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NEW Data Engineering Integration for Developers

  • Instructor Led
  • Data Engineering
  • 3 Days

This course is applicable for software version 10.4.0. Learn to accelerate Data Engineering Integration through mass ingestion, incremental loads, transformations, processing of complex files, creating dynamic mappings, and integrating data science using Python. Optimize the Data Engineering system performance through monitoring, troubleshooting, and best practices while gaining an understanding of how to reuse application logic for Data Engineering use cases.

Course Overview & Agenda

Objectives

After successfully completing this course, students should be able to:

Mass ingest data to Hive and HDFS

Perform incremental loads in Mass Ingestion

Perform initial and incremental loads

Integrate with relational databases using SQOOP

Perform transformations across various engines

Execute a mapping using JDBC in Spark mode

Perform stateful computing and windowing

Process complex files

Parse hierarchical data on Spark engine

Run profiles and choose sampling options on Spark engine

Execute Dynamic Mappings

Monitor logs using REST Operations Hub

Monitor logs using Log Aggregation and troubleshoot

Run mappings in Databricks environment

Create mappings to access Delta Lake tables

Tune performances of Spark and Databricks jobs

Target Audience

Developer

Available Languages

English

Prerequisites

Informatica Developer Tool for Big Data Developers (Instructor Led OR onDemand)

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