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ISQI CDFL Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Ethics & Best Practices | 5% | - Common pitfalls and best practices - Data privacy and compliance |
| Data Management & Processing | 20% | - Batch vs real-time processing - Data ingestion, integration, and cleansing - Data governance, quality, and security |
| Data Sources & Types | 15% | - Structured, semi-structured, unstructured data - Internal and external data sources - Data formats and storage considerations |
| Data Analysis & Visualization | 15% | - Exploratory data analysis - Visualization principles and tools - Basic statistical and analytical concepts |
| Big Data Fundamentals | 20% | - Definition and characteristics of Big Data - The 5 Vs of Big Data - Business drivers and use cases |
| Big Data Architecture & Technologies | 25% | - NoSQL databases types and use cases - Distributed systems and frameworks - Hadoop ecosystem (HDFS, MapReduce, YARN) - Processing tools: Spark, Hive, Pig |
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