C1000-190
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C1000 190 Watsonx Data Lakehouse
IBM Certified watsonx Data Lakehouse Engineer v1 - Associate (C1000-190) teaches the architecture, core components, query optimization, ingestion pipelines, storage management, and governance of watsonx.data lakehouses, enabling professionals to design and operate efficient data platforms.
90
Minutes
62
Questions
60/100
Passing Score
$200
Exam Cost
Who Should Take This
Data engineers, data architects, and analytics specialists with at least two years of experience in cloud data platforms should pursue this certification. They seek to validate their ability to implement and optimize watsonx.data lakehouse solutions, ensure proper governance, and accelerate data-driven initiatives within their organizations.
What's Covered
1
Domain 1: watsonx.data Lakehouse Architecture and Core Components
2
Domain 2: Query Engines and Performance Optimization
3
Domain 3: Data Ingestion and ETL/ELT Pipelines
4
Domain 4: Storage Management and Object Storage
5
Domain 5: Data Governance and Access Control
6
Domain 6: Monitoring, Troubleshooting, and Best Practices
What's Included in AccelaStudy® AI
Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
20 Activity Formats
Course Outline
78 learning goals
1
Domain 1: watsonx.data Lakehouse Architecture and Core Components
3 topics
Lakehouse Architecture Fundamentals
- Identify the key architectural components of watsonx.data lakehouse including compute engines, storage, and metadata layers
- Explain how watsonx.data combines data lake flexibility with data warehouse performance characteristics
- Compare lakehouse architecture benefits over traditional data lake and data warehouse approaches
- Describe the separation of compute and storage in watsonx.data architecture
- Analyze how watsonx.data supports multi-engine query federation across different data sources
Data Formats and Storage Technologies
- Identify Apache Parquet columnar storage format characteristics and benefits for analytical workloads
- Explain Apache Iceberg table format features including schema evolution and time travel capabilities
- Apply Parquet file optimization techniques including compression algorithms and column pruning
- Compare Iceberg table format advantages over traditional Hive-style partitioning for large datasets
- Analyze the impact of file size and partitioning strategies on query performance in lakehouse environments
Metadata Management and Catalogs
- Identify the role of Hive Metastore in watsonx.data for metadata management and table definitions
- Explain how watsonx.data integrates with external catalogs including Apache Hive and custom metadata stores
- Apply metadata catalog configuration for multi-engine access to shared table definitions
- Analyze metadata synchronization challenges when using multiple query engines with shared catalogs
2
Domain 2: Query Engines and Performance Optimization
3 topics
Presto Query Engine
- Identify Presto distributed SQL query engine architecture components including coordinators and workers
- Configure Presto connectors for accessing various data sources in watsonx.data environments
- Apply Presto query optimization techniques including predicate pushdown and projection pruning
- Analyze Presto query execution plans to identify performance bottlenecks and optimization opportunities
- Evaluate Presto memory management and resource allocation strategies for concurrent query workloads
Apache Spark Integration
- Identify Spark engine capabilities for batch processing and ETL operations in watsonx.data
- Configure Spark sessions with appropriate drivers and executors for lakehouse data processing
- Apply Spark DataFrame operations for data transformation and aggregation tasks
- Analyze Spark job execution metrics to optimize partition sizes and parallelism levels
- Compare Spark and Presto engine selection criteria based on workload characteristics and performance requirements
Query Federation and Cross-Engine Operations
- Explain federated query capabilities across multiple data sources and engines in watsonx.data
- Apply cross-catalog queries to access data from different storage systems and databases
- Analyze query federation performance considerations including data movement and join optimization
- Evaluate trade-offs between federated queries versus data consolidation strategies within the IBM cloud platform environment.
3
Domain 3: Data Ingestion and ETL/ELT Pipelines
3 topics
Data Ingestion Strategies
- Identify various data ingestion patterns including batch, streaming, and micro-batch approaches
- Configure data ingestion workflows using watsonx.data native tools and external integration methods
- Apply data validation and quality checks during ingestion processes to ensure data integrity
- Analyze ingestion performance bottlenecks and implement optimization strategies for large-scale data loads
- Evaluate ingestion frequency and latency requirements to select appropriate ingestion strategies
ETL and ELT Pipeline Development
- Identify differences between ETL and ELT approaches in lakehouse architectures
- Design data transformation pipelines using Spark SQL and DataFrame operations
- Implement incremental data processing patterns using Iceberg table capabilities within the IBM cloud platform environment.
- Apply error handling and data lineage tracking in ETL pipeline implementations
- Analyze pipeline performance metrics and optimize transformation logic for scalability
Data Transformation and Processing
- Apply common data transformation operations including cleansing, normalization, and aggregation
- Implement complex data joins and window functions for analytical data preparation
- Configure data type conversions and schema mapping for heterogeneous data sources
- Analyze data transformation performance and memory utilization patterns within the IBM cloud platform environment.
- Evaluate transformation logic efficiency and recommend optimization strategies within the IBM cloud platform environment.
4
Domain 4: Storage Management and Object Storage
2 topics
Object Storage Integration
- Identify supported object storage systems including IBM Cloud Object Storage and S3-compatible storage
- Configure object storage connections and authentication mechanisms in watsonx.data within the IBM cloud platform environment.
- Apply object storage bucket organization strategies for optimal data access patterns
- Analyze object storage performance characteristics and access pattern optimization within the IBM cloud platform environment.
- Evaluate object storage cost implications and implement cost optimization strategies
Data Lifecycle and Tiering
- Explain data lifecycle management concepts including hot, warm, and cold storage tiers
- Configure automated data tiering policies based on access frequency and retention requirements
- Apply data archival strategies for long-term retention and compliance requirements
- Analyze storage utilization patterns to optimize tiering policies and reduce costs
- Evaluate data retention policies and implement automated cleanup procedures within the IBM cloud platform environment.
5
Domain 5: Data Governance and Access Control
3 topics
Security and Access Management
- Identify authentication and authorization mechanisms available in watsonx.data within the IBM cloud platform environment.
- Configure role-based access control (RBAC) for users and groups accessing lakehouse data
- Apply row-level and column-level security policies for sensitive data protection
- Implement data masking and encryption strategies for data privacy compliance
- Analyze access patterns and audit logs to identify potential security vulnerabilities
Data Cataloging and Discovery
- Explain data catalog functionality for metadata management and data discovery
- Configure automated data profiling and metadata extraction from various data sources
- Apply data classification and tagging strategies for improved data organization
- Analyze data usage patterns and recommend data catalog improvements within the IBM cloud platform environment.
- Evaluate search and discovery capabilities to enhance data findability for business users
Data Lineage and Compliance
- Identify data lineage tracking capabilities for understanding data flow and transformations
- Configure data lineage collection from ETL pipelines and query operations
- Apply compliance reporting and audit trail generation for regulatory requirements
- Analyze data lineage graphs to identify data quality issues and impact analysis
- Evaluate governance policies and implement automated compliance monitoring within the IBM cloud platform environment.
6
Domain 6: Monitoring, Troubleshooting, and Best Practices
2 topics
Performance Monitoring and Optimization
- Identify key performance metrics for watsonx.data including query execution time and resource utilization
- Configure monitoring dashboards and alerting for lakehouse system health and performance
- Apply performance tuning techniques for query optimization and resource allocation
- Analyze system bottlenecks and implement capacity planning strategies within the IBM cloud platform environment.
- Evaluate workload patterns and recommend infrastructure scaling approaches within the IBM cloud platform environment.
Troubleshooting and Problem Resolution
- Identify common issues in lakehouse environments including query failures and data inconsistencies
- Apply systematic troubleshooting methodologies for diagnosing performance and connectivity problems
- Analyze log files and error messages to identify root causes of system issues
- Evaluate error patterns and implement preventive measures for common failure scenarios
- Assess system recovery procedures and implement disaster recovery best practices
Scope
Included Topics
- All domains of C1000-190 IBM Certified watsonx Data Lakehouse Engineer v1 - Associate: watsonx.data: lakehouse architecture, data formats (Parquet, Iceberg), metadata catalogs; query engines (Presto, Spark), query optimization, federation; data ingestion, transformation, ETL/ELT pipelin.
- Exam-specific technical content covering es; storage management with Object Storage, lifecycle, tiering; data governance, access control, cataloging, lineage..
Not Covered
- Topics outside the C1000-190 exam scope and other certification levels.
- Current pricing, promotional offers, and vendor-specific values that change over time.
- Implementation details for competing vendor products and platforms.
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