Data modeling practice: Evaluate the statement below for accuracy: "Packaged (industry) data models can reduce implementation time and cost."

Introduction / Context:
Packaged or industry data models are pre-built, domain-specific schemas and reference structures provided by vendors or consulting firms. They encapsulate common entities, relationships, and vocabularies for sectors such as retail, healthcare, telecom, and finance. This question probes whether you recognize their impact on implementation speed and cost.

Given Data / Assumptions:

• The packaged model aligns reasonably well with the organization’s domain and use cases.
• Customization and gap analysis are still performed.
• Data governance and integration work remain necessary.

Concept / Approach:
Starting from a vetted blueprint avoids reinventing core structures (customers, products, orders, claims, policies). It accelerates conceptual and logical modeling, improves naming consistency, and shortens requirements discovery because common patterns are already captured. This typically reduces project risk, elapsed time, and overall cost.

Step-by-Step Solution:

Verification / Alternative check:
Compare project timelines with and without a reference model; examine reduction in modeling workshops and rework rates.

Why Other Options Are Wrong:

• Incorrect: Evidence shows typical schedule and cost reductions.
• Only for startups/OLAP/no customization: Enterprises of all sizes and both OLTP and analytics can benefit; customization is expected and factored in.

Common Pitfalls:
Adopting a model wholesale without governance; over-customizing to the point of losing upgradeability; ignoring localized regulatory requirements.

Final Answer:
Correct