Description
Introduction
Teradata Customer Experience, Applications & Enterprise Solutions training focuses on using Teradata technologies to support customer analytics, enterprise applications, business intelligence, and data-driven decision-making. Participants learn how to integrate customer data, develop analytical solutions, manage enterprise workloads, and support business applications using Teradata Vantage and related capabilities.
Prerequisites
- Basic understanding of relational database concepts.
- Familiarity with SQL and database queries.
- Basic knowledge of data warehousing and data integration.
- Understanding of business applications and enterprise data.
- Familiarity with customer relationship management (CRM) concepts is beneficial.
- Basic knowledge of analytics and reporting concepts.
Estimated Duration
- Beginner Level: 30–35 hours
- Intermediate Level: 40–45 hours
- Advanced Level: 50–60 hours
- Enterprise Level: 65–75 hours
Training Lab Setup Specifications
- Teradata Vantage environment or an accessible Teradata training instance.
- Teradata Studio or compatible SQL development environment.
- Teradata database credentials with appropriate access privileges.
- Sample customer, sales, transaction, and enterprise application datasets.
- SQL editor and query execution environment.
- Python environment for application and analytics integration exercises.
- Business intelligence and reporting tools for visualization exercises.
- Stable internet connectivity for cloud-based Teradata environments.
- Access to relevant Teradata documentation and learning resources.
TABLE OF CONTENTS
Module 1: Introduction to Teradata Customer Experience & Enterprise Solutions
1.1 Understanding Teradata Customer Experience Solutions
1.1.1 Overview of Teradata Vantage and enterprise data capabilities
1.1.2 Role of customer data in enterprise decision-making
1.1.3 Customer experience analytics and business objectives
1.1.4 Enterprise applications and data-driven operations
1.2 Teradata Architecture for Customer and Enterprise Workloads
1.2.1 Teradata database architecture and core components
1.2.2 Massively Parallel Processing (MPP) architecture
1.2.3 Enterprise data storage and processing
1.2.4 Workload management for business applications
1.3 Teradata Enterprise Solution Ecosystem
1.3.1 Overview of Teradata Vantage capabilities
1.3.2 Enterprise application integration architecture
1.3.3 Customer analytics and operational data environments
1.3.4 Teradata deployment and consumption models
Module 2: Customer Data Management & Customer 360
2.1 Customer Data Architecture
2.1.1 Customer data sources and acquisition
2.1.2 Customer profiles and data attributes
2.1.3 Customer identity and relationship management
2.1.4 Customer data integration and consolidation
2.2 Customer 360 Data Management
2.2.1 Building unified customer profiles
2.2.2 Customer segmentation and classification
2.2.3 Customer interaction and transaction histories
2.2.4 Managing customer data across enterprise systems
2.3 Customer Data Quality and Governance
2.3.1 Customer data validation and standardization
2.3.2 Duplicate detection and data cleansing
2.3.3 Customer data consistency and integrity
2.3.4 Data governance and privacy considerations
Module 3: Teradata Customer Experience Analytics
3.1 Customer Behavior and Interaction Analytics
3.1.1 Understanding customer behavior patterns
3.1.2 Customer journey and interaction analysis
3.1.3 Customer purchase and transaction analytics
3.1.4 Identifying customer preferences and trends
3.2 Customer Segmentation and Profiling
3.2.1 Developing customer segmentation models
3.2.2 Demographic and behavioral segmentation
3.2.3 Customer value and profitability analysis
3.2.4 Target audience identification
3.3 Customer Experience Measurement
3.3.1 Customer satisfaction and engagement analysis
3.3.2 Customer retention and churn analysis
3.3.3 Customer lifetime value measurement
3.3.4 Customer experience performance indicators
Module 4: Teradata SQL & Enterprise Application Development
4.1 SQL Development for Enterprise Applications
4.1.1 SQL query development and execution
4.1.2 Joins, subqueries, and common table expressions
4.1.3 Analytical functions and advanced SQL operations
4.1.4 Stored procedures and database programming
4.2 Application Data Access and Processing
4.2.1 Accessing Teradata data from enterprise applications
4.2.2 JDBC and ODBC connectivity
4.2.3 Application queries and transaction processing
4.2.4 Data retrieval and application-level processing
4.3 Enterprise Application Database Design
4.3.1 Designing application-oriented data structures
4.3.2 Managing relational tables and database objects
4.3.3 Implementing application data workflows
4.3.4 Supporting concurrent application operations
Module 5: Teradata Integration with Enterprise Applications
5.1 Enterprise Application Integration Architecture
5.1.1 Enterprise integration patterns and architecture
5.1.2 Connecting Teradata with business applications
5.1.3 Application interfaces and data exchange
5.1.4 Integration architecture and implementation planning
5.2 API and Application Connectivity
5.2.1 Understanding API-based data integration
5.2.2 Connecting applications through supported interfaces
5.2.3 Managing application authentication and access
5.2.4 Handling application data requests and responses
5.3 Enterprise System Integration
5.3.1 CRM and customer management system integration
5.3.2 ERP and enterprise application integration
5.3.3 Marketing and customer engagement platform integration
5.3.4 Integrating external data sources and services
Module 6: Business Intelligence, Reporting & Customer Insights
6.1 Enterprise Business Intelligence Architecture
6.1.1 Overview of business intelligence solutions
6.1.2 Connecting Teradata with BI platforms
6.1.3 Preparing analytical datasets for reporting
6.1.4 Enterprise reporting architecture
6.2 Customer Analytics Dashboards
6.2.1 Designing customer performance dashboards
6.2.2 Visualizing customer segmentation results
6.2.3 Developing sales and transaction reports
6.3 Advanced Reporting and Business Insights
6.3.1 Creating analytical reports using SQL
6.3.2 Developing operational and management reports
6.3.3 Trend analysis and performance comparisons
6.3.4 Delivering actionable business insights
Module 7: Teradata Marketing & Customer Engagement Applications
7.1 Customer Marketing Analytics
7.1.1 Customer campaign data management
7.1.2 Marketing audience segmentation
7.1.3 Campaign performance measurement
7.2 Personalized Customer Engagement
7.2.1 Customer preference and interest analysis
7.2.2 Personalized offer and recommendation data
7.2.3 Cross-selling and upselling analytics
7.3 Omnichannel Customer Experience
7.3.1 Integrating digital and physical customer interactions
7.3.2 Web, mobile, and contact center data analysis
7.3.3 Cross-channel customer journey analysis
7.3.4 Measuring omnichannel engagement performance
Module 8: Advanced Analytics & AI for Customer Solutions
8.1 Advanced Customer Analytics
8.1.1 Predictive customer behavior analysis
8.1.2 Customer churn prediction
8.1.3 Customer lifetime value modeling
8.1.4 Forecasting customer demand and trends
8.2 Artificial Intelligence and Machine Learning
8.2.1 Introduction to AI and machine learning capabilities in Teradata
8.2.2 Preparing customer datasets for machine learning
8.2.3 Developing analytical models using supported tools
8.2.4 Model scoring and analytical result integration
8.3 AI-Driven Enterprise Applications
8.3.1 Applying AI to customer engagement use cases
8.3.2 Intelligent customer segmentation
8.3.3 Recommendation and decision-support applications
Module 9: Enterprise Data Warehousing & Application Workloads
9.1 Enterprise Data Warehouse Architecture
9.1.1 Designing enterprise data warehouse environments
9.1.2 Customer and operational data warehouse models
9.1.3 Fact tables, dimension tables, and data relationships
9.2 Data Processing and Workload Management
9.2.1 Managing concurrent application workloads
9.2.2 Workload prioritization and resource allocation
9.2.3 Query execution and workload monitoring
9.3 Data Integration and Pipeline Management
9.3.1 Enterprise data ingestion strategies
9.3.2 ETL and ELT processing concepts
9.3.3 Batch and near-real-time data integration
9.3.4 Data pipeline monitoring and error handling
Module 10: Enterprise Security, Privacy & Compliance
10.1 Teradata Security Architecture
10.1.1 User and role management
10.1.2 Authentication and authorization
10.1.3 Database privileges and access controls
10.1.4 Securing enterprise application connections
10.2 Customer Data Privacy and Protection
10.2.1 Protecting personally identifiable information
10.2.2 Data masking and sensitive data handling
10.2.3 Customer consent and data access management
10.2.4 Data retention and privacy requirements
10.3 Enterprise Governance and Compliance
10.3.1 Enterprise data governance frameworks
10.3.2 Data lineage and audit management
10.3.3 Regulatory and industry compliance considerations
10.3.4 Monitoring security and compliance activities
Module 11: Cloud Deployment, Integration & Enterprise Operations
11.1 Teradata Cloud Solutions
11.1.1 Overview of Teradata VantageCloud
11.1.2 Cloud deployment and service architecture
11.1.3 Connecting enterprise applications to cloud environments
11.1.4 Cloud data access and workload operations
11.2 Hybrid and Multi-Environment Integration
11.2.1 Integrating on-premises and cloud data platforms
11.2.2 Hybrid application connectivity
11.2.3 Data synchronization across environments
11.3 Enterprise Operations and Monitoring
11.3.1 Monitoring database and application performance
11.3.2 Managing system availability and resource utilization
11.3.3 Backup, recovery, and operational continuity
Module 12: Practical Enterprise Projects & Capstone Implementation
12.1 Customer 360 Implementation Project
12.1.1 Customer data integration and consolidation
12.1.2 Developing unified customer profiles
12.1.3 Building customer segmentation datasets
12.2 Customer Analytics and Application Project
12.2.1 Developing customer analytics SQL queries
12.2.2 Building customer engagement reports
12.2.3 Integrating analytical results with applications
12.3 Enterprise Solution Capstone
12.3.1 Designing an end-to-end Teradata enterprise solution
12.3.2 Implementing data integration workflows
12.3.3 Applying analytics to enterprise business scenarios
Conclusion
The Teradata Customer Experience, Applications & Enterprise Solutions training equips participants with practical knowledge of customer data management, customer analytics, enterprise application integration, business intelligence, AI-driven insights, and cloud-based data operations. Participants gain the skills to design and support Teradata solutions that improve customer engagement, strengthen enterprise applications, and enable data-driven business decisions.
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