DESCRIPTION:

Participants gain a clear understanding of data domains, data flows, and configuration principles through guided hands on exercises. The training emphasize practical competence, enabling learners to construct data import and export processes, and support operational workflows that deliver accurate and reliable data sets.

FOCUS AREAS / MODULES

• Data Import

This module introduces data import in SimCorp Dimension using the Filter Toolbox: covering data mapping between files and target applications, data transformation with translations and formulas, message-based processing with queues and validation of import configurations. 

• Data Export

This module covers data export using the Data Extractor, focusing  on building extractions on SimCorp Dimension’s data model,  directing output to various destinations, and generate export files;  starting from understanding the data model with usage of the  technical documentation. The module also covers how reporting  data is delivered via the Data Warehouse Manager.

• System Maintenance

This module focuses on automation and user administration. Learners will configure batch jobs to prepare business tasks for automated workflows; manage services through automation models on the Service Platform; define users and their authorization settings to control access across the platform.

TARGET AUDIENCE:

This focus stream is ideal for:

• Data analysts and data management specialists
• Reporting and business intelligence professionals
• Technical consultants and system specialists
• IT and system support roles
• Anyone working with data flows, integration, or reporting in SimCorp One 

PREQUISITES:  

Completion of the SimCorp One Academy Foundation Training is required.

DATA MANAGEMENT TRAINING DETAILS:

Dates: 19 - 23 October, 2026

Format: Virtual / Blended

Time:  Group A: 8:00–11:00 AM CET // 3:00 – 6:00 PM SGT 
Group B: 3:00 - 6:00 PM CET // 9:00AM - 12:00 PM EST

Language: English

Data Management Training fee per participant: 2500 EUR / 2915 USD / 3715 SGD