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Hitachi HQT-2900 real answers - Hitachi Vantara Qualified Professional - Pre-sales Data Analytics Foundation

HQT-2900
  • Exam Code: HQT-2900
  • Exam Name: Hitachi Vantara Qualified Professional - Pre-sales Data Analytics Foundation
  • Updated: Oct 12, 2026
  • Q & A: 0 Questions and Answers

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Hitachi HQT-2900 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Integration (PDI)- Transformation Techniques
  • 1. Joins and merge operations
    • 2. Data standardization and scripting
      - ETL Concepts
      • 1. Incremental load and CDC
        • 2. Extract, Transform, Load fundamentals
          Topic 2: Pentaho Business Analytics- Reporting and dashboards
          • 1. Pixel-perfect reporting
            • 2. Embedded analytics
              - Self-service analytics
              • 1. Interactive visualization (Analyzer)
                • 2. Drill-down and exploration
                  Topic 3: Data Analytics Foundations- Enterprise Data Challenges
                  • 1. Data silos and AI readiness
                    • 2. Data governance fundamentals
                      - Data Quality Concepts
                      • 1. Data profiling and cleansing concepts
                        • 2. Impact of data quality on analytics and AI
                          Topic 4: Pentaho+ Platform Overview- Core platform capabilities
                          • 1. Catalog and metadata management (PDC)
                            • 2. Data quality management (PDQ)
                              • 3. Data optimization and tiering (PDO)
                                • 4. Data ingestion and integration (PDI)
                                  Topic 5: Data Optimization (PDO)- Storage optimization
                                  • 1. Data tiering to lower-cost storage
                                    • 2. Cold data identification
                                      Topic 6: Data Catalog and Governance- Metadata management
                                      • 1. Data dictionary generation
                                        • 2. Automated data discovery
                                          - Lineage and compliance
                                          • 1. Impact analysis for changes
                                            • 2. Data lineage visualization

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