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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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Official link to the Dell DEA-7TT2 Certification Exam
What do You need To Know About The Dell DEA-7TT2 Certification Exam?
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% | - Classification and clustering techniques - Model evaluation and validation methods - Unsupervised and supervised learning concepts - Association rules and time series analysis - Linear and logistic regression |
| Advanced Analytics for Big Data - Technology and Tools | 22% | - Hadoop ecosystem and its components - Spark and distributed processing frameworks - Advanced SQL: window functions, aggregates, MADlib - In-database analytics and SQL fundamentals |
| Data Analytics Lifecycle | 8% | - Discovery phase activities and roles - Model building phase activities and roles - Purpose and phases of the lifecycle - Data preparation phase activities and roles - Model planning phase activities and roles - Communicating results and operationalization |
| 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 - Characteristics of Big Data - Role and required skills of a Data Scientist |
| Operationalizing an Analytics Project and Data Visualization | 10% | - Deployment and integration of models - Guidelines for communicating findings - Visualization best practices and tools |






