Creating a temporary data solution, Building a slowly DP-203 evolving dimension, Building a logical folder structure, Building external tables, Implementation of file and folder structures for efficient data querying and pruning, Implementing the service layer, Data delivery in a relational star schema, DP-203 exam dumps Data delivery in Parquet files, Maintain metadata, Implementing a dimensional hierarchy, Design and develop data processing – (25%-30%)
This part is divided into four subareas shown below.
Ingest and transform data, Data transformation using Apache Spark, Data transformation using Transact-SQL, Data transformation using DP-203 dumps Data Factory, Data transformation using Azure Synapse Pipelines, Data Transformation Using Stream Analytics, Data Cleaning, Split data, JSON shredding, Data encoding and decoding.,
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