Overview

This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.

This course consists of two four-hour modules.

SQL Analytics on Databricks

In this course, you’ll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights.

You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL.

Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.

AI/BI for Data Analysts

In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.

Private in-house training

Apart from public, instructor-led classes, we also offer private in-house trainings of this program for organizations. Call us at +852 2116 3328 or email us at [email protected] for more details.

Why Choose KORNERSTONE

  • Accredited, practitioner-led, expert certificate trainers to provide high quality training
  • Official training material included
  • Practical, scenario-based learning – focus on application, not just theory
  • Excellent Passing Rate

Skills Covered

SQL Analytics on Databricks

  • Data Discovery
  • Data Importing
  • SQL Execution
  • Query Analysis

AI/BI for Data Analysts

  • Dashboards and Visualizations in Databricks
  • AI/BI Genie

Prerequisites

  • A working knowledge of using SQL for data analysis purposes.
  • Be familiar with how data is created, stored, and managed.
  • A basic understanding of the purpose and use of statistical analysis results
  • Understand the structure and defining characteristics of specific data formats such as CSV, JSON, TXT, and Parquet.
  • Be familiar with the user interface of the Databricks Data Intelligence Platform.
  • Prior experience or basic familiarity with the Databricks Workspace UI.
  • Familiarity with the concepts around dashboards used for business intelligence.

Course Curriculum

Module 1: SQL Analytics on Databricks

Data Discovery

  • Using Unity Catalog as a Data Discovery Tool
  • Understanding Data Object Ownership
  • Use Unity Catalog to Locate and Inspect Datasets

Data Importing

Ingesting Data into Databricks

  • Uploading Data to Databricks Using the UI
  • Programmatic Exploration and Data Ingestion to Unity Catalog
  • Import Data into Databricks

SQL Execution

  • Databricks SQL and Databricks SQL Warehouses
  • The Unified SQL Editor
  • Manipulate and Transform Data with Databricks SQL
  • Creating Views with Databricks SQL
  • Manipulate and Analyze a Table

Query Analysis

  • Databricks Photon and Optimization in Databricks
  • Query Insights
  • Best Practices for SQL Analytics

Module 2: AI/BI for Data Analysts

Dashboards and Visualizations in Databricks

  • AI/BI Dashboards
  • Just enough SQL
  • Designing Datasets for Dashboards
  • Creating Visualizations and adding Summary Statistics to Dashboards
  • AI Enhanced Features
  • Filters
  • Sharing Dashboards with Stakeholders and Others
  • Managing Dashboards in Production
  • Dashboard and Visualization Lab Activity

AI/BI Genie

  • AI/BI Genie
  • Developing Genie Spaces
  • Sharing Genie Spaces
  • AI/BI Genie Development Activity Lab

Let's make it work for you

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Dates & Locations

Exam & Certification

Databricks Certified Data Analyst Associate.

The Databricks Certified Data Analyst Associate exam evaluates a candidate’s proficiency with the Databricks Data Intelligence Platform, assessing their ability to manage data with Unity Catalog – this includes discovering, querying, cleaning, and managing certified datasets, import data by utilizing various methods such as the UI, S3 ingestion, Delta Sharing for external systems, API-driven intake, Auto Loader, and the Marketplace feature, and excuting and optimizing queries for Data Analysis – including creating views, performing aggregate operations, combining tables with joins, filtering, sorting, and analyzing queries using auditing, history, logs, and Liquid clustering features.  

Additionally, the exam covers the basics of working with Dashboards and Visualisations, understanding the fundamentals of developing, sharing, and maintaining AI/BI Genie spaces within Databricks, data modelling with Databricks SQL, and securing data by adhering to best practices for data storage and management.

This exam covers:

  1. Understanding of Databricks Data Intelligence Platform – 11%
  2. Managing Data – 8%
  3. Importing Data – 5%
  4. Executing queries using Databricks SQL and Databricks SQL Warehouses – 20%
  5. Analyzing Queries – 15%
  6. Creating Dashboards and Visualizations in Databricks – 16%
  7. Developing, Sharing, and Maintaining AI/BI Genie spaces – 12%
  8. Data Modeling with Databricks SQL – 5%
  9. Securing Data – 8%

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