Databricks Course Overview

Enrol for three-day Databricks training from The Edu Plus. This course is geared toward statistics Scientists, Analysts, software developers, architects, who are seeking to create and deploy cloud-primarily based information engineering answers. Databricks is used for processing and remodeling huge data, and exploring that information the usage of machine studying fashions. to be had as a Platform-as-a-provider on Microsoft's Azure and Amazon web services cloud platforms, it is a major competitor to BigQuery and Dataflow on Google Cloud Platform (GCP).  
Target Audience: Data Scientists Analysts Software Developers Database Developers Data Warehouse Managers and Business Intelligence Specialists Software Architects
 Module 1: Overview of Apache Spark and Databricks
  • How do we define Big Data?
  • Spark languages - Scala, Python, R, Java, SQL
  • Databricks Community Edition
  • Databricks Architecture
  • Defining Data Analytics
  • Defining Machine Learning
  • Azure implementation
  • AWS implementation
 Module 2: Databricks benefits
  • Integrating into Pipelines
 Module 3: Getting started with Databricks
  • Creating a Databricks Workspace on Azure
  • Creating and configuring your Cluster
  • Creating and attaching your first Notebook
  • Testing your Notebook
 Module 4: Uploading data
  • Connecting to a Spark data source
  • Previewing your Table
  • Columns and Datatypes basics
 Module 5: Bringing your data into your Notebook
  • Writing the initial SQL query to import
  • View aggregates
  • Perform Joins
 Module 6: Visualisations & DataFrames
  • Datatypes
  • Structured Streaming DataFrames
  • Plots
  • Choosing Chart types
  • Chart Toolbar
  • Layout and styling considerations
  • Machine Learning visualisations
 Module 7: Databricks Jobs
  • View Jobs and Job details
  • Running your first Job
  • Viewing completed jobs
  • Setting up Alerts
 Module 8: Delta Lake and Delta Tables
  • Getting data into Delta Lake
  • Delete, update, merge
  • Overview of Delta Engine
Learning Objectives
  • Apache Spark (Overview)
  • Real-world uses for Databricks
  • How Databricks and Apache Spark fit together
  • Getting started with Databricks
  • Uploading, preparing and transforming data
  • Creating Notebooks
  • Creating Clusters
  • Running Jobs
  • Delta Lake and Delta Tables


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