DA0-002 Data Concepts and Environments Practice Question
A national retailer is consolidating data from 40 regional stores into a central analytics platform. Each region uses different codes for the same product categories, and store managers report sales in local currencies. Before loading the data, the integration team must resolve these inconsistencies. Which two activities are appropriate steps to standardize the data? (Choose two.)
⚠ Common exam trap
The trap here is thinking that consolidation only means moving data into one place, when it also requires resolving semantic and unit mismatches during transformation.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Convert all monetary values to a single reporting currency using a defined exchange rate table.
Standardizing inconsistent data requires resolving both the category code mismatch and the currency unit mismatch. A crosswalk mapping table unifies product categories under one enterprise code set, while conversion using a governed exchange rate table unifies monetary values into one reporting currency. Deleting records, isolating databases, or deferring translation to report time all leave the inconsistencies unresolved or shift the burden downstream.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Convert all monetary values to a single reporting currency using a defined exchange rate table.
Why this is correct
Converting local currency amounts to one reporting currency using a governed exchange rate table makes financial figures directly comparable across regions. The rate table documents which rate applies to which period, preserving auditability. This standardization step addresses the unit inconsistency in monetary values and is essential before aggregating sales at the enterprise level.
- ✓
Build a mapping table that translates each region's product category codes into a single enterprise code set.
Why this is correct
A mapping table resolves the semantic inconsistency where different regions use different codes for the same category. By translating each local code to one enterprise code, the platform can aggregate and compare categories consistently. This is a standard data transformation step that preserves the original values while enabling unified analysis across all regions.
- ✗
Delete records from regions whose currency differs from the headquarters currency.
Why it's wrong here
Deleting records based on currency would discard valid sales data and bias the analysis toward one region. The goal is to make data comparable, not to remove it. Currency differences are handled through conversion using exchange rates, so deletion is both unnecessary and harmful to the completeness and accuracy of the consolidated dataset.
- ✗
Store each region's data in a separate database and report from each database independently.
Why it's wrong here
Keeping regions in separate databases preserves the inconsistency rather than resolving it, and it prevents enterprise-wide aggregation. Analysts would have to manually reconcile categories and currencies across systems, reintroducing the original problem. The consolidation effort requires standardized values in a shared platform, not isolated silos that each retain their own codes and currencies.
- ✗
Allow each region to keep its own category codes and currencies, and resolve differences during reporting.
Why it's wrong here
Deferring resolution to report time pushes the inconsistency downstream, where every analyst must replicate the same translation logic. This approach invites errors and inconsistent results across reports. Standardization should happen once during integration so that downstream consumers work with a single, trusted representation of categories and currency values.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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