The Credentialing 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 Big Data 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 Big Data 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 Big Data 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 Big Data Science.

The DASCA bouquet includes six certification programs along three professional tracks: Big Data Analyst (ABDA™ & SBDA™), Big Data Engineer (ABDE™ & SBDE™), Big Data Scientist (SDS™ & PDS™). These credentials are emerging as the world's most robust and trustworthy benchmark–qualifications for top–end Big Data 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.