Certifications from Data Science Council of America (DASCA)
The Data Science Council of America (DASCA) advents state-of-the-art paradigms of evaluating and certifying skills, competence and employability of technical and managerial workforce and professionals working in the Big Data technology space. Aspiring and working Big Data professionals study and prepare for DASCA certification examinations from the world’s finest platform-independent knowledgeware & learning kit on Big Data yet, and earn their DASCA credentials after qualifying these examinations conducted in Pearson centers in select locations around the world.
Find the right DASCA certification
Four DASCA credentials are currently available on the Pearson platform for the two most popular and in-demand Big Data tracks – Big Data Engineers and Big Data Analysts. Younger professionals and those who are starting out their Big Data careers may choose between ABDE™ or ABDA™; and professionals on the growth path can opt between SBDA™ and SBDE™.
ABDE™ is awarded to individuals exhibiting a proven exposure and knowledge of fundamentals in information technology as well as software designing, data structures, and programming. ABDE™ credentialed individuals have been tested successfully for their knowledge and understanding of the latest concepts, principles, methods, tools, and techniques deployed in Big Data engineering and development today. Proficiencies in back-end OOPS programming as well as knowledge of how to write high-performance, reliable, and maintainable codes and programs for clustered scale-out data processing on commonly used Big Data platforms are also tested during evaluation in order to get the ABDE™ credential. The ABDE™ individual must successfully test its understanding and command of the entire spectrum of areas that decide its promise and potential for designing, engineering, and developing a complex 21st century Big Data Management System.
ABDE™ program applicants undergo a rigorous online assessment structured to evaluate their knowledge and understanding of the accepted principles of theory and practice in the field of Big Data engineering, before being awarded the ABDE™ credential.
SBDE™ credentialed individual must assure exposures to a compelling breadth of open-source and proprietary Big Data environments, with level appropriate knowledge and skills related to design, development, coding, building, installing, configuring, and supporting Big Data applications on popular Big Data platforms like Spark and Hadoop; translating complex functional and technical requirements into detailed design and perform analysis of vast data stores and uncovering insights; ensuring information and data security; and testing prototypes. Not the least, the SBDE™ credentialed Big Data Engineers and Developers must display tested knowledge of open-source developer tools like HBase, Hive, Pig, HiveQL, among others.
SBDE™ program applicants undergo a series of rigorous online assessment structured to evaluate their knowledge and understanding of the accepted principles of theory and practice in the field of Big Data engineering, before being awarded the SBDE™ credential.
ABDA™ credential is awarded to individuals who have successfully tested their theoretical and applied exposures to the contemporary open-source and proprietary Data Analytics platforms, tools, technologies, and ecosystems. Proven understanding of statistical concepts, principles, methodologies and RDBMS in the Big Data environment for effective business and marketing decision making are validated during evaluation. A credentialed individual must understand the broad trends and fundamentals of Business, Statistics, Marketing, Research, and Information Technology to help them have a richer perspective of the Big Data Ecosystem.
ABDA™ program applicants undergo a rigorous online assessment structured to evaluate their knowledge and understanding of the accepted principles of theory and practice in the field of Big Data analysis, before being awarded the ABDA™ credential.
SBDA™ credentialed professional must exhibit in-depth understanding of how to apply concepts, principles, technologies, and tools of statistics, applied mathematics, operations research, and RDBMS. The professional must be able to manage large volumes of variegated data; design models for analysis; interpret the importance of subject data for business intelligence; as well as migrate and visualize Big Data as assignments and objectives demand. To be able to operate with full force, SBDA™ professional must possess calibrated knowledge of popular Big Data platforms, including Hadoop, Spark and must successfully test diverse analytical functions on a cross- section of all popular Big Data distribution like Hortonworks and Cloudera. SBDA™ program applicants undergo a rigorous online assessment structured to evaluate their knowledge and understanding of the accepted principles of theory and practice in the field of Big Data analysis, before being awarded the SBDA™ credential.
Training and Exam Preparation
Registrants for DASCA programs can learn and prepare on their own for their certification examinations. They can do so with the help of the Official DASCA Certification Preparation Kit published by Wiley.
Apply for a DASCA Certification Today!
The Big Data Engineer and Big Data Analyst certifications of the Data Science Council of America (DASCA) add a powerful, most international edge to the employability of professionals for the international Big Data industry. Founded on the world’s first, most robust generic Big Data knowledge framework — the EKF™.
If you aspire your career to break exciting new grounds, think of a DASCA credential, and apply today.