Creating a temporary data solution, Building
DP-203 a slowly 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, 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
DP-203 exam dumps below.
Ingest and transform data, Data transformation using Apache Spark, Data transformation using Transact-SQL, Data transformation using Data Factory, Data transformation using Azure Synapse Pipelines, Data Transformation Using Stream Analytics, Data Cleaning, Split data, JSON shredding, Data encoding and decoding.,
Error configuration and transformation
DP-203 dumps management., Normalization and denormalization values., Data transformation using Scala, Perform exploratory data analysis., Design and develop a batch processing solution., Develop batch processing solutions using Data Factory, Data Lake, Spark, Azure Synapse Pipelines, PolyBase, and Azure Databricks.
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