Accelerate IFS Data Migration with a 60% Time Reduction—Minimize Costs, Ensure data quality
A fully automated data migration tool designed for businesses implementing or upgrading IFS solutions. It ensures seamless validation, cleansing, and transformation of legacy data, eliminating manual errors and delays. With KAIMIG, organizations can achieve guaranteed 100% migration success, reducing project timelines and enhancing efficiency
Say goodbye to spreadsheet chaos
Relying on spreadsheets to manage your migration process is risky and chaotic, especially for complex and time-consuming project like IFS Implementation and upgrade. By eliminating spreadsheet dependency throughout the migration process with the smart features below we automate and expedite the migration process, reduce errors, and ensure data integrity.
- Smart Data Cleansing - Offers multiple cleansing options. It uses AI to highlight duplicates in loaded data, making it easier for users to modify or remove them. Updates can be performed in batches. Additionally, it is capable of checking scope and generate keys.
- Enhanced Data Loader - Load data directly to IFS staging tables without relying on spreadsheet allowing data is reusable at each stage. It levers existing IFS Migration jobs to create new jobs using API, aligning seamlessly with IFS business logic. It also allows earlier data loading and supports delta extractions during cut-offs and post go lives.
- Legacy Data Extractor - Extract data directly from legacy systems based on defined criteria.
Clear away the uncertainties in the implementation
Accurately estimating the time, costs and resource needs for implementation project is not easy. KAIMig automates the migration process with significant productivity enhancements allowing to take control of cost/time budgets and quality in the implementation project. It facilitates a collaborative approach eliminating communication burden and keeping everyone on the same page with the updated info. It improves predictability of the migration task with.
- Automatic data mapping - Intelligently suggests mapping for most of the legacy columns and target columns and the user has the options to modify unmatched columns manually.
- Approval Process - Ensure clean and validated data is approved by right persons before loading into target systems
- Re-usable data and configurations - Reuse configurations and rules across multiple phases (dev, test, UAT, prod) by exporting them. It also allows to reuse data seamlessly accross multiple environments (e.g. dev, test, UAT, prod)
- Legacy Data Archiving - Efficiently archive historical data for future reference and compliance.
Ensure data integrity in loaded data
Making sure quality of the migrated data is a time consuming and cumbersome task regardless you are migrating from older IFS systems or other legacy systems. Finding it out later in the migrated system make it even worse. Apart from the Smart Data Cleansing capabilities, KAIMIG offers multiple features that validates what is being moved and re-use data and practices across multiple phases of the implementation project.
- Pre-validation before data loading - Ensures no errors in data formats, verifies all required references and basic data exists in IFS. Provides detailed validation reports for accuracy.
- History Tracking and status reporting - Include progress tracking tools within the system and logs errors and validation for troubleshooting. It also generates reconciliation reports for data accuracy.
- Global & Local Level Transformation - Applies standardized and localized values (e.g. UOM, Payment Terms, Tax Codes)