ChainSys Mass Data Loading for Siemens Teamcenter PLM
Chainsys
ChainSys Mass Data Loading for Siemens Teamcenter PLM
Chainsys
ChainSys Mass Data Loading for Siemens Teamcenter PLM
Chainsys
Mass load data from Excel or CSV into Siemens Teamcenter PLM.
Solution Description
ChainSys Mass Data Loading automates expensive, time-consuming, and error prone manual data entry for Siemens Teamcenter PLM with its fast, accurate, secure browser-based utility to perform mass data loads from CSV or Excel files to your system. Each mass data load complies with system import routines, system security, and custom business rules. Pre-validate each load, fix data errors, and keep a detailed audit trail.
Key Features and Highlights
Mass Load Additions or Changes to Master Data, such as Items, BOMs, Manufacturers, etc.
Mass Load Additions or Changes to Reference Data, such as Lookup Values, Manufacturer Part Numbers, etc.
Mass Load Additions or Changes to Orders, such as Change Orders, Change Requests, etc.
Mass Load Additions to Attachments, such as Item Attachments, Manufacturer Attachments, etc.
Require User Authentication and Stamp Inserts and Updates with System Username, Date and Time
Pre-Validate against System Constraints and Configurable Business Rules, and Resolve Errors for Each Load before Committing
Provide Row and Column-Level Audit Trail of Each Load, Insert / Update Performed by a User
Support Ad Hoc CSV and Excel Data Loads, or Automate Bulk Data Loads from a File System through a Scheduler
Why ChainSys
Time for repetitive data entry tasks is reduced.
User errors for repetitive data entry tasks are reduced through pre-validation.
System security is enforced.
Centralized load monitoring and row and column-level audit trails are supported.
ChainSys Approach
Upon signing into the ChainSys Mass Data Loading tool, users can connect to file shares where CSV or Excel files are stored. Users then create a Loader and map the CSV or Excel files to the Loader through a drag-and-drop interface. In addition to the target system constraints, users can configure business rules to validate or transform data prior to loading to the target.
During execution, each loader will perform pre-validation against business rules configured in advance. Any validation failures can be fixed and re-submitted to the pre-validation engine. After pre-validation and data fixes are complete, the loader will execute the load against the target system. Successes and failures returned by the target system are also logged.