As increasing data volumes are being generated and stored in the cloud, enterprises are rethinking their strategies for big data processing and analytics. Driven by the business imperative of unlocking the value of their data to derive new business value, data and analytics teams are advancing this fundamental building block: how to store and process data as efficiently as possible.
Migrating data processing and analytics workloads to the cloud is easier said than done, however—especially with multiple cloud providers and data processing approaches to choose from, as well as ongoing investment in on-premises data processing and analytics resources.
In this webinar, Matt Aslett, Research VP at 451 Research and Ramesh Menon, VP Products, Infoworks will discuss key considerations for successful big data analytics in the cloud, including:
The trend towards data processing and analytics cloud services
Benefits and challenges of data processing in the cloud
Hybrid/multi-cloud and distributed data processing
Execution venue decision-drivers and cloud migration options
Migrating from cloud to cloud and maintaining portability
The separation of compute and storage
Big data processing options and trends—including Hadoop vs. Spark
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