IBM InfoSphere MDM Training
IBM InfoSphere Master Data Management (MDM) is a solution designed to help organizations manage and maintain a single, consistent view of their critical business data across the enterprise. It ensures that data is accurate, consistent, and reliable, supporting processes like customer relationship management, analytics, and regulatory compliance.
Why should you choose Nisa For IBM InfoSphere MDM Training?
Nisa Trainings is the best online training platform for conducting one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and happy to clarify your doubts anytime. Our teaching style at Nisa Trainings is entirely hands-on. You’ll have access to our desktop screen and will be actively conducting hands-on labs on your desktop.
Job Assistance
If you face any problem while working on IBM InfoSphere MDM Course, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.
The Process we follow for our Online Job Support Service:
- We receive your inquiry for Online Job
- We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re
- If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, we will only agree to provide service. And then you have to make the payment to get the service from
- We will fix the timing for Online Job Support as mutually agreed by you and our consultant.
Course Information
IBM InfoSphere MDM Training
Duration: 25 Hours
Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)
Training Method: Instructor Led Online One-on-One Live Interactive
Sessions.
COURSE CONTENT :
1. Introduction to IBM InfoSphere MDM
- Overview of Master Data Management (MDM)
- Importance of MDM for data consistency, accuracy, and governance.
- MDM in the context of business data integration and analytics.
- Key Concepts in MDM
- What constitutes “master data.”
- Types of master data: Customer, Product, Supplier, etc.
- Single customer view and 360-degree views in MDM.
- Architecture of IBM InfoSphere MDM
- High-level architecture and components.
- IBM InfoSphere MDM deployment options: On-premise, Cloud, Hybrid.
- IBM InfoSphere MDM Suite Overview
- IBM InfoSphere MDM Server, MDM Workbench, and related tools.
- Comparison of IBM InfoSphere MDM with other MDM solutions.
2. Installing and Configuring IBM InfoSphere MDM
- System Requirements and Prerequisites
- Hardware and software requirements for installation.
- Configuration of database and application servers.
- Installation of InfoSphere MDM
- Step-by-step guide for installing InfoSphere MDM components.
- Configuring web services and server settings.
- Setting Up the Environment
- Configuration of InfoSphere MDM for development, testing, and production environments.
- Configuring roles, users, and access permissions.
3. MDM Data Modeling and Data Governance
- Data Modeling in InfoSphere MDM
- Designing and creating master data models.
- Understanding and implementing entity types (e.g., Customer, Product).
- Managing relationships and hierarchies in master data.
- Data Governance Framework
- Principles of data governance in IBM InfoSphere MDM.
- Setting up policies for data quality, stewardship, and monitoring.
- Data Quality Rules
- Implementing data quality rules for data validation.
- Working with data validation mechanisms in InfoSphere MDM.
- Standardization, de-duplication, and data enrichment.
4. Managing Master Data
- Creating and Managing Master Data Records
- Creating, updating, and deleting master data records.
- Merging and unmerging records for data consistency.
- Managing data conflicts and resolutions.
- Master Data Lifecycle
- Lifecycle management of master data (creation, update, deactivation).
- Versioning and history tracking of master data.
- Data Stewardship and Workflow Management
- Implementing workflows for data stewardship.
- Monitoring and managing the data governance process.
- Automated approval processes for master data records.
5. Integration with Other Systems
- Data Integration Concepts
- Integration of InfoSphere MDM with external systems (ERP, CRM, etc.).
- Introduction to ETL (Extract, Transform, Load) processes.
- InfoSphere MDM and IBM DataStage
- Configuring DataStage to integrate master data into MDM.
- Implementing data flows for MDM integration.
- Web Services and APIs
- Creating and consuming web services in InfoSphere MDM.
- Using RESTful and SOAP APIs to integrate with other applications.
6. Security, Privacy, and Compliance
- Security Best Practices in InfoSphere MDM
- User roles, permissions, and access controls.
- Configuring multi-layered security for sensitive master data.
- Data Privacy
- Techniques for protecting sensitive data in MDM systems.
- Encryption, anonymization, and pseudonymization techniques.
- Compliance Management
- Ensuring MDM compliance with data protection regulations (GDPR, HIPAA).
- Implementing audit trails and data lineage.
7. Performance Optimization and Troubleshooting
- Performance Tuning
- Optimizing InfoSphere MDM for handling large datasets.
- Tuning database queries, indexing, and memory usage.
- Monitoring and Troubleshooting
- Configuring monitoring tools to track system health.
- Troubleshooting common issues with data synchronization, conflict resolution, and service interruptions.
- Backup and Recovery
- Implementing backup strategies for master data.
- Data recovery and disaster recovery planning.
8. Advanced Topics in IBM InfoSphere MDM
- Advanced Data Quality Management
- Advanced techniques for data cleansing, de-duplication, and data enrichment.
- Customizing data quality rules and metrics.
- Advanced MDM Customization
- Customizing InfoSphere MDM interfaces and workflows.
- Extending InfoSphere MDM to meet specific business needs.
- Data Integration with Big Data Platforms
- Integration with Hadoop and other big data environments.
- Managing big data through InfoSphere MDM.
- IBM Watson Integration for Analytics
- Using IBM Watson’s AI capabilities for advanced analytics and insights.
- Implementing predictive analytics on master data.