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Explore DASCA’s comprehensive certification paths tailored for professionals in:
Validate your expertise in designing, building, and managing Big Data infrastructure.
ABDE™ Brochure SBDE™ Brochure
Master the tools and techniques for advanced data analysis and insight generation.
ABDA™ Brochure SBDA™ Brochure
Become an expert in data science methodologies and applications.
SDS™ Brochure PDS™ BrochureChoose your qualification and experience level to find the DASCA certification that aligns with your career goals.
Learn about the steps to earn your DASCA certification, from application to becoming a certified professional.
DASCA certification exams are available online worldwide, accessible in 180+ countries with 5th-generation TEI technology.
Find answers to common questions about DASCA certifications, exam process and policies.
Showcase your DASCA certification with digital badges recognized worldwide.
Discover how DASCA Accreditation enhances data science and AI education, ensuring global recognition and academic excellence.
Understand how DASCA Accreditation sets the benchmark for excellence in data science and AI education, aligning institutions with global industry standards.
Examine the framework that upholds high benchmarks for curriculum, faculty expertise, and industry relevance in data science and AI programs.
Understand the institutional and program-level requirements to assess your readiness for pursuing DASCA Accreditation.
Explore the step-by-step process to achieve DASCA Accreditation through a rigorous, globally benchmarked, and digitally powered evaluation.
Discover how DASCA Accreditation enhances institutional reputation, academic quality, and global competitiveness in data science and AI education.
Access comprehensive guides, support tools, and subsidy programs designed to assist institutions throughout their accreditation journey.
Learn about the global network of academic and industry experts who support institutions in delivering high-quality data science and AI education.
Get answers to common questions about institutional eligibility, the accreditation process, ongoing compliance and more.
Begin your DASCA accreditation journey and position your institution among global leaders in data science and AI education.
Data Science professionals are evaluated based on their respective knowledge fields, as outlined by the DASCA Data Science body of knowledge. This is to gauge their promise, capacity, and potential to excel as Data Science Engineers, Data Science Analysts, and Data Scientists. This lays the foundation for the certification programs and defines the curricula around which the DASCA examination preparation kit has been prepared.
The DASCA body of knowledge is built around the Essential Knowledge Framework (EKF™). Data Science professionals, passionate about excelling in their roles, can rely on the robust architecture of generic knowledge. The DASCA- DSBoK™ and Essential Knowledge Framework function to transform the new emerging Data Science roles and jobs into clearly structured and compact professions worldwide. Together, they have established an unbiased, vendor-neutral global system of assessing the suitability of individuals for various Data Science roles. The DASCA-EKF™ and the body of knowledge have also defined the most reliable platform and a scientific basis for Data Science educators and recruiters to design high-impact learning and hiring programs.
The five-pronged DASCA-EKF™ knowledge standards framework defines 30 dimensions in which proficiency in knowledge and comprehension is required for aspiring and skilled Data Science professionals to achieve professional excellence. The EKF™ standardizes what professionals need to know, understand, and be able to do as DASCA-certified data science analysts, data science engineers, and data scientists. The framework also indicates the varying levels of knowledge, professionals need to have in these areas as data analysts, data engineers, and data scientists. Exams for DASCA credentials are based on the body of knowledge derived from the first four prongs of the EKF™. While the questions in DASCA certification exams seek to evaluate the knowledge-readiness of candidates to fulfill the requirements laid down in the first four EKF™ prongs, the fifth prong of the EKF™ on professional roles and careers is merely suggestive and candidates are not examined on this.
The framework was sanctioned after extensive research involving hundreds of technology experts, senior recruiters, evangelists, platform developers, and Data Science professionals working for leading global Data Science solution providers across the world. Structurally, the Essential Knowledge Framework elucidates dozens of core knowledge topics across five essential knowledge dimensions.
The DASCA-EKF™ is intrinsic to all three DASCA Certification tracks. It seeks to meet two aims. One for Data Science professionals, it aims to articulate the areas where acquiring knowledge is essential for starting a successful career and ensuring impressive job performance and growth. And then for employers, the framework intends to provide a reliable research-backed listing of performance-critical knowledge areas in the three most important professional practice vectors in Data Science namely, Data Science Analytics, Data Science Engineering, and Data Science.
Across the three professional tracks, there are six certification programs: Data Science Analyst (ABDA™ and SBDA™), Data Science Engineer (ABDE™ and SBDE™), and Data Scientist (SDS™ and PDS™).
These credentials are emerging qualifications for Data Science professionals. Furthermore, they demonstrate to the global technology community that DASCA credential holders are among the most methodically prepped professionals. They are equipped to address any intricately critical assignments, projects, roles, and responsibilities in today’s modern Data Science profession.
Covers knowledge on tools, platforms, principles and concepts of creating big data software applications.
Communicates/conveys cross-platform concepts, techniques, and tools for distilling insights out of big data.
Comprises a range of strategic and business knowledge dimensions critical for data scientists in large organizations.
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