Examples of using Stream processing in English and their translations into Greek
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BASIC Interpreter- for data stream processing.
SAS Event Stream Processing helps customers analyze millions of events per second.
Other jobs related to stream processing use cases.
Use stream processing to provide a higher level of abstraction over messaging systems.
Other jobs related to stream processing use cases.
Stream Processing training is available as"onsite live training" or"remote live training".
Make any collected data available for stream processing.
The software for the video stream processing of various visual effects and transformation filters.
Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing.
Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
Capitalizing on thisopportunity will require innovation, like SAS Event Stream Processing, which gained tremendous traction in 2017.
Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously.
Integrate the most appropriate stream processing library with enterprise applications and microservices.
In this instructor-led, live training,participants will learn how to integrate Kafka Streams into a set of sample Java applications that pass data to and from Apache Kafka for stream processing.
Built on SAS Event Stream Processing, which analyzes data in motion by processing huge volumes at very high rates- with extremely low latency.
In this instructor-led, live training(onsite or remote), participants will learn how to set up andintegrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.
Overview Stream Processing refers to the real-time processing of"data in motion", that is, performing computations on data as it is being received.
This instructor-led, live training introduces the principles behind messaging systems and distributed stream processing, while walking participants through the creation of a sample Samza-based project and job execution.
Our proven event stream processing engine can handle huge volumes of data at very high rates(e.g., millions per second), with extremely low latency(in milliseconds).
The proposed research involves designing and developing the necessary big data infrastructure, which will form a comprehensive solution for( i) collecting and integrating data efficiently from various sources;( ii)enabling stream processing in real time;( iii) storing the data in a fault-tolerant way; and( iv) supporting machine learning and advanced analytical processing of data with the goal of extracting new meaningful insights and supporting decision-making activities for the maritime stakeholders.
Learn how event stream processing technology helps you acquire, understand and use real-time, streaming data to make fact-based, automated decisions.
DataTorrent develops its DataTorrent RTS realtime stream processing system, based on Hadoop 2.0, that businesses use to process, monitor, analyze and act on big data instantly.
Local, instructor-led live Stream Processing training courses demonstrate through interactive discussion and hands-on practice the fundamentals andadvanced topics of Stream Processing.
Through neural networks using SAS Event Stream Processing, the SAS facilities team will track sensors and systems performance in real time to enhance predictive maintenance(identifying equipment problems before they become major) and optimize energy and water usage.
Through a neural network that uses SAS Event Stream Processing, SAS administrative teams track real-time sensor information and the performance of these systems to improve estimates of required maintenance periods(system identifies possible equipment problems before they occur) and optimization water and energy consumption.
He and his colleagues defined a processing"stream" in speech perception that is hierarchical, and which moves increasingly to the front of the superior temporal gyrus.
The backbone of the system is the Pitney Bowes BLP software with CEN interface,which provides access to a real-time processing data stream for tracking, reporting and auditing.
Description: The need to reduce the gap between the generation of data andextraction of insights from these data has led to significant innovations for distributed stream data processing engines(DSPEs).
So, the over-run varies due to the different ice cream formulations and the processing streams.