Description

Certification Name: Certified Big Data Engineer

Global Occupational Skill Standard – GOSS ID: GOSS/CIT/CBDE/V1

Duration: One Month

Eligibility: Graduation or Equivalent is required.

Objective: The Certified Big Data Engineer course is designed to equip professionals with the skills and knowledge to design, build, and manage large-scale data processing systems. The course covers big data technologies and frameworks such as Hadoop, Spark, Kafka, and NoSQL databases, as well as data ingestion, storage, processing, and analytics. Participants learn to handle structured and unstructured data, optimize data pipelines, ensure data quality, and implement scalable and high-performance solutions.

Certification: Within 5 days after Completion of Online Assessment.

Get ready to join the Journey to become a GSDCI Certified Professional  – International Certification and Assessment Body.

Steps to become a GSDCI Certified Professional:

Step 1: Select your certification you want to pursue.

Step 2: Click on get certified tab, new pop up window will open.

Step 3: Click on pay certification fee, you will be redirected to billing details page.

Step 4: Fill your details and click on pay certification fee, you will be redirected to payment gateway, pay fee by any available options like Card (Debit/Credit), Wallet, Paytm, Net banking, UPI and Google pay.

Step 5: You will get Login Credentials of Online E-Books and Online assessment link on your email id, within 48 hrs of payment.

Step 6: After completion of online assessment, you can download your Certificate Immediately.

Assessment Modules:

Module 1 – Big Data Ecosystem & Fundamentals: Introduction to big data concepts and characteristics (volume, velocity, variety, veracity), Big data use‑cases and business value, Traditional data processing vs big data processing, Big data architecture components: data ingestion, storage, processing, analytics, Distributed systems basics (clusters, nodes, fault tolerance), Overview of major big data tools and frameworks

Module 2 – Data Storage & Modeling for Big Data: File systems and distributed storage: HDFS, cloud object storage, data lakes, NoSQL vs SQL in big data context, Data modeling for large scale: schema‑on‑read vs schema‑on‑write, Columnar stores, key‑value and document stores, Partitioning, sharding, indexing for large datasets, Data ingestion formats and optimized storage formats (Parquet, ORC, Avro)

Module 3 – Big Data Processing Frameworks: Batch processing with frameworks like Apache Hadoop MapReduce and YARN, In‑memory and distributed processing with Apache Spark (RDDs, DataFrames, Spark SQL), Streaming data processing and real‑time frameworks (e.g., Spark Streaming, Flink), Performance tuning and optimization of big data jobs, Handling fault‑tolerance, resource management and scalability in processing

Module 4 – Data Ingestion, ETL/ELT & Workflow Orchestration: Extracting data from diverse sources (databases, logs, sensors, APIs), Transforming and cleaning data at scale, Loading data into target stores or warehouses, Choosing ETL vs ELT strategies in big data context, Workflow orchestration using tools like Apache Airflow, automation, scheduling and monitoring of pipelines, Change‑data‑capture (CDC), incremental loads and streaming ingestion mechanisms

Module 5 – Big Data Analytics, Machine Learning & Visualization: Exploratory data analysis on big datasets, Feature engineering at scale, Applying machine learning algorithms (classification, clustering, recommendation systems) in big data environments, Integrating with libraries/frameworks for ML in big data (e.g., Spark MLlib), Real‑time analytics, dashboards and visualisation tools for large‑scale data, Monitoring and evaluating analytics outcomes and deriving business insights

Module 6 – Cloud, Governance, Security & Emerging Trends in Big Data: Deploying big data solutions on cloud platforms (AWS, Azure, GCP) and hybrid architectures, Data governance, lineage, metadata management and data cataloguing in big environments, Security, privacy and compliance in big data (encryption, access control, GDPR/HIPAA concerns), Cost‑optimization, resource management and operational monitoring in big data clusters, Emerging trends: data mesh, lakehouse architecture, serverless big data, edge‑analytics

GSDCI Online Assessment Detail:

• Duration- 60 minutes.
• Number of Questions- 30.
• Number of Questions from each module: 5.
• Language: English.
• Exam Type: Multiple Choice Questions.
• Maximum Marks- 100, Passing Marks- 50%.
• There is no negative marking in any module.

Benefits of Certification:

🌍 1. Global Recognition & Credibility – Stand out worldwide with a certification that opens doors across borders. Trusted by employers, respected by institutions, and recognized in over 100 countries.

📜 2. Quality Assurance through ISO Certification – Certified to global ISO standards, our programs deliver excellence, consistency, and a benchmarked learning experience that speaks for itself.

💼 3. Career Advancement & Employability – Enhances your resume and increases chances of promotions or job offers.

🤝 4. Non-Profit Trust Factor – Certifications from non-profit organizations are mission-driven rather than profit-driven.

📚 5. Access to Verified Learning & Resources – Often includes e-books, mock tests, and online support without hidden costs.

🔍 6. Transparency & Online Verification – Certifications come with a unique Enrolment ID for easy online verification by employers and institutions.

⏳ 7. Lifetime or Long-Term Validity – Certifications usually have lifetime validity or long-term recognition, reducing the need for frequent renewals.