IICTI Certified Data Analyst

Holders demonstrate that they can apply and evaluate analytical problem framing and decision-centred metric design, advanced SQL analytics and semantic-layer modelling, data quality diagnostics and analytical data contracts and statistical inference and robust estimation for business data, plus 8 further areas, in realistic professional scenarios, as defined in the AQSCERT scheme for Data Analyst.

Who it is for: Professionals working, or preparing to work, in data roles.

1. 01Analytical problem framing and decision-centred metric design4% of the exam

   • Design metric frameworks and analysis plans that tie measurable outcomes to concrete business decisions.
   • Scope: Translating ambiguous business questions into testable hypotheses, metric trees and North Star/guardrail metrics, Goodhart effects, leading vs lagging indicators and decision-impact framing.
2. 02Advanced SQL analytics and semantic-layer modelling17% of the exam

   • Architect performant, reusable analytical queries and governed metric definitions on cloud warehouses.
   • Scope: Window functions, recursive CTEs, sessionisation, cohort and funnel queries, query plans and cost on columnar warehouses (BigQuery, Snowflake, DuckDB), dbt models and metric/semantic layers.
3. 03Data quality diagnostics and analytical data contracts13% of the exam

   • Diagnose data quality defects and their impact on conclusions, and define controls that prevent recurrence.
   • Scope: Profiling, anomaly and drift checks, missingness mechanisms (MCAR/MAR/MNAR) and imputation, deduplication and entity resolution, data contracts and tests (dbt tests, Great Expectations, Soda).
4. 04Statistical inference and robust estimation for business data14% of the exam

   • Evaluate the validity and uncertainty of statistical claims and select robust estimators for real-world data.
   • Scope: Sampling distributions, bootstrap and permutation methods, confidence vs credible intervals, heavy-tailed and skewed metrics, multiple comparisons (FDR/Bonferroni), effect sizes and power analysis.
5. 05Experimentation design and online A/B test analysis3% of the exam

   • Design and analyse controlled experiments that yield trustworthy, decision-ready results.
   • Scope: Randomisation units, sample-ratio mismatch, CUPED variance reduction, sequential testing and peeking, novelty and network effects, ratio metrics with the delta method, Bayesian experiment analysis.
6. 06Causal inference from observational data4% of the exam

   • Evaluate causal claims and select quasi-experimental methods appropriate to the available data and assumptions.
   • Scope: DAGs and confounding, difference-in-differences, synthetic control, regression discontinuity, instrumental variables, propensity score matching and weighting, sensitivity analysis.
7. 07Predictive analytics, segmentation and forecasting13% of the exam

   • Design and validate predictive and forecasting analyses whose limitations are explicitly quantified.
   • Scope: Regression and classification diagnostics, clustering and RFM/behavioural segmentation, churn and propensity models, time-series decomposition, ARIMA/ETS/Prophet, forecast accuracy (MAPE, MASE) and backtesting.
8. 08Product, customer and financial analytics3% of the exam

   • Diagnose drivers of business performance by combining product, marketing and financial analytical methods.
   • Scope: Cohort retention and LTV/CAC, funnel and attribution models (multi-touch, MMM), pricing and elasticity analysis, unit economics, variance and driver-based analysis of KPIs.
9. 09Visual analytics and dashboard architecture13% of the exam

   • Design dashboards and visual analyses that support accurate interpretation and scale across user groups.
   • Scope: Perceptual principles and chart selection, dashboard information architecture, self-service BI governance (Power BI, Tableau, Looker), performance tuning, accessibility and misleading-visualisation risks.
10. 10Analytical storytelling and executive decision support4% of the exam

    • Lead the communication of complex findings so that executives can make informed, risk-aware decisions.
    • Scope: Pyramid principle, narrative structure, communicating uncertainty and trade-offs, scenario and sensitivity analysis, stakeholder management and handling of challenged findings.
11. 11Data governance, privacy and responsible analytics8% of the exam

    • Evaluate analytical work for privacy, ethical and regulatory compliance and apply appropriate safeguards.
    • Scope: GDPR and aligned national data protection law, lawful basis and purpose limitation, pseudonymisation, k-anonymity and differential privacy, data lineage and catalogues, bias and fairness in analysis.
12. 12Leading the analytics practice and reproducible workflows4% of the exam

    • Lead an analytics function with reproducible, reviewed workflows and a prioritised, value-driven portfolio.
    • Scope: Analytics operating models (centralised, hub-and-spoke), peer review of analyses, reproducibility with notebooks, version-controlled SQL/Python and environment pinning, prioritisation and value tracking.

Question types

Single choice 100%

Delivery

Online (remote proctored), Test centre, On-site (corporate)

Retakes

Up to three attempts within any 12-month period. A 14-day waiting period applies after a first unsuccessful attempt and 30 days after a second. Each retake requires a new booking and fee. Retakes draw a different randomised form from the question bank.

Provisional cut score — psychometric validation is required before live delivery. Blueprint v1.0.

1. 1

   Register

   Create a free account and start the programme.

2. 2

   Practice

   Online practice test (coming soon).

3. 3

   Training

   Optional

   Online course or classroom — or skip it.

4. 4

   Certification

   Independent exam and certification decision.

Training is optional and does not by itself confer certification. Find a training partner