How Are DASCA Certifications Structured Across Levels and Domains?

About DASCA and Its Credentialing Framework

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How are DASCA certifications structured across levels and domains?

Data Science Council of America (DASCA) structures its certifications across clearly defined levels and domains to reflect increasing responsibility, complexity, and professional maturity in data-driven roles.

Certification Levels

DASCA certifications are organized into progressive levels that align with career stage rather than academic background alone.

  • Associate-level certifications are designed for early-career professionals, recent graduates, and individuals transitioning into data analytics, or data engineering roles. These certifications focus on foundational concepts, core techniques, and applied understanding required to operate in entry-level or junior roles.
Associate Big Data Engineer (ABDE™) Associate Big Data Analyst (ABDA™)
  • Professional-level certifications are intended for working professionals with hands-on experience. They assess the ability to apply methods, tools, and frameworks in real-world environments, including problem formulation, analytical reasoning, and practical execution.
Senior Big Data Engineer (SBDE™) Senior Big Data Analyst (SBDA™)
  • Senior and advanced certifications like are designed for experienced practitioners and leaders who operate at a higher level of responsibility. These credentials emphasize judgment, system-level thinking, architectural understanding, governance awareness, and the ability to make informed decisions in complex data environments.
Senior Data Scientist (SDS™) Principal Data Scientist (PDS™)

Progression across levels is not automatic. Each certification has defined expectations, and candidates are expected to demonstrate readiness appropriate to the certification they attempt.

Certification Domains

In addition to levels, DASCA certifications are organized across distinct but related domains:

  • Data Science, focusing on statistical reasoning, modeling, machine learning concepts, and analytical problem-solving
  • Data Analytics, focusing on data interpretation, business analysis, visualization, and decision support
  • Data Engineering, focusing on data pipelines, architectures, integration, and operational reliability

Each domain reflects different professional roles and responsibilities. While there may be conceptual overlap, certifications are designed to assess domain-specific competence.

To help determine the certification that best aligns with your academic background and professional experience, use the Eligibility Checking Tool.

Alignment between levels and domains

Not all domains necessarily follow identical level structures, and not every professional is expected to progress through every level or domain. DASCA’s framework allows candidates to pursue certifications that align with their role, experience, and career direction rather than a single linear pathway.

Certification structure is reviewed periodically to ensure continued relevance to evolving industry practices, technological shifts, and professional expectations.

DASCA certifications are structured to provide clear differentiation by both career stage and functional domain, enabling employers, institutions, and professionals to interpret credentials with clarity and confidence.

Ready to Advance Your Data Science Career?

Download the program brochures to learn about the exam coverage, competencies, and career alignment.

Ready to Advance Your Data Science Career?

Download the program brochures to learn about the exam coverage, competencies, and career alignment.

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