Choosing a DASCA Credential

ABDE™ aspirants seek to develop in learners, a strong and complete generic, as well as platform-based understanding of the concepts, principles, tools, and techniques. ABDE™ aspirants are expected to know Big Data and its application, Hadoop technologies and its applications including Pig, Hive, Sqoop, Flume, Yarn, Spark, Scala etc.

Ideal for you if you are finishing or have completed your Undergraduate Degree in Information Technology/ Computer Science OR Diploma in Computer Programming/ Software Engineering from an accredited institution; You should certainly display a very good basic-level understanding of the fundamentals of programming; logic and database management.

• Hadoop development and implementation.
• Designing, building, and supporting Hadoop applications.
• Turn business requirements into conceptual, logical, and physical design for various data types and large volumes.
• Hands-on development of code which helps in data injection as well as data analysis.

SBDE™ aspirants seek to develop in learners, a strong and complete generic, as well as platform-based understanding of the concepts, principles, tools, and techniques. SBDE™ aspirants are expected to know Big Data and its application, Hadoop technologies and its applications including Pig, Hive, Sqoop, Flume, Yarn, Spark, Scala etc., Big Data Analytics, and integration with Big Data technologies.

Should be your choice if you have been working as a programmer or a software engineer for the last two years and you exhibit advanced knowledge of the techniques and tools of programming; database etc. Of course, you will also have to hold at least an Undergraduate Degree in Information Technology/ Computer Science OR Diploma in Computer Programming/ Software Engineering from an accredited institution.

• Hadoop development and implementation.
• Designing, building, and supporting Hadoop applications.
• Turn business requirements into conceptual, logical, and physical design for various data types and large volumes.
• Hands-on development of code which helps in data injection as well as data analysis.

ABDA™ aspirants seek to develop in learners, a strong and complete generic, as well as platform–based understanding of the concepts, principles, tools, techniques, and technologies of designing, developing, and applying analytics frameworks and utilities required for sharper information management and decision making. ABDA™ aspirants are expected to know Big Data and its application, Analytics and its application, R & it's implementation, Mobile Analytics, Statistical Analysis tools, techniques, and methodologies etc.

This is an ideal certification for you if you are finishing, or have just finished your Undergraduate/ Bachelor's Degree in Information Technology/ Computer Science/ Undergraduate Degree in Business/ Management/ Statistics/ Economics/ Mathematics OR Diploma in Computer Programming or Software Engineering OR Diploma in Business/ Management from an accredited institution. Indeed, you are expected to be very confident about your basic-level understanding of the principles and tools of Statistics and should love problem-solving using numbers and analysis.

• Interpret data, analyze results using statistical techniques and provide ongoing reports.
• Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality.
• Acquire data from primary or secondary data sources and maintain databases/data systems.
• Identify, analyze, and interpret trends or patterns in complex data sets.
• Locate and define new process improvement opportunities.

SBDA™ aspirants seek to develop in learners, a strong and complete generic, as well as platform–based understanding of the concepts, principles, tools, techniques, and technologies of designing, developing, and applying analytics frameworks and utilities required for sharper information management and decision making. SBDA™ aspirants are expected to know Big Data technologies and its application, Big Data Analytics and its application, R & it's implementation, Mobile Analytics, Visualization, Machine learning, Artificial Intelligence, Statistical Analysis tools, techniques, and methodologies etc.

SBDA™ works strong for individuals who are in the analytics and research space for 2 years or more, and hence show excellent skills on solving problems using Statistics and Quantitative methods; knowledge of RDBMS and Spreadsheets; awareness about Big Data uses in decision-making. This is an ideal certification for you if you are finishing, or have just finished your Undergraduate/ Bachelor's Degree in Information Technology; Computer Science OR Undergraduate Degree in Business/ Management/ Statistics/ Economics/ Mathematics OR Diploma in Computer Programming/ Software Engineering OR Diploma in Business/ Management from an accredited institution.

• Interpret data, analyze results using statistical techniques, and provide ongoing reports.
• Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality.
• Acquire data from primary or secondary data sources and maintain databases/data systems.
• Identify, analyze, and interpret trends or patterns in complex data sets.
• Work closely with management to prioritize business and information needs.
• Locate and define new process improvement opportunities.

SDS™ aspirants seek to develop in learners, a strong and complete generic, as well as platform–based understanding of the concepts, principles, tools, techniques, and technologies of designing, developing, and applying analytics frameworks and utilities required for sharper information management and decision making. SDS™ aspirants are expected to know advanced knowledge of Statistical Analysis tools, techniques, and methodologies; exposure to different big SDS™ & analytics language and platforms. SDS™ aspirants should source and analyze data from various angles with different business insights, determine what it indicates, and recommend ways to apply the data.

If you're a seasoned campaigner with 5 years plus of exposure in leading Big Data analytics or science function, you are fit for the Data Scientist Credential. You will be required to have at least an Undergraduate/ Bachelor's Degree in Information Technology/ Computer Science OR Undergraduate/ Bachelor's Degree in Business/ Management/ Statistics/ Economics/ Mathematics OR Diploma in Computer Programming/ Software Engineering OR Diploma in Business/ Management from an accredited institution. In the SDS™ program, you will thrive if you already possess Advanced-level knowledge and skills of statistical analysis techniques and tools; exposure to analytics platforms like SPSS/ SAS; a good exposure to R; quantitative methods; fundamentals of object oriented programming and RDBMS, and yes, also the confidence of having worked on popular/ common Big Data programming and analytics platforms and technologies.

• Develop and plan required analytic projects in response to business needs.
• In conjunction with data owners and department managers, contribute to the development of data models and protocols for mining production databases.
• Develop new analytical methods and/or tools as required.
• Contribute to data mining architectures, modeling standards, reporting, and data analysis methodologies.
• Conduct research and make recommendations on data mining products, services, protocols, and standards in support of procurement and development efforts.
• Work with application developers to extract data relevant for analysis.
• Collaborate with unit managers, end users, development staff, and other stakeholders to integrate data mining results with existing systems.
• Provide and apply quality assurance best practices for data mining/analysis services.
• Adhere to change control and testing processes for modifications to analytical models.
• Create data definitions for new database file/table development and/or changes to existing ones as needed for analysis.
• Determine required network components to ensure data access, as well as data consistency and integrity.
• Respond to and resolve data mining performance issues. Monitor data mining system performance and implement efficiency improvements.
• Manage and/or provide guidance to junior members of the team.