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SASInstitute A00-220 Exam consists of 60 multiple-choice questions that must be completed within a time limit of 2 hours and 15 minutes. A00-220 exam covers a wide range of topics, including data preparation, data exploration, statistical modeling, and visualization. Candidates must demonstrate their ability to use SAS software to perform tasks such as data manipulation, data cleaning, and data visualization.
SASInstitute A00-220 Exam Overview:
| Certification Vendor: | SAS Institute |
|---|---|
| Exam Name: | SAS Big Data Preparation, Statistics, and Visual Exploration |
| Exam Number: | A00-220 |
| Certificate Validity Period: | Not specified |
| Available Languages: | English |
| Passing Score: | 67% |
| Real Exam Qty: | 55-60 |
| Exam Price: | $180 USD |
| Related Certifications: | SAS Certified Big Data Professional SAS Big Data Programming and Loading (A00-221) |
| Exam Duration: | 110 minutes |
| Exam Format: | Interactive Questions, Multiple Choice, Short Answer |
| Exam Way: | Pearson VUE testing centers and SAS-authorized exam delivery. |
| Pre Condition: | Recommended hands-on experience with SAS/STAT, SAS Visual Analytics, and SAS DataFlux Data Management Studio. Commonly pursued as part of the SAS Certified Big Data Professional credential path. |
| Official Syllabus URL: | https://www.sas.com/en_in/certification/credentials/data-management/big-data-professional/big-data-preparation-exam.html |
SASInstitute A00-220 certification exam is designed for professionals who want to validate their skills in SAS Big Data Preparation, Statistics, and Visual Exploration. SAS Big Data Preparation, Statistics, and Visual Exploration certification is a globally recognized credential that demonstrates an individual's expertise in managing and analyzing big data using SAS tools. A00-220 exam requires candidates to have a deep understanding of various SAS software components such as SAS Visual Analytics, SAS Data Management, and SAS Data Integration Studio.
SASInstitute A00-220 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Hadoop and Hive Integration | - Big Data Platform Usage
|
| Topic 2: Data Quality Management | - Data Quality Improvement
|
| Topic 3: Big Data Fundamentals | - Big Data Concepts
|
| Topic 4: SAS Programming and Data Preparation | - Data Access and Manipulation
|
| Topic 5: Statistics | - Fundamental Statistical Techniques
|
| Topic 6: Data Exploration and Visualization | - Visual Analytics
|
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