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The Dell DEA-7TT2 is mainly a certification exam that tests your knowledge and skills in the related field. There are several benefits of having the Dell DEA-7TT2 certification. The main benefit of having this certification is that it will help you to get a good job with a high salary.
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Here is the about the significance of taking the Dell DEA-7TT2 Certification Exam
The Dell DEA-7TT2 certification exam is for those who have a knack in dealing with data and the related issues. The Dell DEA-7TT2 exam is a kind of test that is made to ensure that the students who have opted for it are able to deal with all the problems and issues related to data science and big data analytics v2.
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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:
Data Analytics Lifecycle (8%)
Big Data, Analytics, and the Data Scientist Role (5%)
Initial Analysis of the Data (15%)
Advanced Analytics - Theory, Application, and Interpretation of Results for
Eight Methods (40%)
Operationalizing an Analytics Project and Data Visualization Techniques
Advanced Analytics for Big Data - Technology and Tools (22%)
(10%)
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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
Passing scores: 71%
Number of questions: 60
Duration: 90 minutes
Languages: English
EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Operationalizing an Analytics Project and Data Visualization | 10% | - Visualization best practices and tools - Guidelines for communicating findings - Deployment and integration of models |
| Advanced Analytics - Theory, Application, and Interpretation | 40% | - Association rules and time series analysis - Classification and clustering techniques - Unsupervised and supervised learning concepts - Model evaluation and validation methods - Linear and logistic regression |
| 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% | - Role and required skills of a Data Scientist - Business drivers for Big Data analytics - Characteristics of Big Data |
| Advanced Analytics for Big Data - Technology and Tools | 22% | - In-database analytics and SQL fundamentals - Advanced SQL: window functions, aggregates, MADlib - Spark and distributed processing frameworks - Hadoop ecosystem and its components |
| Data Analytics Lifecycle | 8% | - Discovery phase activities and roles - Data preparation phase activities and roles - Purpose and phases of the lifecycle - Model building phase activities and roles - Communicating results and operationalization - Model planning phase activities and roles |
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