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Get to know about the topics of the Dell DEA-7TT2 Certification Exam
The topics of the Dell DEA-7TT2 Certification Exam are following:
Advanced Analytics - Theory, Application, and Interpretation of Results for
Initial Analysis of the Data (15%)
Big Data, Analytics, and the Data Scientist Role (5%)
Data Analytics Lifecycle (8%)
Eight Methods (40%)
Operationalizing an Analytics Project and Data Visualization Techniques
Advanced Analytics for Big Data - Technology and Tools (22%)
(10%)
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
Read the DEA-7TT2 Certification Candidate Agreement
Register for a Pearson VUE account
Schedule your test
Understanding of the salary of the Dell DEA-7TT2 Certified Professional
The Average Salary of different countries of Dell DEA-7TT2 Certified Professional
United States: USD $103,000
UK: Pounds £73,500
India: INR 5,60,000
EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Advanced Analytics - Theory, Application, and Interpretation | 40% | - Association rules and time series analysis - Linear and logistic regression - Model evaluation and validation methods - Unsupervised and supervised learning concepts - Classification and clustering techniques |
| Topic 2: Operationalizing an Analytics Project and Data Visualization | 10% | - Visualization best practices and tools - Deployment and integration of models - Guidelines for communicating findings |
| Topic 3: Big Data, Analytics, and the Data Scientist Role | 5% | - Characteristics of Big Data - Role and required skills of a Data Scientist - Business drivers for Big Data analytics |
| Topic 4: Data Analytics Lifecycle | 8% | - Data preparation phase activities and roles - Model building phase activities and roles - Discovery phase activities and roles - Communicating results and operationalization - Model planning phase activities and roles - Purpose and phases of the lifecycle |
| Topic 5: Advanced Analytics for Big Data - Technology and Tools | 22% | - Advanced SQL: window functions, aggregates, MADlib - In-database analytics and SQL fundamentals - Spark and distributed processing frameworks - Hadoop ecosystem and its components |
| Topic 6: Initial Analysis of the Data | 15% | - Hypothesis testing concepts and application - Statistical measures and data visualization - Basic R commands for data exploration |
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