Executives in various industries are facing pressure to quickly gather insights and make decisions. Streaming data and analytics are becoming increasingly important in enabling informed decisions that lead to faster and better outcomes.
Traditional systems handle data in batches, while streaming data continuously flows from multiple sources. Data streaming involves capturing and processing data at different speeds, depending on business needs. Contrary to common belief, streaming does not always have to be in milliseconds; it can range from seconds to hours.
Data streaming comes with challenges, such as ingesting data from various sources at low latency. Organizations must balance latency and cost to derive value from data.
Industry leaders are turning to Snowflake’s solution, which combines streaming and batch pipelines in a single layer of architecture. By centralizing data on a single platform with Snowflake and partners like AWS, organizations can achieve cost-effective streaming.
An Industry View of Streaming Use Cases and Architectures
In the ebook “The Modern Data Streaming Pipeline,” Snowflake explores common streaming use cases and architectures across sectors like financial services, manufacturing, healthcare, cybersecurity, retail, advertising, and telecommunications.
For example, in manufacturing, data streaming helps companies gather critical information from the value chain, such as sensor data, inventory levels, and customer demand. This data flow enables manufacturers to create new revenue streams, cut costs, and improve product quality.
A reference architecture for IoT analytics in manufacturing is shown below:
Smart devices and sensors generate continuous data, which is communicated using IoT protocols like MQTT. A streaming service can ingest real-time data and Snowpipe Streaming ensures reliable delivery to Snowflake.
Snowflake’s Streams and Tasks automate workflows to aggregate incoming data, with Dynamic Tables enabling incremental processing. Snowpark can enrich and validate data for transformation and machine learning training.
Manufacturing partners like DXC, Infosys, Kipi, and LTI offer integrated IoT solutions with Snowflake’s streaming capabilities.
Customers across various industries are leveraging Snowflake for streaming analytics, from retail personalization to medical IoT device ingestion. Recommended reference architectures can optimize performance for these use cases.
To learn how organizations are benefiting from Snowflake for streaming analytics in your industry, download the ebook “The Modern Data Streaming Pipeline: Top Streaming Architectures and Use Cases Across 7 Industries.”
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