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Added information on Dataflow

Data-streaming/gcloud-dataflow.md

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+## Google Cloud Dataflow
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+Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem.
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+Benefits:
+- Streaming data analytics with speed: Dataflow enables fast, simplified streaming data pipeline development with lower data latency.
+- Simplify operations and management: Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads.
+- Reduce total cost of ownership: Resource autoscaling paired with cost-optimized batch processing capabilities means Dataflow offers virtually limitless capacity to manage your seasonal and spiky workloads without overspending.
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+Features:
+- Autoscaling of resources and dynamic work rebalancing: Minimize pipeline latency, maximize resource utilization, and reduce processing cost per data record with data-aware resource autoscaling. Data inputs are partitioned automatically and constantly rebalanced to even out worker resource utilization and reduce the effect of “hot keys” on pipeline performance.
+- Flexible scheduling and pricing for batch processing: For processing with flexibility in job scheduling time, such as overnight jobs, flexible resource scheduling (FlexRS) offers a lower price for batch processing. These flexible jobs are placed into a queue with a guarantee that they will be retrieved for execution within a six-hour window.
+- Ready-to-use real-time AI patterns: Enabled through ready-to-use patterns, Dataflow’s real-time AI capabilities allow for real-time reactions with near-human intelligence to large torrents of events. Customers can build intelligent solutions ranging from predictive analytics and anomaly detection to real-time personalization and other advanced analytics use cases. 
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+For more info: [https://cloud.google.com/dataflow](https://cloud.google.com/dataflow)