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DASCA Certifications Have Strong Foundations

The DASCA Data Science body of knowledge 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. It not only provides the basis for the certification programs but also 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™). It consists of a robust architecture of generic knowledge essential for Data Science professionals wanting to excel in their roles. The DASCA- DSBoK™ and Essential Knowledge Framework serve to transform emerging Big Data roles and jobs into compact, well–defined professions around the world. Together, they have established an unbiased, vendor-neutral global system of assessing the suitability of individuals for various Big Data roles. The DASCA-EKF™ and the body of knowledge 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.

Body of Knowledge

The five-pronged DASCA-EKF™ knowledge standards framework defines 30 dimensions in which possession of knowledge and understanding is required for aspiring and harnessed Data Science professionals to achieve professional excellence. The EKF™ standardizes what professionals need to know, understand and be able to do as DASCA certified big data analysts, big data 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 knowledge-readiness of candidates to fulfil 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.


Essential Knowledge Framework

The framework was finalized 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 Essential Knowledge Framework spells out dozens of core knowledge topics across five essential knowledge dimensions.

The DASCA-EKF™ is fundamental to all three DASCA Certification tracks. It seeks to meet two aims: 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; while 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 Big Data – Big Data Analytics, Big Data Engineering, and Data Science.

There are six certification programs along three professional tracks: Big Data Analyst (ABDA™ and SBDA™), Big Data Engineer (ABDE™ and SBDE™), and Data Scientist (SDS™ and PDS™). These credentials are emerging qualifications for Data Science professionals and demonstrate to the global technology community that DASCA Credential-holders are among the most prepared professionals for the most challenging assignments, projects, roles, and responsibilities in Data Science profession today.

  • Framework for Engineers

    Covers knowledge on tools, platforms, principles and concepts of creating big data software applications.

  • Framework for Analysts

    Communicates/conveys cross-platform concepts, techniques, and tools for distilling insights out of big data.

  • Framework for Scientists

    Comprises a range of strategic and business knowledge dimensions critical for data scientists in large organizations.

Currently, DASCA offers six international certification programs

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