EMC Specialist - Data Scientist, Data Engineering : DES-7DE1

DES-7DE1 real exams

Exam Code: DES-7DE1

Exam Name: Specialist - Data Scientist, Data Engineering Exam

Updated: Sep 28, 2026

Q & A: 0 Questions and Answers

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About EMC DES-7DE1 Exam

EMC DES-7DE1 certification exam covers a wide range of topics, including data mining, machine learning, statistical analysis, and data visualization techniques. Specialist - Data Scientist, Data Engineering Exam certification exam is ideal for professionals who want to demonstrate their expertise in data science and data engineering and want to advance their careers in these fields. DES-7DE1 exam is also a great way for employers to ensure that their employees have the necessary skills and knowledge to effectively analyze and manage data, which is crucial in today's data-driven business environment.

The DES-7DE1 exam focuses on the core concepts of data science and engineering, including data modeling, data visualization, data integration, and data governance. It also covers advanced topics such as machine learning, deep learning, natural language processing, and big data technologies. DES-7DE1 exam is designed to test the knowledge and skills of data scientists and data engineers in these areas.

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EMC DES-7DE1 Exam is intended for data scientists, data engineers, and other professionals who work with data on a regular basis. It is an excellent certification for individuals who want to advance their career in the field of data science and engineering. By obtaining this certification, candidates can demonstrate their expertise in data science and engineering, and their ability to design and deploy data-driven solutions that can help organizations to achieve their business objectives.

Reference: https://education.dellemc.com/content/dam/dell-emc/documents/en-us/DS_DataEng_SpecExamDesc_APR1020_Current.pdf

EMC DES-7DE1 Exam Syllabus Topics:

SectionWeightObjectives
Building Data Pipelines with Python20%- Python programming for data pipeline development
The Role of the Data Engineer5%- Skills and responsibilities of a data engineer
Processing Streaming and IoT Data20%- Streaming architectures (e.g., Apache Kafka, Apache Flink)
- IoT data use cases and streaming tools
Data Warehousing with SQL and NoSQL17%- Relational database characteristics and performance
- NoSQL tools use cases and features
Extract-Transform-Load (ETL) Offload with Hadoop and Spark18%- ETL, ELT processes and schedulers
- Hadoop ecosystem and Apache Spark architecture
Data Governance, Security and Privacy for Big Data20%- Data governance roles and models
- Metadata, Master Data Management and privacy considerations

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