Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Greenplum Architecture
- Parallel processing and symmetric multi-processing
- Segment roles and cluster configuration
- Scalability and data movement
- Greenplum Data Warehouse architecture
Greenplum Table Structures
- Distributed vs. randomly assigned tables
- Heap vs. append-only tables
- Row vs. columnar storage formats
- Partitioned and clustered tables
Data Distribution and Hashing
- Hashing logic and distribution keys
- Skew handling and performance impact
- Hash maps and row placement strategies
Indexes and Performance Optimization
- Clustered and non-clustered indexes
- B-tree and bitmap index use cases
- Index scan and storage behavior
Physical Database Design
- Normalization and logical model design
- User access strategies and distribution analysis
- Data demographics and indexing decisions
Denormalization Techniques
- Derived data, summary tables, and pre-joins
- Columnar tables as vertical partitioning
- Data marts and materialized views
Advanced SQL and Query Execution
- Join strategies and redistribution
- OLAP and window functions
- Temporary tables, subqueries, and derived tables
EXPLAIN Plans and Query Tuning
- Reading and interpreting EXPLAIN output
- Cost analysis and plan optimization
- Join movement and segment-local operations
Greenplum Utilities and Best Practices
- ANALYZE and VACUUM
- Data loading and movement with Nexus
- Security, permissions, and performance tips
Summary and Next Steps
Requirements
- An understanding of relational databases and SQL
- Experience with data warehousing or analytical systems
- Familiarity with Linux command line operations
Audience
- Data architects and engineers
- Database administrators and technical leads
- BI developers and analytics specialists working with Greenplum
21 Hours
Testimonials (5)
**Exercises and Problem Solving**- Understanding the Basics of Problem-Solving - Identifying the problem - Breaking down the problem - Formulating a plan- Practical Exercises - Exercise 1: Basic Algorithms - Exercise 2: Data Structures - Exercise 3: Debugging Techniques- Advanced Problem-Solving - Recursive Problems - Dynamic Programming - Graph Algorithms- Real-World Applications - Case Studies - Industry-Specific Problems - Collaborative Problem-Solving
Mario Humberto Serrano Gutierrez - Hipodromo de Agua Caliente
Course - Greenplum Architecture and Data Modeling
Machine Translated
It was most interesting.
Luis Antonio Jimenez Gil - Hipodromo de Agua Caliente
Course - Greenplum Architecture and Data Modeling
Machine Translated
The practical exercises and the willingness to answer questions
Edith Vichua Solis - Hipodromo de Agua Caliente
Course - Greenplum Architecture and Data Modeling
Machine Translated
I explained it, but I think I used terms that were too complex for everyone to understand.
Moises Jafet Hernandez Fuentes - Hipodromo de Agua Caliente
Course - Greenplum Architecture and Data Modeling
Machine Translated
the practices
