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What are the steps to follow for the registration for the CompTIA DA0-001 Exam
Go to the official website of CompTIA Data+ and click on the “Register” button.
Fill in all the required fields in the registration form and click on “Submit”.
A confirmation email will be sent to you, which contains a link to activate your account and a link to print your exam voucher (you can also opt for an alternative method of delivery).
Go through your exam voucher and note down all the details mentioned on it, including: Exam ID, Exam Number, Date, Time & Location of test, Venue Phone Number (if applicable).
Take a printout of this voucher and carry it with you when appearing for your exam at the specified venue on that particular day/time window allotted by CompTIA to test centers worldwide
Reference: https://www.comptia.org/training/books/data-da0-001-study-guide
CompTIA DA0-001日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualization and Reporting | 23% | - Design principles and best practices - Communicating insights and recommendations - Building dashboards and reports - Selecting appropriate visualizations and charts |
| Topic 2: Data Mining | 25% | - Data profiling, cleansing, and validation - Querying and retrieving data - Data transformation, manipulation, and enrichment - Data acquisition and integration methods |
| Topic 3: Data Concepts and Environments | 15% | - Data schemas, dimensions, and attributes - Structured, semi-structured, and unstructured data - Data types, structures, and formats - Data storage systems: databases, data marts, warehouses, data lakes |
| Topic 4: Data Governance, Quality and Controls | 14% | - Data governance frameworks and policies - Data lifecycle management and controls - Data privacy, security, and compliance - Data quality standards and measurement |
| Topic 5: Data Analysis | 23% | - Interpreting results and identifying patterns/anomalies - Descriptive and inferential statistics - Statistical methods: correlation, regression, hypothesis testing - Analytical techniques: trend, performance, exploratory, comparative |
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