technologies are easing those challenges to the point where companies are willing to graduate from experimental to full-blown big data analytics deployments. Still, the march toward that goal can be long and arduous, and not just from a technological and architectural standpoint. Before taking the plunge, big data users, including data scientists, managers and evangelists, are faced with the sometimes monumental task of justifying big data's return on investment to business executives focused on competition, profit margins and allocation of funds. "For a lot of organizations like ours, big data has not yet become a core foundation of running the business," said Beata Puncevic, director of analytics, data engineering and data management at Blue Cross Blue Shield of Michigan. Yet, actionable insights gained from big data analytics can be indispensable in driving revenue, reducing costs and developing new products.
This handbook on big data analytics examines the trials and tribulations of big data users who are on the front lines, devising and implementing partial and full-blown applications. In the first feature, editor Craig Stedman interviews battle-tested IT and analytics warriors from Blue Cross, Macy's and Progressive Insurance who reveal the business challenges in justifying the worthiness of big data applications. In the second feature, Stedman explains how real-time big data analytics is helping companies like Comcast and eBay to move quickly on massive amounts of incoming information. And in the third feature, reporter Ed Burns spotlights the decisions at Neilsen and Nasdaq to run or not to run big data systems in the cloud.Continue Reading
Hadoop and all the related technologies surrounding it enable organizations to design big data environments that meet their specific needs. But putting everything together isn't easy. Continue Reading