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A comprehensive guide: How to pass the Dell DEA-7TT2 Certification Exam
Preparation guide to passing the Dell DEA-7TT2 Certification Exam in the first attempt
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Before attempting to pass the Dell DEA-7TT2 certification exam, please take a moment to read this article. Why? Because it can save you time and hassle - not only in your first attempt at taking the test, but also with each attempt thereafter.
If you are looking for a reasonable way to get started with the Dell DEA-7TT2 certification exam or just to pass it and earn the Dell DEA-7TT2 certifications, then this is the guide for you. It covers all the areas of the certification and has tips and tricks that will help you pass the Dell DEA-7TT2 exam dumps.
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How long does it take to pass the Dell DEA-7TT2 Certification Exam?
According to the passing Score, duration & question for the Dell DEA-7TT2 Certification Exam is given below
Duration: 90 minutes
Passing scores: 71%
Number of questions: 60
Languages: English
Understanding of the salary of the Dell DEA-7TT2 Certified Professional
The Average Salary of different countries of Dell DEA-7TT2 Certified Professional
UK: Pounds £73,500
United States: USD $103,000
India: INR 5,60,000
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EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Advanced Analytics - Theory, Application, and Interpretation | 40% | - Unsupervised and supervised learning concepts - Linear and logistic regression - Model evaluation and validation methods - Association rules and time series analysis - Classification and clustering techniques |
| Initial Analysis of the Data | 15% | - Statistical measures and data visualization - Basic R commands for data exploration - Hypothesis testing concepts and application |
| Big Data, Analytics, and the Data Scientist Role | 5% | - Business drivers for Big Data analytics - Role and required skills of a Data Scientist - Characteristics of Big Data |
| 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 |
| Operationalizing an Analytics Project and Data Visualization | 10% | - Deployment and integration of models - Guidelines for communicating findings - Visualization best practices and tools |
| Data Analytics Lifecycle | 8% | - Communicating results and operationalization - Purpose and phases of the lifecycle - Model building phase activities and roles - Model planning phase activities and roles - Data preparation phase activities and roles - Discovery phase activities and roles |



