Last Updated: Sep 12, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Working with Data Sources | 20% | - Data integration and transformation - Structured and unstructured data sources - Extracting data from databases, web, and APIs - Data cleaning and preparation |
| Topic 2: Introduction to Big Data | 15% | - Big Data storage and processing - Cloud-based data environments - Big Data characteristics and concepts |
| Topic 3: Fundamentals of Data Analysis | 20% | - Data quality and integrity - Data lifecycle management - Data governance and policies - Data types and structures |
| Topic 4: Tools for Capturing and Analyzing Data | 20% | - Data visualization tools - Using tools for data mining and discovery - Open-source and commercial analysis tools - Spreadsheet tools |
| Topic 5: Analyzing and Reporting Data | 25% | - Designing effective reports and dashboards - Statistical analysis and interpretation - Presenting data insights for decision-making - Identifying trends, patterns, and correlations |
What is the key to effective data analysis in content planning?
Correct Answer: A 🗳️
How can analyzing network traffic data contribute to content planning?
Correct Answer: A 🗳️
How can CRM and customer service be integrated?
Correct Answer: A 🗳️
What is the relationship between content planning and business goals?
Correct Answer: C 🗳️
How can data be accessed and obtained from knowledge bases, including Facebook, Twitter, LinkedIn, enterprise resource management systems, and accounting sources?
Correct Answer: C 🗳️
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