Get More Value out of Multiple Hadoop Data Centers - Hosted by O'Reilly Media

WANdisco

For businesses that depend on Hadoop for critical operations, secondary clusters are commonly used for backup, sitting idle while the primary cluster handles the workload. In this webcast, we'll examine how to get the most out of your multi-data center Hadoop investment.Topics include: Understanding how secondary data centers are typically set up and what role they play Maximizing hardware utilization by running jobs in multiple data centers. How to efficiently split tasks between clusters
Watch Now

Spotlight

Apache Spark is a powerful, scalable real-time data analytics engine that is fast becoming the de facto hub for data science and big data. However, in parallel, GPU clusters are fast becoming the default way to quickly develop and train deep learning models. As data science teams and data savvy companies mature, they will need to invest in both platforms if they intend to leverage both big data and artificial intelligence for competitive advantage.


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Get More Value out of Multiple Hadoop Data Centers - Hosted by O'Reilly Media

WANdisco

For businesses that depend on Hadoop for critical operations, secondary clusters are commonly used for backup, sitting idle while the primary cluster handles the workload. In this webcast, we'll examine how to get the most out of your multi-data center Hadoop investment.Topics include: Understanding how secondary data centers are typically set up and what role they play Maximizing hardware utilization by running jobs in multiple data centers. How to efficiently split tasks between clusters
Watch Now

Building a Big Data Fabric with a Next Generation Data Platform

BrightTALK

For more than 25 years IT organizations have spent many cycles building enterprise data warehouses, but both speed to market and high cost has left people continually searching for a better way. Over the last 10 years, many found an answer with Hadoop, but the inability to recruit skilled resources, combined with common enterprise necessities such as ANSI compliant SQL, security and the overall complexity has Hadoop relegated to an inexpensive, but scalable data repository.
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Geospatial Analytics with Big Data: Five Steps for Creating Business Value

Organizations can gain powerful, actionable insights by combining maps, geographical data, and relevant “big data” sources such as customer behavior or sensor data. Leading firms in a variety of industries—including retail, real estate, energy, telecommunications, land management, and law enforcement—are today engaged in projects involving geospatial analytics, and broader interest is growing. TDWI Research, in a recent survey on emerging technologies, found that the number of respondents who stated that they would be using geospatial analytics will double over the next three years.
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Big Data Analytics

MicroStrategy

NoSQL sources, such as Hadoop, are growing in popularity among large organizations. MicroStrategy lets these organizations connect to their entire data ecosystem - including big data sources - as if it were a single database. With easy access to structured and unstructured data, organizations can analyze large datasets of any type and maximize the value of these investments. Watch the webcast to learn how to take control of NoSQL data using MicroStrategy.
Watch Now

Spotlight

Apache Spark is a powerful, scalable real-time data analytics engine that is fast becoming the de facto hub for data science and big data. However, in parallel, GPU clusters are fast becoming the default way to quickly develop and train deep learning models. As data science teams and data savvy companies mature, they will need to invest in both platforms if they intend to leverage both big data and artificial intelligence for competitive advantage.

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