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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility. Pipelining.

Big Data 154
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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 187
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Driving down the cost of Big-Data analytics - All Things Distributed

All Things Distributed

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 111
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How Our Paths Brought Us to Data and Netflix

The Netflix TechBlog

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. benefit more?

Analytics 223
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.

Big Data 321
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Expanding the Cloud: Introducing the AWS Asia Pacific (Mumbai) Region

All Things Distributed

AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift. Advanced problem solving that connects big data with machine learning. warehouses to glean business insights for jobs, ad spend, or financials for mobile apps.

AWS 90
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Cloud-Based Testing – A tester’s perspective

Testsigma

However, the primary goal of traditional testing and cloud-based testing remains the same i.e., to deliver high-quality and efficient software. May pose security issues, since the data is handed over to a third party during testing. Requires very good internet connectivity. Limited control and dependency on the service provider.

Cloud 67