Use this quick start guide to collect all the information about Dell Technologies Data Engineering Optimize (D-DS-OP-23) Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the D-DS-OP-23 Dell Technologies Data Engineering Optimize exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual Dell Technologies Data Engineering Optimize certification exam.
The Dell Technologies Data Engineering Optimize certification is mainly targeted to those candidates who want to build their career in Data Science domain. The Dell Technologies Certified Data Engineering Optimize exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of Dell Technologies Data Engineering Optimize.
Dell Technologies Data Engineering Optimize Exam Summary:
| Exam Name | Dell Technologies Certified Data Engineering Optimize |
| Exam Code | D-DS-OP-23 |
| Exam Price | $230 (USD) |
| Duration | 90 mins |
| Number of Questions | 60 |
| Passing Score | 63% |
| Books / Training | Data Scientist and Data Engineering Optimize Training |
| Schedule Exam | Pearson VUE |
| Sample Questions | Dell Technologies Data Engineering Optimize Sample Questions |
| Practice Exam | Dell Technologies D-DS-OP-23 Certification Practice Exam |
Dell Technologies D-DS-OP-23 Exam Syllabus Topics:
| Topic | Details | Weights |
|---|---|---|
| The Role of the Data Engineer |
- Describe the skills of a data engineer - Describe the role of a data engineer in a data analytics project |
5% |
| Data Warehousing with SQL and NoSQL |
- Describe characteristics and performance considerations of a relational database - Describe relational database schemas and normalization techniques - Describe use cases and features of various NoSQL tools |
17% |
| Extract-Transform-Load (ETL) Offload with Hadoop and Spark |
- Describe ETL, ELT, and related schedulers - Describe the Hadoop ecosystem, HDFS, and data ingestion tools - Describe Apache Spark and its architecture |
18% |
| Data Governance, Security and Privacy for Big Data |
- Describe data governance, key roles, and related models - Describe metadata and Master Data Management - Describe security considerations with Hadoop and the Cloud - Describe the uses of Apache Atlas, Ranger, and Knox - Describe privacy regulations and ethics |
20% |
| Processing Streaming and IoT Data |
- Describe uses and application of IoT tools - Describe the Apache Storm system and topology - Describe the Apache Kafka queueing system and architecture - Describe Apache Spark - Streaming processing and architecture - Describe Apache Flink and its architecture - Describe Pravega and its storage architecture - Describe EdgeX Foundry and its architecture |
20% |
| Building Data Pipelines with Python |
- Describe Python, reasons to use, and its libraries - Describe the use of lists, dictionaries, tuples, sets, and strings - Describe the use of Apache Airflow - Describe data pipeline best practices |
20% |
To ensure success in Dell Technologies Data Engineering Optimize certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for Dell Technologies Data Engineering Optimize (D-DS-OP-23) exam.