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Exam Details

• Exam Name: Big Data Certified Expert (BDCE)
• Exam Format: Multiple choice, online with remote supervision (proctoring)
• Exam Delivery: Safe Exam Browser
• Number of Questions: 50 questions: 70% scenarios / 30% conceptual
• Exam Duration: 90 minutes
• Passing Score: 70% (35 out of 50 correct answers)
• Available Languages: Spanish / English
• Attempts: Maximum 2 attempts (minimum 15 days between attempts)
• Validity: 3 years · 15 CPD credits per year

Main Subjects

• Big Data and data science fundamentals (15%): Definition of Big Data and evolution of data systems; The five Vs: volume, velocity, variety, veracity and value; Structured, semi-structured and unstructured data; Data lifecycle: generation, capture, storage, processing, analysis, visualization and disposal; Batch versus real-time (streaming) processing; Use cases in finance, healthcare, retail, manufacturing and telecommunications; CRISP-DM methodology: phases, roles and deliverables of a data team.
• Data architecture and platforms (20%): Data lakes, data warehouses, data lakehouses and data mesh; On-premise, cloud and hybrid architectures; Components of a Big Data platform: distributed storage, clusters and orchestration; HDFS: architecture, replication and fault tolerance; NoSQL databases: key-value, document, columnar and graph; MapReduce and DAG; Data partitioning, distribution and replication; Data catalogs and metadata management; High availability, disaster recovery and cost optimization.
• Massive data engineering and processing (25%): Ingestion pipeline design (ETL/ELT); Cleaning, deduplication, normalization and transformation at scale; File formats: Parquet, Avro and ORC; Schema handling and schema evolution; Apache Spark: RDDs, DataFrames and Datasets; Batch processing optimization; SQL engines on massive data: Hive, Presto, Trino and Spark SQL; Streaming with Apache Kafka, Flink and Spark Streaming; Time windows and delivery guarantees (exactly-once); Orchestration with Airflow, Oozie and Step Functions; Dimensional models, fact and dimension tables; Cost and efficiency optimization.
• Advanced analytics and machine learning (20%): Exploratory data analysis (EDA) and statistics; Regression, classification and clustering models; Supervised, unsupervised and reinforcement learning; Data preparation: sampling, balancing, encoding and scaling; Neural networks and deep learning; Dimensionality reduction; Metrics: accuracy, precision, recall, F1 and AUC; Cross-validation and data splitting; Overfitting and underfitting; Reproducible machine learning pipelines and MLOps; Data and model drift monitoring.
• Data governance, security and ethics (10%): Data governance frameworks: policies, standards, roles and responsibilities; Data stewardship and data ownership; Data quality: accuracy, completeness, consistency, timeliness and uniqueness; Data lineage and traceability; Encryption at rest and in transit; Access control and identity management; Anonymization and pseudonymization; Regulatory compliance: GDPR, CCPA and local laws; Data and algorithm ethics: transparency, fairness and absence of bias; Model explainability and auditing.
• Visualization, communication and business applications (10%): Designing effective visualizations; Dashboards and Business Intelligence tools; Data storytelling and analytical reports; Presenting to technical and business audiences; Alignment with strategic objectives and KPIs; Assessing the impact and return on investment (ROI) of Big Data; Managing data projects with agile methodologies.

Who is this certification for?

• Data engineers and architects: Who design, implement and operate large-scale Big Data platforms and solutions.
• Leaders and administrators: Technical leads, database administrators and analytics consultants driving data-based transformation in their organizations.
• Data analysts and scientists: Data scientists, analysts and Business Intelligence specialists seeking to certify their skills in advanced analytics and machine learning.

Prerequisites

Mandatory: Big Data Certified Associate (BDCA), valid at the time of registration. BDCE is the second level of the CertJoin Big Data path; the next level is Big Data Certified Specialist (BDCS).