Associate - Data Science and Big Data Analytics V2 Exam
- Product Code: dea-7tt2
- Exam Questions: 117
- Vendor: emc
$9.99
$12.99- Updated At: Nov 21, 2024
Associate - Data Science and Big Data Analytics V2 Exam
This exam is designed for professionals who want to demonstrate their skills in data science and big data analytics. The exam validates their ability to analyze data from various sources, design data structures, and implement big data solutions.
Focus
The Associate - Data Science and Big Data Analytics V2 Exam certification focuses on Data Science, Big Data Analytics, Data Structures, Data Visualization, Predictive Analytics
Exam Duration
The Associate - Data Science and Big Data Analytics V2 Exam exam duration is 120 minutes
Num of Question
The exam contains a total of 80
Exam Fee
The exam fee is N/A.
Exam Validity
The CCRN-Pediatric certification is valid for N/A.
Prior Certification
- EMC Data Science and Big Data Analytics V1 Certification
Exam Format
The Associate - Data Science and Big Data Analytics V2 Exam exam is a Multiple-choice and drag-and-drop questions
Passing Conditions
To pass Associate - Data Science and Big Data Analytics V2 Exam exam, applicants must achieve a minimum score of Passing score: 70%
Who Should Take
Professionals who want to demonstrate their skills in data science and big data analytics, such as data scientists, data analysts, data engineers, and business analysts.
- Data Scientist
- Data Analyst
- Data Engineer
- Business Analyst
Prerequisites
N/A
Or can substitute with certifications:
- EMC Data Science and Big Data Analytics V1 Certification
- EMC Data Lake V1 Certification
Certification Process
- Step 01: Create an account on the EMC website and register for the exam.
- Step 02: Take the exam within the allotted time frame.
Domains with Weights
- Domain 1: Data Sources and Visualization (30%): The ability to collect and analyze data from various sources, and design and create data visualizations.
- Domain 2: Data Structures and Storage (25%): The knowledge of various data structures and file systems used in big data, and the ability to design and implement data storage solutions.
- Domain 3: Big Data Solutions and Architecture (20%): The understanding of big data architectures and the ability to design and implement big data solutions using various tools and technologies.
- Domain 4: Predictive Analytics and Machine Learning (25%): The skills to apply statistical techniques and machine learning algorithms to predict outcomes and make decisions.
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