- Zetaris Support - Knowledge Base
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Zetaris Overview
The Zetaris Modern Lakehouse for AI, is a single converged view of all AI and data operations streamlining data management and simplifying data processes.
By connecting to any data (structured, semi-structured and unstructured), anywhere, we deliver a Modern Lakehouse, that facilitates data integration, preparation and governance, reducing software complexity, and allowing businesses to accelerate their AI & Analytics projects, in the cloud or on-prem.
Structured Data
Structured data is prepared in a standardized format, such as columns and rows. Fairly straight forward to process through ANSI SQL and other basic analytic constructs. Common in transactional record keeping, customer profiling, and historical stores of record for ad-hoc reporting.
Examples: Relational Databases, Data Warehouses, CSV
Semi-structured Data
Semi-structured data doesn't have the strict, predefined format of structured data but still has some organizational properties, such as tags or markers that help define the data's structure. It’s often more flexible and can accommodate varying types of data.
Examples: JSON, XML, NoSQL Databases, Data Lakes (Parquet and Avro), Data Streams, REST APIs
Unstructured Data
Unstructured data does not have a predefined format nor organizational properties to decipher the contents.
Examples: PDFs, Images, Video, Audio