EMC DEA-7TT2 valid dump torrent : 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 20, 2026
  • Q&As: 233 Questions and Answers

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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

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EMC DEA-7TT2 certification exam is a valuable credential for professionals working in the fields of data science and big data analytics. Associate - Data Science and Big Data Analytics v2 Exam certification is designed to test the proficiency of candidates in deploying and managing big data environments, identifying and analyzing data sets, and implementing high-performance algorithms. Candidates who obtain this certification can expect to be in high demand among employers, as this certification is a strong indication of a candidate's expertise in the field.

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EMC DEA-7TT2 Exam Syllabus Topics:

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

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