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Who is this Dell DEA-7TT2 Certification Exam for?
Dell DEA-7TT2 Exam provides user with the opportunity to prove their skills and knowledge of Data Science and Big Data Analytics v2. The test is available for individuals who are interested in assessing their ability to analyze data with tools, develop and implement models, design experiments, and use methods such as machine learning. This certification is suitable for those who have a solid understanding of the concepts related to data science and big data analytics; these may include linear regression and logistic regression, modeling approaches, distributions, random variables, probability theory, fundamentals of statistics, hypothesis testing, exploratory data analysis, clustering techniques, predictive modeling, classification algorithm, and others. Dell DEA-7TT2 exam dumps will help you to clear your concepts.
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Understanding of the salary of the Dell DEA-7TT2 Certified Professional
The Average Salary of different countries of Dell DEA-7TT2 Certified Professional
India: INR 5,60,000
UK: Pounds £73,500
United States: USD $103,000
EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 2: Operationalizing an Analytics Project and Data Visualization | 10% | - Deployment and integration of models - Visualization best practices and tools - Guidelines for communicating findings |
| Topic 3: Data Analytics Lifecycle | 8% | - Communicating results and operationalization - Data preparation phase activities and roles - Model planning phase activities and roles - Model building phase activities and roles - Discovery phase activities and roles - Purpose and phases of the lifecycle |
| Topic 4: Initial Analysis of the Data | 15% | - Basic R commands for data exploration - Hypothesis testing concepts and application - Statistical measures and data visualization |
| Topic 5: Advanced Analytics for Big Data - Technology and Tools | 22% | - In-database analytics and SQL fundamentals - Hadoop ecosystem and its components - Spark and distributed processing frameworks - Advanced SQL: window functions, aggregates, MADlib |
| Topic 6: Advanced Analytics - Theory, Application, and Interpretation | 40% | - Unsupervised and supervised learning concepts - Linear and logistic regression - Model evaluation and validation methods - Classification and clustering techniques - Association rules and time series analysis |
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