Cleared the Path: A Comprehensive Guide and Reflection on Passing the Databricks Certified Data Analyst Associate Exam

On September 30th, I sat for the most recent version of the Databricks Data Analyst Certification. I decided to attempt this exam to enhance my Databricks skills and as a foundational step for their more advanced certifications.

Below are the additional details regarding the Databricks Certified Data Analyst Associate certification exam:

· Type: The exam is a proctored certification, meaning it is monitored to ensure the integrity of the testing process.

· Total number of questions: There are 45 questions in total on the exam.

· Time limit: You have 90 minutes to complete the exam.

· Registration fee: The registration fee for the exam is $200. However, Databricks partners can receive a 50% discount on the registration fee.

· Question types: The exam consists of multiple-choice questions.

· Test aides: You are not allowed to use any test aides or reference materials during the exam.

· Languages: The exam is available in English.

· Delivery method: The exam is conducted online and proctored, which means it is administered remotely, and your actions are monitored during the test.

· Prerequisites: There are no specific prerequisites to take the exam, but it’s recommended to have related training to prepare effectively.

· Recommended experience: Databricks recommends having at least 6+ months of hands-on experience performing the data analysis tasks outlined in the exam guide to increase your chances of success.

· Validity period: The certification is valid for two years from the issue date.

· Recertification: To maintain your certification status, you will need to recertify after two years.

· Unscored content: The exam may include unscored items, which are used for statistical purposes but do not affect your score. Additional time is factored into the exam to account for these items.

This exam is designed to assess an individual’s proficiency in using Databricks SQL service and related tools for data analysis tasks. The exam is divided into five main areas, each with its respective weight in terms of the content covered:

· Databricks SQL (22%): This section evaluates your understanding of Databricks SQL service and its core features. It likely includes questions related to how to use Databricks SQL for data analysis, writing SQL queries, and leveraging its capabilities effectively.

· Data Management (20%): In this part, your ability to manage data using Databricks tools following best practices will be assessed. This may involve tasks like data ingestion, data transformation, data storage, and data quality considerations within the Databricks environment.

· SQL (29%): This section focuses on SQL proficiency. You’ll likely be tested on your ability to write SQL queries, manipulate data, and perform various data operations using SQL.

· Data Visualization and Dashboards (18%): Data visualization is a critical aspect of data analysis. This part of the exam will assess your skills in creating production-grade data visualizations and dashboards, possibly using Databricks or related tools.

· Analytics Applications (11%): Analytics applications involve using data analysis techniques to solve real-world problems. This section will likely test your ability to develop analytics applications to address common data analytics challenges.

To pass the Databricks Certified Data Analyst Associate certification exam, you need to demonstrate competence in these five areas. The weightings indicate the approximate distribution of questions or tasks related to each topic on the exam. It’s important to prepare thoroughly for each of these domains to ensure a successful outcome in the certification process.

I scored 82.2% which resulted in a PASS as you need 70% to pass. My score breakdown is as follows:

· Databricks SQL: 100.00%

· Data Management: 88.88%

· SQL: 69.23%

· Data Visualization and Dashboards: 62.50%

· Analytics Applications: 100.00%

I faced more challenges with the SQL section and dashboard, while the rest were relatively smooth. Specifically, I would not suggest this certification if you had limited data analytics experience, especially in SQL and dashboards.

You need to be proficient in SQL particularly ANSI standard SQL and some basic Apache Spark SQL. SQL skills needed include importing data from the cloud, DDL (Data Definition Language), DQL (Data Query Language), DML (Data Manipulation Language), DCL (Data Control Language), TCL (Transaction Control Language), understanding views/tables/temp views, querying nested data, handling arrays/map types, using cube/roll-up for aggregation, optimizing performance using higher-order Spark SQL functions and creating/applying UDF’s in common scaling scenarios. If any of these topics don’t seem familiar, please study adequately and practice.

The data visualization section proved challenging as some of the mentioned visualizations were unfamiliar. I recommend referring to the “Storytelling with Data” textbook by Cole Nussbaumer Knaflic for this part.

To prepare for this exam, I used an Azure account to start up a Databricks environment to do labs and practice some concepts. You need to practice using the query editor, data explorer, and dashboarding tool to prepare adequately.

I also used the Data Analyst learning plan on Databricks Academy as one learning tool; this consisted of about 6 hours of learning content. This learning plan will prepare you well for the Databricks SQL and Data management sections but for the other sections, you would need to refer to the exam guide for more preparations.

The exam guide provides a detailed breakdown of the concepts needed for each section and I prepared a Notion page having each of these concepts in a checklist. This list is a bit extensive, but you need to understand each concept, especially the SQL and dashboarding sections.

Best of Luck on the Databricks Data Analyst Associate exam!