Updated: Oct 03, 2026
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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.
The benefits of having a Dell DEA-7TT2 Certification Exam are immense. It will help you out in getting an enhanced grip over your job, and you will be able to handle all the problems related to it very easily. You can go for this examination if you want to get more out of your job. Dell DEA-7TT2 exam dumps will help to get certified and get highly paid job.
It also ensures that you are able to give more than what is expected from you in your job which means that it gives you more chances of earning more money. It will help you in improving your career prospects as well as giving you a better chance of getting into some good jobs.
The cost for taking the Dell DEA-7TT2 Certification Exam is $250 USD.
| Certification Vendor: | Dell EMC |
|---|---|
| Exam Name: | Associate - Data Science and Big Data Analytics v2 Exam |
| Exam Number: | DEA-7TT2 |
| Exam Price: | $230 USD |
| Exam Duration: | 90 minutes |
| Related Certifications: | Dell EMC Proven Professional - Data Science Associate (DECA-DS) |
| Available Languages: | English |
| Passing Score: | 60% |
| Real Exam Qty: | 60 |
| Exam Format: | Multiple Choice |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Data Science and Big Data Analytics v2 Course |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | EMC DEA-7TT2 Sample Questions |
| Exam Way: | Online proctored or Onsite at Pearson VUE test centers |
| Pre Condition: | Basic knowledge of statistics, programming (preferably R), and data management concepts; recommended 3+ months hands-on experience with data analytics projects or tools |
| Official Syllabus URL: | https://education.dell.com/learning/certification/exam/dea-7tt2-associate-data-science-and-big-data-analytics-v2 |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Initial Analysis of the Data | 15% | - Hypothesis testing concepts and application - Basic R commands for data exploration - Statistical measures and data visualization |
| Topic 3: Operationalizing an Analytics Project and Data Visualization | 10% | - Deployment and integration of models - Guidelines for communicating findings - Visualization best practices and tools |
| Topic 4: Data Analytics Lifecycle | 8% | - Communicating results and operationalization - Model building phase activities and roles - Model planning phase activities and roles - Purpose and phases of the lifecycle - Discovery phase activities and roles - Data preparation phase activities and roles |
| Topic 5: Advanced Analytics for Big Data - Technology and Tools | 22% | - Hadoop ecosystem and its components - Advanced SQL: window functions, aggregates, MADlib - Spark and distributed processing frameworks - In-database analytics and SQL fundamentals |
| Topic 6: Advanced Analytics - Theory, Application, and Interpretation | 40% | - Model evaluation and validation methods - Unsupervised and supervised learning concepts - Association rules and time series analysis - Classification and clustering techniques - Linear and logistic regression |
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