Data Analysis with Databricks SQL - Extended Course Overview

Minimum Required Prerequisites for Data Analysis with Databricks SQL - Extended Course:

• Basic knowledge of SQL and relational databases.
• Familiarity with any programming or scripting language (Python, R, or similar).
• Understanding of data analysis concepts and methodologies.
• Basic understanding of data formats (CSV, JSON, Parquet, etc.).
• An eagerness to learn and explore data analysis using Databricks SQL.

Target Audience for Data Analysis with Databricks SQL - Extended

Introduction:
The "Data Analysis with Databricks SQL - Extended" course equips professionals with essential skills in data analysis, visualization, and management using Databricks SQL, perfect for elevating careers in data-driven industries.

Target Audience and Job Roles:

• Data Analysts
• Data Engineers
• Data Scientists
• Business Intelligence Analysts
• Data Architects
• SQL Developers
• Analytics Consultants
• Database Administrators
• ETL Developers
• Machine Learning Engineers
• IT Managers
• Reporting Analysts
• Financial Analysts
• Research Scientists
• Statisticians
• Big Data Engineers
• Technical Consultants
• Project Managers in data-centric projects
• Software Developers focusing on data solutions
• Academic Professionals in data sciences
• Graduate students in Data Science, Computer Science, or related fields

Learning Objectives - What you will Learn in this Data Analysis with Databricks SQL - Extended?

Course Introduction

The Data Analysis with Databricks SQL - Extended course provides comprehensive training on utilizing Databricks SQL for data analysis, including data ingestion, management, visualization, and job scheduling. This course spans three days and covers crucial concepts and functionalities of Databricks.

Learning Objectives and Outcomes

• Understand Databricks SQL and its capabilities: Learn the benefits of Databricks SQL, its workspace, and notebook functionalities.
• Master table and view management: Grasp the creation, management of tables and views, and handling temporary and permanent tables within Databricks SQL.
• Ingest various data formats: Discover methods for importing data from external sources in different formats like CSV, Parquet, and JSON using Databricks SQL.
• Utilize Delta commands: Learn to write, read, and manage data using Delta Lake with commands like MERGE, UPDATE, and DELETE.
• Perform complex data operations: Execute analytical functions such as window functions, grouping, joins, aggregations, filtering, and using UDFs.
• Create data visualizations: Build a variety of visualizations and interactive dashboards, and employ SQL queries within these visualizations.
• Manage Databricks jobs: Gain expertise in creating, running,