Labour Day Special Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: get65

Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Topics, Blueprint and Syllabus

Databricks Certified Associate Developer for Apache Spark 3.0 Exam

Last Update May 7, 2024
Total Questions : 180

Our Databricks Certification Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam questions and answers cover all the topics of the latest Databricks Certified Associate Developer for Apache Spark 3.0 Exam exam, See the topics listed below. We also provide Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam dumps with accurate exam content to help you prepare for the exam quickly and easily. Additionally, we offer a range of Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 resources to help you understand the topics covered in the exam, such as Databricks Certification video tutorials, Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 study guides, and Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 practice exams. With these resources, you can develop a better understanding of the topics covered in the exam and be better prepared for success.

Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0
PDF

$35  $99.99

Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Testing Engine

$42  $119.99

Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 PDF + Testing Engine

$56  $159.99

Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Overview :

Exam Name Databricks Certified Associate Developer for Apache Spark 3.0 Exam
Exam Code Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0
Actual Exam Duration The duration of the Databricks Certified Associate Developer for Apache Spark 3.0 exam is 120 minutes (2 hours).
Expected no. of Questions in Actual Exam 60
What exam is all about The Databricks Certified Associate Developer for Apache Spark 3.0 exam is a certification exam that tests the knowledge and skills of developers who work with Apache Spark 3.0 using Databricks. The exam covers topics such as Spark architecture, data processing, Spark SQL, Spark Streaming, and machine learning with Spark. The exam is designed to validate the candidate's ability to develop and deploy Spark applications using Databricks. Passing this exam demonstrates that the candidate has the skills and knowledge required to work with Spark and Databricks in a professional setting.
Passing Score required The passing score required in the Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam is 70%. This means that you need to answer at least 70% of the questions correctly to pass the exam and earn the certification. The exam consists of multiple-choice questions and is designed to test your knowledge and skills in using Apache Spark to solve real-world data processing problems. To prepare for the exam, you should have a good understanding of Spark architecture, data processing using Spark SQL, Spark Streaming, and Spark MLlib. You should also have hands-on experience in using Spark to build data pipelines and perform data analysis.
Competency Level required According to the Databricks website, the exam is designed for developers who have a basic understanding of Apache Spark and are familiar with programming in Python or Scala. The exam covers topics such as Spark architecture, data processing, data analysis, and machine learning. It is recommended that candidates have at least six months of experience working with Spark before taking the exam.
Questions Format The Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam consists of multiple-choice questions. The exam includes 60 questions, and the candidate has 90 minutes to complete the exam. The questions are designed to test the candidate's knowledge and skills in Apache Spark 3.0, including Spark SQL, Spark Streaming, and Spark MLlib. The exam also covers topics such as data frames, RDDs, data sources, and data processing. The questions are designed to be challenging and require a deep understanding of Apache Spark 3.0.
Delivery of Exam The Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam is an online proctored exam that can be taken from anywhere with a stable internet connection. The exam is delivered through the Databricks Academy platform, which provides a secure and reliable testing environment. The exam consists of multiple-choice questions and is timed, with a total duration of 2 hours. Candidates must pass the exam with a score of 70% or higher to earn the certification.
Language offered The Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam is offered in English language only.
Cost of exam You can visit the official website of Databricks or contact their customer support team to get the latest pricing information.
Target Audience The Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 certification is designed for individuals who have a basic understanding of Apache Spark and want to demonstrate their skills in developing Spark applications using Databricks. The target audience for this certification includes: 1. Developers who want to demonstrate their proficiency in developing Spark applications using Databricks. 2. Data engineers who want to validate their skills in building and managing Spark-based data pipelines. 3. Data analysts who want to demonstrate their ability to use Spark for data analysis and visualization. 4. IT professionals who want to validate their knowledge of Spark and Databricks for managing big data. 5. Students and fresh graduates who want to start their career in big data and analytics and want to demonstrate their skills in Spark and Databricks.
Average Salary in Market According to some online sources, the average salary for a Databricks Certified Associate Developer for Apache Spark 3.0 ranges from $100,000 to $150,000 per year, depending on the location, experience, and skills of the candidate. It's important to note that salary can vary widely based on many factors, and it's best to research current job openings and salary data in your specific area to get a more accurate estimate.
Testing Provider You can visit the official Databricks website to register for the exam and access study materials.
Recommended Experience According to the official Databricks website, the recommended experience for the Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam is: - At least six months of experience using Apache Spark in a production environment - Knowledge of programming languages such as Python or Scala - Familiarity with data processing and analysis concepts - Understanding of distributed computing and cluster management - Experience with SQL and data modeling It is also recommended to have completed the Databricks Apache Spark Developer course or have equivalent knowledge and experience.
Prerequisite The prerequisites for the Databricks Certified Associate Developer for Apache Spark 3.0 exam are: 1. Basic knowledge of programming concepts and experience with at least one programming language such as Python, Scala, or Java. 2. Familiarity with Apache Spark and its core concepts such as RDDs, DataFrames, and Spark SQL. 3. Experience with data processing and analysis using Spark. 4. Understanding of distributed computing and parallel processing. 5. Knowledge of SQL and data modeling concepts. 6. Familiarity with data storage and retrieval technologies such as Hadoop Distributed File System (HDFS) and Apache Parquet. 7. Experience with data visualization and reporting tools such as Tableau or Power BI. 8. Understanding of machine learning concepts and experience with machine learning libraries such as MLlib. 9. Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. 10. Experience with software development tools such as Git, Jenkins, and Docker.
Retirement (If Applicable) It is recommended to check with Databricks or their official website for the latest updates on the certification exam.
Certification Track (RoadMap): The certification track or roadmap for Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam includes the following steps: 1. Preparation: Candidates should have a good understanding of Apache Spark, including its architecture, programming model, and APIs. They should also be familiar with the Databricks platform and its features. 2. Training: Candidates can take the Databricks Apache Spark Developer Certification course, which covers the topics and skills required for the exam. 3. Exam: Candidates must pass the Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam, which tests their knowledge and skills in Apache Spark development using Databricks. 4. Certification: Candidates who pass the exam will receive the Databricks Certified Associate Developer for Apache Spark 3.0 certification, which validates their skills and knowledge in Apache Spark development using Databricks. 5. Continuing education: Certified developers should continue to stay up-to-date with the latest developments in Apache Spark and Databricks, and may consider pursuing additional certifications or training to further enhance their skills and knowledge.
Official Information https://academy.databricks.com/exam/databricks-certified-associate-developer
See Expected Questions Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Expected Questions in Actual Exam
Take Self-Assessment Use Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Test to Assess your preparation - Save Time and Reduce Chances of Failure

Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Exam Topics :

Section Weight Objectives
Objective 1:  
  • Define the major components of Spark architecture and execution hierarchy
Objective 2:  
  • Describe how DataFrames are built, transformed, and evaluated in Spark
Objective 3:  
  • Apply the DataFrame API to explore, preprocess, join, and ingest data in Spark
Objective 4:  
  • Apply the Structured Streaming API to perform analytics on streaming data
Objective 5:  
  • Navigate the Spark UI and describe how the catalyst optimizer, partitioning, and caching affect Spark's execution performance