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Data Science Council of America Credentialing Framework/data-science-council-of-america-credentialing-framework/index

The Credentialing Framework

DASCA Big Data Certifications prove potential and promise for professional excellence in the most challenging of Data Science roles most reliably because they are based on the world’s most robust platform- and vendor-independent standards and framework of pre-requisites of Data Science knowledge.

DASCA Credentialing Framework

DASCA Certifications Have Rigorous Foundations

All DASCA Credentials are based on the world’s first, the only, and the most rigorously unified body of knowledge on the Data Science profession today. The DASCA Data Science Body of Knowledge (DASCA DSBoK™) defines the knowledge areas in which professionals are tested for their promise, capacities, and potential to excel in their roles as Big Data Engineers, Big Data Analysts, and Data Scientists. The DASCA DSBoK™ not only provides the basis for DASCA Certification examinations, but also defines the curricula around which the DASCA examination preparation kit has been prepared.

The DASCA DSBoK™ is fleshed around the ground-breaking Essential Knowledge Framework (EKF™) of DASCA. It spells out for the first time ever in the world a robust architecture of generic knowledge essential for Data Science professionals to have if they want to excel in their roles. The EKF™ and the DASCA DSBoK™ together serve to transform emerging Big Data roles and jobs mature into compact, well–defined professions around the world. Together, they have established the first unbiased, vendor-neutral global system of assessing suitability of individuals for various Big Data roles. Indeed, the EKF™ and the DASCA DSBoK™ have also defined the most reliable platform and a scientific basis for Big Data educators and recruiters, to design high-impact learning and hiring programs.

DASCA-DSBoK™ & DASCA-EKF™

DASCA Credentials are fleshed out of the DASCA Data Science Essential Knowledge Framework (EKF Release:11-1.3) and governed in accordance to the DASCA Data Science Body of Knowledge (DSBoK™).

The DASCA-EKF™ knowledge standards framework defines dimensions in which possession of knowledge is critical for aspiring and harnessed Data Science professionals to achieve professional excellence. Exams for DASCA Credentials are based on the EKF™-pivoted DASCA-DSBoK™ and available in 180+ countries.

EKF Release: 11 knowledge framework is the world’s first and the only research-curated professional excellence assurance model for the Data Science profession today. It enunciates the architecture of essential knowledge which individuals planning to enter the Data Science profession or those who are already working as Big Data Analysts, Big Data Engineers, and Data Scientists, need to possess to be able to consistently perform at high levels of excellence.

The EKF™ framework standardizes what Data Science professionals need to know, understand and be able to do on the basis of a DASCA Credential. In a related vein, the framework also demonstrates how professionals can advance to higher levels of credential-qualifications within the DASCA credentialing system. The DASCA Certifications are available in 180+ countries via the DASCA examination global network and training companies, workforce development agencies, higher-education institutions, universities, business schools, and colleges around the world are joining DASCA platform.

DASCA-DSBoK
Essential

Knowledge Framework

The Essential Knowledge Framework (EKF™) of the Data Science Council of America was crystallized after extensive research involving hundreds of technology experts, senior recruiters, evangelists, platform developers, and Data Science professionals working for leading global Big Data solution providers across the world. Structurally, the DASCA-EKF™ spells out 30 core knowledge topics across its 5 essential knowledge dimensions or prongs – essentially the aspects along which having knowledge is deemed critical by DASCA for individuals who desire to turn–in explosive performance in their jobs, and do it consistently. Worldwide advocacy programs by DASCA partners are encouraging Data Science professionals internationally to use the EKF™ as a convenient, complete roadmap for planning their professional capabilities development, advancing in their careers, and accomplishing bigger results in their jobs.

Indeed, EKF™ is fundamental to all the three DASCA Certification tracks. It seeks to meet two aims: For Data Science professionals, it aims to crisply enunciate the areas where acquiring knowledge is essential for successful career starts, job performance, and growth; while for employers, the EKF™ intends to provide a reliable research–backed listing of performance–critical knowledge areas in the four most important professional practice vectors in Big Data – Big Data Analytics, Big Data Engineering, and Data Science.

The DASCA bouquet includes six certification programs along three professional tracks: Big Data Analyst (ABDA™ & SBDA™), Big Data Engineer (ABDE™ & SBDE™), Data Scientist (SDS™ & PDS™). These credentials are emerging as the world's most robust and trustworthy benchmark–qualifications for top–end Data Science professionals, demonstrating to the global technology community that DASCA Credential-holders are among the fittest around that we may have for the most challenging of assignments, projects, roles, and responsibilities as they may come in the Big Data industry.

  • Framework for Engineer

    Framework forEngineer

    Check out the core areas in which the world’s finest Big Data Developers & Engineers are expected to prove they have the knowledge & proficiencies required to excel in their art.

  • Framework for Analyst

    Framework for Analyst

    The DASCA essential knowledge framework for Big Data Analysts enunciates dimensions in which knowledge of concepts, techniques, and tools are mandatory for top jobs.

  • Framework for Scientist

    Framework forScientist

    The DASCA Essential Knowledge Framework (EKF™) includes a number of strategic & business knowledge dimensions which a world-class Data Scientist requires to attend to.

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