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














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