Explore KSACs by Pathway
In late 2025, the Partnership pulled together members of industry from across tech to share how the in-demand skillsets for entry-level roles in their fields have changed in the last two years. The Knowledge, Skills & Abilities and Credentials (KSACs) below reflect their feedback on entry-level expectations, especially in a tech workplace increasingly shaped by AI.
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5. Data Quality, Validation, and Monitoring
| Label | KSAC Description | Bloom's Taxonomy Level | |
|---|---|---|---|
| a | Explain data quality dimensions (accuracy, completeness, consistency, integrity, timeliness) | knowledge | 3 |
| b | Identify common data quality issues such as missing values, outliers, duplication, and inconsistent definitions | knowledge | 3 |
| c | Perform data profiling and summarization to understand distributions, trends, and anomalies | skill | 3 |
| d | Perform data validation and sanity checks to confirm data meets expected rules and constraints | skill | 3 |
| e | Review AI-generated data summaries or transformations for accuracy and alignment with source or expected data | skill | 3 |
| f | Explain continuous data quality monitoring concepts, including why proactive monitoring is necessary in automated environments | knowledge | 3 |
| g | Identify data leakage risks in analytics and AI pipelines, including unintended use of future or restricted data | knowledge | 3 |
| h | Assess data fitness for specific analytical or AI-driven use cases, considering quality, scope, and limitations | ability | 4 |
Credentials
Vendor Certifications - DBMS
- Oracle Associate
- Microsoft
- IBM
Vendor Certifications - Cloud
- AWS
- Oracle
- Microsoft