Data Warehouses, ETL, and Big Data Governance

This chapter covers broader data environments that combine many sources for analysis and reporting. ISC focuses on the governance and control challenges that arise when scale, variety, and transformation complexity increase.

In This Chapter

• Data Warehouses, Data Lakes, and Data Marts compares the main large-scale storage and reporting environments.
• ETL (Extract, Transform, Load) Processes and Controls explains how data is moved and reshaped in a controlled way.
• Managing Structured, Semi‑Structured, and Unstructured Data covers the control implications of different data forms.
• Governance Challenges in Big Data addresses oversight, quality, and accountability problems in large environments.

How to Use This Chapter

• Read this chapter when analytics topics move beyond traditional operational systems.
• Focus on how movement and transformation of data create control risk.
• Revisit it whenever an ISC question depends on whether large data environments can be trusted for reporting or monitoring.

In this section

• Data Warehouses, Data Lakes, Data Marts, and Their Use Cases
  Data warehouses, data lakes, data marts, and their use cases.
• ETL Processes, Transformation Risk, and Related Controls
  ETL processes, transformation risk, and related controls.
• Managing Structured, Semi-Structured, and Unstructured Data
  Managing structured, semi-structured, and unstructured data.
• Big Data Governance Challenges, Privacy, and Accountability
  Big data governance challenges, privacy, and accountability.