Analytics Architecture Architecture Data Preparation 
ThoughtSpot
APRIL 22, 2025
While foundational models like GPT are trained for natural language, they cant accommodate every complexity of real-world data on their ownthink: business context, analytics expressibility, massive and messy datasets. Thats where ThoughtSpots architecture comes in.
Edureka
FEBRUARY 7, 2023
Data entry into PDW is optimized by Polybase, which also supports T-SQL. It allows developers to query external data from supported data stores transparently, regardless of the storage architecture of the external data store. 7) Describe the Azure Synapse Analytics architecture.
Towards Data Science
MAY 22, 2023
Solving data preparation tasks with ChatGPT Photo by Ricardo Gomez Angel on Unsplash Data engineering makes up a large part of the data science process. In CRISP-DM this process stage is called “data preparation”. It comprises tasks such as data ingestion, data transformation and data quality assurance.
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