UUY-DTS 4122 units400 LevelFirst Semester

Data Management II

B.Sc. Data Science, University of Uyo

Enterprise-scale data management, continuing DTS 314: data architecture, pipelines and orchestration, master data and quality management, governance, and the modern data stack.

On Areté, UUY-DTS 412 comes with

  • 3 recommended textbooks
  • an AI tutor that has read this course’s outline and notes
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Course outline

  1. 01Enterprise data architecture: operational vs analytical systems
  2. 02Data integration: ETL vs ELT, batch vs streaming ingestion
  3. 03Pipeline orchestration and scheduling; DAGs and tools such as Airflow
  4. 04Data lakes, data warehouses and the lakehouse pattern; file formats (Parquet, Avro, ORC)
  5. 05Master data management and reference data
  6. 06Data quality: dimensions, profiling, validation rules and monitoring
  7. 07Metadata management, data catalogues and data lineage
  8. 08Data governance: ownership, stewardship, policy and regulatory compliance
  9. 09Data lifecycle management: retention, archiving and secure disposal

Recommended textbooks

  • Fundamentals of Data Engineering — Joe Reis & Matt Housley

    The best current overview of the whole discipline

  • DAMA-DMBOK: Data Management Body of Knowledge — DAMA International

    2nd ed. — the governance framework this course follows

  • The Data Warehouse Toolkit — Ralph Kimball & Margy Ross

    3rd ed. — read alongside UUY-DTS 423

How to pass UUY-DTS 412

  • Build one real pipeline end to end (ingest → transform → store → schedule), even a small one. Data engineering is understood by doing
  • Know why Parquet beats CSV for analytics (columnar, compressed, typed) — a favourite short-answer question and a genuinely useful fact
  • Data quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness) are examinable as a list — memorise them
  • Governance sounds bureaucratic until you inherit an undocumented database. Frame your answers around that reality

Other 400 Level courses

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