Data Driven Analytics

At Mettl, an in-house team of experts on data analytics ensures the efficacy of certifications, which depend on the validity and credibility of the certification criteria. By considering various performance parameters, we achieve a clear, actionable reporting of skill assessments.

Precise, Accurate Analysis with Data Sciences

Linear programming

To develop a numerical basis for the pass/fail criteria based on qualitative research

Refining with Statistical Techniques

Fine tuning of our numerical basis using several statistical techniques and data clustering algorithms such as k-means and hierarchical clustering , which in turn eliminate practical anomalies


To map candidate performances into broad clusters to segregate and analyze different pockets of skill proficiency.


Continuous recalibration

of test scores and assessment content to ensure we reach a defined basis for our certification criteria.

Industry Validation

The Mettl team also utilizes Industry Validation, identified as the best method to validate the quality of training and certifications awarded to candidates. Detailed analyses are conducted to measure the efficacy of certifications on several demographics.

Detailed analyses are conducted to measure the efficacy of certifications on several demographics such as:

Job Role Variations

Regional & Language Study

Study by tier of towns

Study by Gender & Age

This readily measures the job readiness of a candidate by comparing him or her to top performers in an organization.

Reporting that is driven by data

Removes Agency Rating Bias

Removes Agency Rating Bias

Achieve Stable and Fair Benchmarks

Achieve Stable and Fair Benchmarks

Reinforced Validity

Reinforced Validity

Pre-cursor to Industrial Validation

Pre-cursor to Industrial Validation

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