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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.
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.
Understanding of the salary of the Dell DEA-7TT2 Certified Professional
The Average Salary of different countries of Dell DEA-7TT2 Certified Professional
Reference: https://education.emc.com/content/dam/dell-emc/documents/en-us/DEA-7TT2_Associate-Data_Science_and_Big_Data_Analytics_v2_Exam.pdf
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EMC DEA-7TT2 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Operationalizing an Analytics Project and Data Visualization Techniques | 10% | - Analytics project deployment and visualization
- 1. Planning and creating effective data visualizations
- 2. Communicating findings and operationalizing analytics projects
- 3. Building project presentations for audiences
|
| Topic 2: Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods | 40% | - Advanced analytics methods
- 1. Logistic regression
- 2. Decision trees
- 3. Time Series Analysis
- 4. Association rules
- 5. K-means clustering
- 6. Naïve Bayesian classifiers
- 7. Linear regression
- 8. Text Analytics
|
| Topic 3: Big Data, Analytics, and the Data Scientist Role | 5% | - Characteristics of Big Data
- 1. Data Scientist role and related skills
- 2. Business drivers for Big Data analytics and data science
|
| Topic 4: Data Analytics Lifecycle | 8% | - Data Analytics Lifecycle phases
- 1. Discovery phase activities and roles
- 2. Model building phase activities and roles
- 3. Data preparation phase activities and roles
- 4. Model planning phase activities and roles
|
| Topic 5: Initial Analysis of the Data | 15% | - Data exploration and statistical analysis
- 1. Hypothesis testing and model evaluation
- 2. Basic R commands for data analysis
- 3. Statistical measures and data visualization
|
| Topic 6: Advanced Analytics for Big Data - Technology and Tools | 22% | - Big Data technologies and analytics tools
- 1. Advanced SQL methods and MADlib
- 2. Big Data technology challenges
- 3. In-database analytics and SQL essentials
- 4. Hadoop ecosystem and product use cases
- 5. MapReduce and Apache Hadoop
|