Coming Soon
Intermediate

Application Retirement & Modernization for AI

This course provides IT leaders with a strategic "Clean Start" framework to decommission expensive legacy systems while transforming trapped data into high-performance AI assets. You will master the technical process of archiving SAP, Oracle, and Mainframe environments into the Solix Common Data Platform, ensuring decades of historical data remain searchable and "AI-readable." By learning to quantify the ROI of retirement, you will gain the skills to eliminate massive maintenance costs and reinvest those savings into scalable enterprise AI innovation.

Instructor-Led
20 hours
5 modules
Recommended Course Audience

Recommended Course Audience

IT Directors Legacy System Managers Enterprise Architects.
Pre-Required Skills

Pre-Required Skills

  • Pre-Required Skills Ckeck
    This course is engineered specifically for IT leaders, enterprise architects, and database managers tasked with solving the high cost of legacy data maintenance while paving the way for AI adoption.
Course Highlights

Course Highlights

5 modules
Inventory & Discovery: Techniques for cataloging legacy applications across SAP, Oracle, IBM DB2, and Mainframe environments. Data Value Scoring: Assessing legacy data for Intelligence Value determining what is required for AI training, what is needed for compliance, and what can be purged. The High Cost of Maintenance: Analyzing the hidden costs of keeping legacy systems alive (hardware, specialized talent, security risks).
Decommissioning without Deleting: How to retire an application while keeping the data fully searchable and accessible for AI models. Metadata Preservation: Ensuring that when data moves from a 20-year-old database, it retains its context (relationships, timestamps, and schemas) so AI can understand it. The Medallion Approach to Legacy: Mapping legacy data into Bronze, Silver, and Gold layers within the Solix CDP.
Active Archiving: Strategies for moving large volumes of cold data to the cloud while maintaining seamless access for BI and AI tools. Hybrid Cloud Architectures: Managing data distribution between on-premise legacy systems and modern cloud environments (Azure, AWS, GCP). Intelligence Preservation: Using Apache Hudi and Parquet formats to ensure archived data remains AI-readable at scale.
The Legacy-to-AI Pivot: Building a business case that proves how retiring one legacy system can fund an entire RAG or LLM pilot program. Compliance & Legal Hold: Managing GDPR, CCPA, and data retention policies during the retirement process. E-Discovery in Archived Data: How to quickly retrieve specific historical records from the Solix archive for legal or audit requests without rebooting old software.
Connector Workshop: Configuring Solix connectors for common legacy databases. Building the Virtual Archive: Creating a user-friendly Virtual Interface so business users can still query the data from a retired app. Connecting the Archive to Solix GPT: A capstone project where students feed legacy archived data into a RAG framework to answer historical business questions.
Application Retirement & Modernization for AI
$699.00

This course is coming soon. Enrollment is not yet open.

For any support or technical enquiries, please reach out to info@solixacademy.com

Download Brochure
Level : Intermediate
Modules : 5
Duration : 20 hours