Description
- Teradata overview and features
- MPP Architecture — Massively Parallel Processing distributes data and queries across nodes for linear scalability and high concurrency.
- Teradata Vantage — Unified analytics platform combining RDBMS, in-database analytics, and ecosystem connectors for hybrid cloud deployments.
- SQL Compatibility — Full ANSI SQL support plus Teradata-specific extensions for analytic functions and set-based processing.
- Data Distribution & Hashing — Primary index hashing ensures even data distribution and minimizes data movement during joins.
- Partitioned Primary Index — Improves query performance and maintenance for time-series and large tables.
- Advanced Indexing — Secondary, join, and aggregate join indexes reduce I/O and accelerate complex joins and aggregations.
- Compression & Storage Optimization — Multi-level compression and block-level storage strategies lower footprint and speed scans.
- Workload Management — Prioritizes queries, enforces SLAs, and isolates ETL, BI, and ad-hoc workloads for predictable performance.
- High Availability & RAS — Built-in redundancy, failover, and RAS features for enterprise uptime and serviceability.
- Data Loading Utilities — FastLoad, MultiLoad, FastExport, and BTEQ support high-throughput bulk loads and exports.
- In-Database Analytics — Native analytic functions, machine-learning libraries, and SQL-embedded analytics to reduce data movement.
- Integration & Ecosystem — Connectors for Hadoop, Spark, Kafka, and cloud object stores enable hybrid pipelines and streaming ingestion.
- Security & Governance — Role-based access, encryption, auditing, and data dictionary features for compliance and governance.
- Performance Tuning & Explain — EXPLAIN plans, statistics, and optimizer hints drive index, join, and partition strategies for complex workloads.
- Cloud and SaaS Options — Flexible deployment: on-prem, private cloud, public cloud, and Teradata-as-a-Service for cost and agility tradeoffs.
- Advanced Topics for Senior Engineers — Capacity planning, node balancing, custom UDFs, workload SLAs, cross-platform data fabric, and migration strategies for petabyte-scale systems.
