Mastering Databricks & Apache spark -Build ETL data pipeline

Posted in: Tutorials | By: AD-TEAMSSS | 8-01-2022, 20:27 | 0 Comments
08
January
2022

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 47 lectures (4h 23m) | Size: 2.18 GB

Learn fundamental concept about databricks and process big data by building your first data pipeline on Azure

Databricks
Build your first data pipeline to process CSV, JSON, XML
Orchestrate data pipeline on Azure data factory
Spin up spark cluster
Delta tables
Concept of travel and vacuum on delta tables
Apache Spark SQL
Filtering Dataframe
Renaming, drop, Select, Cast
Aggregation operations SUM, AVERAGE, MAX, MIN
Rank, Row Number, Dense Rank
Building dashboards
Build Complete project
Build End to End data pipeline

There are no pre requisites with this course

Welcome to the course on Mastering Databricks & Apache spark -Build ETL data pipeline
Databricks combines the best of data warehouses and data lakes into a lakehouse architecture.


In this course we will be learning how to perform various operations in Scala, Python and Spark SQL. This will help every student in building solutions which will create value and mindset to build batch process in any of the language. This course will help in writing same commands in different language and based on your client needs we can adopt and deliver world class solution. We will be building end to end solution in azure databricks.
Key Learning Points
We will be building our own cluster which will process our data and with one click operation we will load different sources data to Azure SQL and Delta tables
After that we will be leveraging databricks notebook to prepare dashboard to answer business questions
Based on the needs we will be deploying infrastructure on Azure cloud
These scenarios will give student 360 degree exposure on cloud platform and how to step up various resources
All activities are performed in Azure Databricks
Fundamentals
Databricks
Delta tables
Concept of versions and vacuum on delta tables
Apache Spark SQL
Filtering Dataframe
Renaming, drop, Select, Cast
Aggregation operations SUM, AVERAGE, MAX, MIN
Rank, Row Number, Dense Rank
Building dashboards
Analytics
This course is suitable for Data eeers, BI architect, Data Analyst, ETL developer, BI Manager

Data eeer
People who are interested in build End to End ETL data pipeline
Learn fundamentals commands in Python, Apache Spark SQL, Scala




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