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Updated: Sep 12, 2026
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EMC DEA-7TT2 Exam Overview:
| Certification Vendor: | Dell EMC |
|---|---|
| Exam Name: | Associate - Data Science and Big Data Analytics v2 Exam |
| Exam Number: | DEA-7TT2 |
| Exam Format: | Multiple Choice |
| Available Languages: | English |
| Exam Duration: | 90 minutes |
| Passing Score: | 60% |
| Real Exam Qty: | 60 |
| Related Certifications: | Specialist - Data Scientist, Advanced Analytics Version 1.0 Dell EMC Proven Professional – Data Science Associate |
| Sample Questions: | EMC DEA-7TT2 Sample Questions |
| Exam Way: | Online proctored or test center exam via Pearson VUE |
| Pre Condition: | Recommended to have a strong quantitative background, understanding of statistics, experience with scripting languages such as Python, R, Java or Perl, and SQL knowledge. |
| Official Syllabus URL: | https://learning.dell.com/content/dam/dell-emc/documents/en-us/DEA-7TT2_Associate-Data_Science_and_Big_Data_Analytics_v2_Exam.pdf |
What are the registration steps for the DEA-7TT2 Associate - Data Science and Big Data Analytics v2 Certification Exam
Here are the steps you need to take to register for the DEA-7TT2 Associate - Data Science and Big Data Analytics v2 Certification Exam:
Create an account on the EMC Proven Professional website
Register for a Pearson VUE account
Schedule your test
Read the DEA-7TT2 Certification Candidate Agreement
What are the prerequisites for Dell DEA-7TT2 Certification Exam?
There are no formal prerequisites for Dell EMC DEA-7TT2 exam. However, it's recommended that you have:
6 months experience in the IT industry and knowledge of data science fundamentals
3 months hands-on experience with data science tools
EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced Analytics for Big Data - Technology and Tools | 22% | - Big Data technologies and analytics tools
|
| Topic 2: Big Data, Analytics, and the Data Scientist Role | 5% | - Characteristics of Big Data
|
| Topic 3: Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods | 40% | - Advanced analytics methods
|
| Topic 4: Initial Analysis of the Data | 15% | - Data exploration and statistical analysis
|
| Topic 5: Operationalizing an Analytics Project and Data Visualization Techniques | 10% | - Analytics project deployment and visualization
|
| Topic 6: Data Analytics Lifecycle | 8% | - Data Analytics Lifecycle phases
|
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