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If you work in the information technology sector, you have probably heard a lot of people discussing their certifications. Since the beginning of IT certifications, the number of available certificates has been steadily rising. The Dell DEA-7TT2 certification exam is just one that you may want to consider. Let's take a closer look at what this certification entails. By looking at the different things that are covered by this certificate, you can make an informed decision about whether it is relevant to your career path. Dell DEA-7TT2 exam dumps will help you to get certified.
The Dell DEA-7TT2 certification has been developed to enhance individual skills and knowledge in Data Science and Big Data Analytics. The test will verify that the professionals have the ability to handle the complex tasks of Data Science and Big Data Analytics. It will also check if the candidates are well versed with the advanced features of Data Science and Big Data Analytics software. The certification program will ensure that the professionals associated with Dell services are highly qualified in design and implementation of data center systems.
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EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Advanced Analytics - Theory, Application, and Interpretation | 40% | - Linear and logistic regression - Association rules and time series analysis - Unsupervised and supervised learning concepts - Classification and clustering techniques - Model evaluation and validation methods |
| 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 |
| Initial Analysis of the Data | 15% | - Basic R commands for data exploration - Hypothesis testing concepts and application - Statistical measures and data visualization |
| Data Analytics Lifecycle | 8% | - Model planning phase activities and roles - Communicating results and operationalization - Purpose and phases of the lifecycle - Discovery phase activities and roles - Model building phase activities and roles - Data preparation phase activities and roles |
| Operationalizing an Analytics Project and Data Visualization | 10% | - Deployment and integration of models - Guidelines for communicating findings - Visualization best practices and tools |
| Advanced Analytics for Big Data - Technology and Tools | 22% | - Spark and distributed processing frameworks - In-database analytics and SQL fundamentals - Advanced SQL: window functions, aggregates, MADlib - Hadoop ecosystem and its components |
