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The IBM 1Z0-1041-21 exam is a specialist-level certification that tests the skills and knowledge required to successfully implement and manage the Oracle Cloud Platform Enterprise Analytics solution. Oracle Cloud Platform Enterprise Analytics 2021 Specialist certification is ideal for professionals who want to enhance their career opportunities in the field of enterprise analytics. By passing 1Z0-1041-21 exam, candidates can demonstrate their expertise in using the Oracle Analytics Cloud to create data models, visualizations, and reports that can help organizations make informed decisions based on data-driven insights.
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The IBM 1Z0-1041-21 exam consists of 55 multiple-choice questions and requires a passing score of 66% to earn the certification. 1Z0-1041-21 exam covers various topics such as analytics cloud architecture, data integration, data governance, and advanced analytics techniques. Upon achieving the certification, candidates can demonstrate their expertise in using Oracle Cloud Platform Enterprise Analytics services, which can unlock new career opportunities and help them excel in their current roles.
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Oracle Cloud Platform Enterprise Analytics solution provides businesses with a powerful set of tools and services to help them manage and analyze their data. Oracle Cloud Platform Enterprise Analytics 2021 Specialist certification exam tests candidates on their ability to use these tools and services effectively, including the Oracle Analytics Cloud, Oracle Autonomous Data Warehouse, and Oracle Data Integrator Cloud Service. Candidates must also demonstrate their knowledge of data governance, security, and compliance.
Oracle 1Z0-1041-21 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Oracle Analytics Cloud Overview and Administration | 25% | - Architecture and components - Monitoring and maintenance - Provisioning and lifecycle management - Security and access control |
| Advanced Analytics and Machine Learning | 5% | - Advanced statistical functions - Predictive analytics - Machine learning model creation and deployment |
| Data Modeling and Semantic Layer | 25% | - Calculations and aggregations - Creating and managing semantic models - Dimensional modeling concepts - Hierarchies, measures and attributes |
| Data Visualization and Analysis | 20% | - Building visualizations and dashboards - Storytelling and presentation - Interactive analysis and filtering - Sharing and collaboration |
| Data Preparation and Integration | 25% | - Data transformation and enrichment - Data sources connection - Data quality and validation - Data synchronization and refresh |





