Certified Big Data and Data Analytics Practitioner (CBDDAP)
Big data is a force for change that upends the conventional methods used by organizational leaders to make choices. In order to promote analytics-driven solutions within their businesses, this course gives participants the confidence to explain big data structures. With the help of this course, students will gain practical experience with the major big data technologies. The knowledge and abilities required to put together and oversee a sizable big data analytics project will be acquired by the participants. Finally, participants will learn about the data structures that support machine learning algorithms and applications of artificial intelligence conceptually.
The participants will seek to determine the types of changes that can be made through analytical processes as well as the areas within their business that can be enhanced through big data-driven solutions.
Certification Learning Objectives:
- Create strategies for data-driven solutions and big data deployment plans.
- Describe the difficulties with using standard technology like Excel and big data.
- Describe the primary drawbacks and benefits of the Hadoop ecosystem and other distributed big data frameworks.
- Discuss and demonstrate important large data computing and storage technologies, like PostgreSQL and MongoDB.
- Talk about the significance of ethics in data analytics and artificial intelligence as well as prominent machine learning methods.
- Deliver an architectural diagram for use cases centered on analytics.
- Bachelor’s Degree
- 5 years of work experience in Big Data and Data Analytics
- To be certified as CBDDAP, student should take up a 1.5 hours exam at the designated examination centers.
- The qualifying exam would consist of 50 multiple choice questions, testing core certification modules.
- Professionals with relevant experience and other qualifying criteria may be exempted from the examination.
Module 1: Introduction to Big Data Analytics
Module 2: Storing Big Data
Module 3: Computing Big Data
Module 4: Architecting Big Data Solutions