Exam Code: TDVCL2

Related Certification(s): Teradata VantageCloud Lake Consultant Certification

Certification Provider: Teradata

Number of TDVCL2 practice questions in our database: 51

Expected TDVCL2 Exam Topics, as outlined by Teradata:

Module 1: General Concepts (18%)
Candidates should understand relational concepts, characteristics of relational databases and dimensional models, use cases for deploying these models, and identify ClearScape Analytics™ capabilities in VantageCloud Lake.

Module 2: VantageCloud Lake Architecture & Components (36%)
Candidates should comprehend data flow from source to consumption, features and benefits of VantageCloud Lake’s logical components, definitions of objects within the platform, space and storage options, table definition components, and the purpose of workload management.

Module 3: Security and Privacy (11%)
Candidates should identify privacy and security mechanisms, features for managing user privileges, and functions and types of user authentication.

Module 4: Data Architectures (13%)
Candidates should grasp high-level concepts and major components of data lake architecture, understand use cases, data flow, reasons for deploying a data lake architecture, and identify reasons for using AI.

Module 5: Data Distribution and Access (11%)
Candidates should identify use cases of advanced indexes, the impact of the Primary Index on data distribution, differences between Primary Index and Primary Key, types, levels, and functionality of locking, the purpose and components of the access layer, and use cases of semi-structured data.

Module 6: Teradata Tools and Utilities (11%)
Candidates must identify common data integration techniques, features and functions to administer and monitor VantageCloud Lake, access methods for VantageCloud Lake, and features and functions to manage and monitor analytic workflows.

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Expected TDBL4-16.20 Exam Topics, as suggested by Teradata

Topic 1: Advanced Teradata Architecture and Internals
This topic dives deep into Teradata’s advanced architecture, covering hashing algorithms, AMP operations, BYNET efficiency, and system resource utilization. It also focuses on multi-temperature data management and workload distribution.

Topic 2: Performance Optimization and Indexing Strategies
Understanding key performance tuning techniques, including the role of primary and secondary indexes, join indexes, partitioned primary indexes (PPI), and system statistics collection. It also discusses query rewrites and optimizer strategies.

Topic 3: Workload Management and System Monitoring
Exploring Teradata’s workload management features, including Teradata Active System Management (TASM), QueryGrid, and priority scheduling. It also covers the use of Viewpoint and DBQL for real-time monitoring.

Topic 4: Data Security, User Management, and Access Control
Focusing on authentication methods, role-based security, encryption, user privileges, object-level security, and best practices for securing sensitive data within a Teradata environment.

Topic 5: Advanced SQL and Query Performance Tuning
Covering complex SQL optimizations, query parallelism, join strategies, temporary tables, and macros. It also explains handling skew issues and using Explain plans for troubleshooting.

Topic 6: Backup, Restore, and High Availability Strategies
Understanding Teradata’s disaster recovery mechanisms, including Dual Active solutions, Unity Director, fallback tables, and restoring data using ARC and BAR (Backup and Restore) utilities.

Topic 7: Data Integration and ETL Optimization
Exploring Teradata utilities such as FastLoad, MultiLoad, TPump, TPT (Teradata Parallel Transporter), and their role in large-scale data ingestion. It also discusses ETL best practices for managing workloads efficiently.

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Expected TDBL1-16.20 Exam Topics, as suggested by Teradata

Topic 1: Teradata Architecture and Components
This topic covers the fundamental architecture of Teradata, including its MPP (Massively Parallel Processing) framework, nodes, parsing engines, BYNET, and AMP components. It also discusses how data is distributed across the system.

Topic 2: Database Design and Indexing
Understanding the concepts of database design, primary and secondary indexes, hashing algorithms, partitioned primary indexes (PPI), and join indexes. The topic also covers best practices for efficient data retrieval and performance optimization.

Topic 3: SQL Essentials and Query Performance
This section explains SQL fundamentals within Teradata, including SELECT statements, joins, subqueries, aggregation functions, and stored procedures. It also discusses query optimization techniques to enhance performance.

Topic 4: Data Loading and ETL Processes
It focuses on various data-loading utilities such as FastLoad, MultiLoad, TPT (Teradata Parallel Transporter), and TPump. The topic also covers ETL best practices, error handling, and troubleshooting data integration issues.

Topic 5: Security and User Access Management
This topic addresses Teradata security measures, including authentication methods, access control mechanisms, user role management, and encryption for data protection.

Topic 6: Performance Tuning and Workload Management
The section discusses performance tuning techniques, including statistics collection, query rewrites, workload management strategies, and the use of Teradata Workload Analyzer (TWA).

Topic 7: Backup, Restore, and Disaster Recovery
It covers different Teradata backup and recovery strategies, ARC utility, disaster recovery planning, and high availability solutions.

Topic 8: Integration with Business Intelligence (BI) Tools
This topic explains how Teradata integrates with BI tools such as Tableau, Power BI, and SAS for analytics and reporting. It also covers ODBC/JDBC connectivity and data visualization strategies.

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