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Big Data and Analytics syllabus

IT 2786 units · 29 topicsAcademic year 2083/84
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Big Data and Analytics

6 units

1. Overview of Big Data (5 LHs)

  1. Introduction and types of data
  2. Evolution and characteristics of big data
  3. Big data versus data warehouse
  4. Advantages, disadvantages and utilization obstacles
  5. Impact of big data

2. Challenges of Big Data (6 LHs)

  1. Big data integration and storage
  2. Maintaining data quality
  3. Big data analysis
  4. Security and privacy management
  5. Accessing and sharing data

3. Big Data Analytics (6 LHs)

  1. Introduction and applications
  2. Types of big data analytics
  3. Comparison of data analytics stages

4. Hadoop and NoSQL Databases (14 LHs)

  1. Hadoop introduction and ecosystem
  2. Storage, processing, access and management components
  3. Apache Spark
  4. NoSQL introduction and database types
  5. Key-value, column-oriented, document-oriented and graph databases
  6. BASE model
  7. Advantages and disadvantages of NoSQL databases

5. Data Lakes (7 LHs)

  1. Data lake introduction and architecture
  2. Usage, challenges, advantages and disadvantages
  3. Lakehouse concept
  4. Data warehouse versus data lake versus lakehouse
  5. Best practices

6. Big Data Applications (10 LHs)

  1. Big data for healthcare
  2. Fraud detection analytics
  3. Social media analytics
  4. Novel applications