Course Summary
The Enterprise Big Data Engineer (EBDE®) training course and certification are designed to equip professionals with the skills and knowledge needed to excel in managing and engineering large-scale data systems. The program places a strong emphasis on building and optimizing data pipelines, which are critical for transforming raw data into actionable insights. Participants will gain expertise in implementing robust pipelines through ETL processes, batch and stream processing, and advanced data integration techniques. They will also learn to work with both structured and unstructured data using SQL for relational databases and NoSQL technologies, ensuring scalability and efficiency in diverse business environments.
A unique aspect of the EBDE certification is its holistic approach to data engineering, integrating machine learning techniques to enhance data pipelines and bridging the gap between data management and data science. Participants will also delve into key topics like distributed systems, real-time data processing, and advanced architectures, with practical exposure to tools such as Hadoop, Spark, Kafka, and Flink. The course also emphasizes the importance of data security and privacy, preparing professionals to safeguard sensitive information and comply with regulatory standards while handling complex data ecosystems.
By the end of the program, learners will be proficient in designing scalable, secure, and efficient data solutions tailored to organizational needs. They will have hands-on experience building interactive dashboards, visualizations, and real-world data engineering projects, making them well-prepared to contribute to data-driven decision-making processes. Whether pursuing a career as a Big Data engineer or further academic study, EBDE-certified professionals will possess the technical and strategic expertise required to thrive in the fast-evolving field of data engineering.
detailed course Information
The Enterprise Big Data Engineer (EBDE®) course equips participants with the practical skills, foundational knowledge, and advanced techniques necessary to excel in the field of data engineering. Upon completion, participants will be able to:
- Explain the foundational concepts and technologies in data engineering, including the differences between structured and unstructured data and their respective storage and processing solutions.
- Describe the principles and techniques of working with relational databases using SQL, and the methods for handling unstructured data with NoSQL databases.
- Demonstrate proficiency in ETL (Extract, Transform, Load) processes, batch processing, and real-time stream processing, and understand their applications in various data integration scenarios.
- Design and implement efficient data pipelines for seamless data movement and processing, ensuring optimal performance and scalability.
- Discuss and apply different data architectures, evaluating their suitability based on specific use cases and business requirements.
- Utilize machine learning techniques to enhance data engineering workflows and solve practical data-related problems.
- Implement security measures and ensure compliance with data privacy regulations to protect sensitive information within data engineering processes.
- Identify key functions, roles, and competences necessary for effective data engineering within enterprise organizations and understand the importance of collaboration with other data-related roles to capture long-term value from data initiatives.
These objectives provide learners with the theoretical knowledge and practical skills necessary to design, manage, and optimize data engineering solutions in real-world scenarios.
The Enterprise Big Data Engineer (EBDE®) course is a structured, hands-on, and dynamic program designed to provide participants with the knowledge and practical skills required to design, implement, and manage robust data engineering solutions. Delivered over 30 hours of instructor-led training, the program is divided into distinct modules that progressively build expertise in critical aspects of data engineering.
Module 1: Foundations of Data Engineering
- Explore the foundational concepts and key technologies in data engineering
- Understand the distinctions between structured and unstructured data
- Learn storage and processing solutions tailored to different data types
Module 2: Relational and NoSQL Databases
- Master the principles of relational databases and proficiency in SQL
- Delve into NoSQL databases and methods for managing unstructured data
- Compare database types to select optimal solutions for business needs
Module 3: Data Integration and Processing
- Gain hands-on expertise in ETL (Extract, Transform, Load) workflows
- Understand batch processing and real-time stream processing techniques
- Apply these processes to enable seamless data integration and movement
Module 4: Designing Scalable Data Pipelines
- Learn to design, implement, and optimize data pipelines
- Explore strategies for ensuring pipeline performance and scalability
- Work through scenarios involving complex data pipeline challenges
Module 5: Data Architectures and Use Cases
- Examine modern data architectures and their components
- Evaluate different architectures for specific business scenarios
- Design tailored solutions that align with organizational goals
Module 6: Machine Learning for Data Engineers
- Discover the integration of machine learning in data engineering workflows
- Utilize ML algorithms to enhance data processing and analytics
- Solve practical problems through real-world case studies
Module 7: Data Security and Compliance
- Implement robust security measures in data engineering processes
- Ensure compliance with data privacy regulations and standards
- Learn best practices for safeguarding sensitive information
Module 8: Roles and Collaboration in Data Engineering
- Identify key roles and competencies essential for data engineering success
- Understand how to collaborate with data scientists, analysts, and stakeholders
- Build strategies to capture long-term value from enterprise data initiatives
This structured approach ensures that participants develop a deep understanding of data engineering concepts, tools, and best practices, preparing them to address real-world challenges and excel in their roles as Big Data Engineers.
The Enterprise Big Data Engineer (EBDE®) certification is tailored for professionals responsible for designing, implementing, and managing robust data systems and infrastructure within organizations. The primary audience includes:
- Data Engineers
- Database Administrators
- Data Architects
- ETL Developers
This certification is also highly beneficial for software engineers, IT professionals, and system analysts seeking to transition into data engineering roles or broaden their expertise in managing complex data ecosystems.
- Exam Format: Closed-book exam with 80 multiple-choice questions.
- Passing Criteria:
- Standard pass mark: 65% (52 correct answers).
- Trainer pass mark: 75% (60 correct answers).
- Duration: 120 minutes; candidates taking the exam in a non-native language receive an additional 25% time (total 150 minutes).
- Question Types: Includes classic questions, negatively worded questions, and select-evaluate tasks requiring candidates to choose the correct options from provided statements.
- Bloom’s Levels: Questions test understanding (Level 2) and application of concepts and skills (Level 3).
- No Negative Marking: Incorrect or unanswered questions receive no penalty.
Candidates should prepare using the Enterprise Big Data Engineer Guide to ensure they grasp key concepts and are ready to apply their knowledge in real-world scenarios.
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Testimonials & Course Reviews
The EBDE course provided a deep dive into Big Data engineering, and I found it extremely valuable in my role at Telefónica. The lessons on data pipelines and real-time processing with Kafka were particularly insightful. I now feel equipped to design scalable and efficient systems that meet the needs of our organization.
The Big Data Engineer course was exactly what I needed for my role at Banco do Brasil. As a Data Engineer, I’m constantly working with large, complex data systems, and I was looking for a course that could give me practical skills I could apply immediately. This course did just that.The biggest takeaway for me was the deep dive into building efficient, scalable data pipelines. I deal with a lot of structured and unstructured data, and the lessons on designing and implementing pipelines were spot on for the challenges I face every day. The course also covered ETL processes, batch processing, and real-time stream processing, all of which are crucial for integrating data from different sources across the bank.
The EBDE course exceeded my expectations. I particularly enjoyed the modules on ETL processes and stream processing. These are essential skills for any data architect, and the course provided the knowledge to handle large-scale data systems. It’s exactly what I needed to enhance our Big Data capabilities at Capgemini.
This course was a great learning experience. The focus on different data architectures, batch, and stream processing gave me a well-rounded understanding of how to design efficient systems. The practical aspects of the course helped me directly apply these concepts to my work at Emirates Group, especially in managing our large data flows.
The Enterprise Big Data Professional course was an exceptional experience from start to finish. As a seasoned Data Scientist, I was initially skeptical about enrolling in an entry-level program, but this course surpassed my expectations. It offered a comprehensive overview of Big Data concepts, blending theoretical insights with practical applications.
One of the standout features was the course’s focus on strategy—understanding how Big Data aligns with business objectives was enlightening, even for someone with my background. The modules on contemporary Big Data architectures and algorithms provided a fresh perspective and introduced techniques I hadn’t encountered before.
The instructors were top-notch, simplifying complex topics like machine learning and artificial intelligence without diluting their depth. The exercises and sample templates added immense value, allowing me to see immediate applications in my ongoing projects. This certification has enhanced my ability to communicate Big Data’s potential to stakeholders and opened doors for more strategic roles in my organization. I’d recommend this course to anyone who wants to elevate their understanding of Big Data, regardless of their experience level.
