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Integrate Datastreamer Dialect Detection Model into Azure Blob Storage
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Datastreamer Dialect Detection Model
Detect dialects of language used within content for over 200+ languages. This classifier can instantly consume the content within a pipeline, optimize the content for speed and cost efficiency, and pass into LLM systems. Within the classifier, the LLM response is restructured, the post is augmented with the new metadata, and continues in the pipeline.
About Azure Blob Storage
Direct data ingestion from Azure blog storage into your pipeline.
Quickly connect Datastreamer Dialect Detection Model and Azure Blob Storage with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Datastreamer Dialect Detection Model
To support enterprise-scale data integration, pipelines must ingest web data from varied origins, including trusted partners, internal databases, and external web-based assets.
Step 2
Transform, and then add Azure Blob Storage
Datastreamer lets you accelerate your data usage by applying operations like structuring, enriching, joining, and filtering—choose from hundreds of prebuilt, plug-and-play options.
Step 3
That's it! You have just connected Datastreamer Dialect Detection Model and Azure Blob Storage
Supercharge your data workflows with Datastreamer. Add flexibility to your Pipelines and put an end to the common bottlenecks in handling web data.