From the course: Microsoft Fabric Analytics Engineer Associate (DP-600) Cert Prep by Microsoft Press

Unlock this course with a free trial

Join today to access over 25,400 courses taught by industry experts.

Store and manage semi-structured data in lakehouses

Store and manage semi-structured data in lakehouses - Microsoft Fabric Tutorial

From the course: Microsoft Fabric Analytics Engineer Associate (DP-600) Cert Prep by Microsoft Press

Start my 1-month free trial Buy for my team

Store and manage semi-structured data in lakehouses

“

- [Instructor] Storing and managing semi-structured data in Fabric Lakehouse involves handling data like JSON, XML, or Avro files that don't fit into traditional databases. Then Lakehouse stores this data in its native format without a predefined schema, allowing flexible data ingestion. Using Schema-on Read approach, the schema is applied when the data is read, enabling adoption to evolve data structures. Tools like Apache Spark and SQL Query Parser transform and analyze semi-structured data, converting it into structured format or performing complex transformations as needed. The Lakehouse also ingests semi-structured data with a structured data from relational tables for comprehensive analysis and reporting. Designed for scalability, the Fabric Lakehouse efficiently manages the large volume of semi-structured data along with structured data, offering a robust environment for comprehensive data insight.

Contents