From the course: Azure Solutions Architect Expert (AZ-305) Cert Prep: Design Data Storage Solutions

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Design for stream processing, data science, and ML

Design for stream processing, data science, and ML - Azure Tutorial

From the course: Azure Solutions Architect Expert (AZ-305) Cert Prep: Design Data Storage Solutions

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Design for stream processing, data science, and ML

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- [Instructor] When architecting a design for stream processing and ingesting time series or log data, analytic requirements are likely to be near real time and run over huge amounts of data. A near time solution requires a hot path and data ingested with low latency and high throughput. The ingested data must be processed, aggregated, and analyzed and presented as aggregated models for consumption through reporting and dashboards. These also need to be in near real time. Azure Data Explorer can ingest terabytes of data within minutes in streaming mode and query petabytes of data in seconds. Azure Data Explorer is a full solution for data ingestion, querying, and visualization. Returning to the Lander Architecture, but this time taken from the Azure documentation, the cold path was explored in an earlier video in this chapter where scheduled ingestion extracts data from various sources. In this example, IoT logs and business…

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