EMC DEA-7TT2 exam dumps : Associate - Data Science and Big Data Analytics v2 Exam

  • Exam Code: DEA-7TT2
  • Exam Name: Associate - Data Science and Big Data Analytics v2 Exam
  • Updated: Aug 29, 2026     Q & A: 233 Questions and Answers

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  • India: INR 5,60,000

  • UK: Pounds £73,500

  • United States: USD $103,000

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Reference: https://education.emc.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:

  • Schedule your test

  • Register for a Pearson VUE account

  • Create an account on the EMC Proven Professional website

  • 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

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EMC DEA-7TT2 Exam Syllabus Topics:

SectionWeightObjectives
Advanced Analytics for Big Data - Technology and Tools22%- Big Data technologies and analytics tools
  • 1. Hadoop ecosystem and product use cases
  • 2. Big Data technology challenges
  • 3. Advanced SQL methods and MADlib
  • 4. MapReduce and Apache Hadoop
  • 5. In-database analytics and SQL essentials
Operationalizing an Analytics Project and Data Visualization Techniques10%- Analytics project deployment and visualization
  • 1. Planning and creating effective data visualizations
  • 2. Communicating findings and operationalizing analytics projects
  • 3. Building project presentations for audiences
Data Analytics Lifecycle8%- Data Analytics Lifecycle phases
  • 1. Data preparation phase activities and roles
  • 2. Model planning phase activities and roles
  • 3. Model building phase activities and roles
  • 4. Discovery phase activities and roles
Big Data, Analytics, and the Data Scientist Role5%- Characteristics of Big Data
  • 1. Data Scientist role and related skills
  • 2. Business drivers for Big Data analytics and data science
Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods40%- Advanced analytics methods
  • 1. Logistic regression
  • 2. Decision trees
  • 3. K-means clustering
  • 4. Association rules
  • 5. Text Analytics
  • 6. Linear regression
  • 7. Naïve Bayesian classifiers
  • 8. Time Series Analysis
Initial Analysis of the Data15%- Data exploration and statistical analysis
  • 1. Statistical measures and data visualization
  • 2. Basic R commands for data analysis
  • 3. Hypothesis testing and model evaluation

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