Automated preprocessing, transformation, and forwarding of field data (survey data, drilling logs, sampling)

Purpose

  1.1. Automate preprocessing, transformation, and forwarding of field data (survey data, drilling logs, sampling) to reduce manual handling, increase data accuracy, synchronize records, and ensure rapid availability for analysis, compliance, and reporting.
  1.2. Automatedly convert raw field data imports into normalized, structured formats that match engineering requirements.
  1.3. Automating validation, error-checking, and enrichment of input streams for automated processing.
  1.4. Automator-driven routing to knowledge management, GIS, BIM, or analytical systems based on pre-configured rules.
  1.5. Support automating standardized archiving and version control by automated tagging and metadata insertion.

Trigger Conditions

  2.1. New data entry from mobile forms or survey devices.
  2.2. Upload or arrival of new drilling logs or sampling files via email, FTP, or API.
  2.3. Scheduled batch data drops from connected tools.
  2.4. Detection of specific field event codes, automatedly launching downstream workflows.
  2.5. Automated API notifications from in-field IoT sensors.

Platform Variants

  3.1. Microsoft Power Automate
    • Feature/Setting: Configure “When a file is created” trigger in SharePoint to automate preprocess and automated data transfer to Excel or Power BI.

  3.2. Zapier
    • Feature/Setting: Use Webhooks or “New Spreadsheet Row” to automate ingest, transformation, and automatedly forward to data destinations.

  3.3. Make (Integromat)
    • Feature/Setting: Build scenarios automating JSON/CSV transform and automated uploads to GIS/ERP endpoints.

  3.4. AWS Lambda
    • Feature/Setting: Use event triggers on S3 bucket uploads to automate code-run for preprocessing and automated push to AWS Athena or DynamoDB.

  3.5. Google Cloud Functions
    • Feature/Setting: Automate preprocessing scripts triggered by new files in Google Cloud Storage and automate output to BigQuery.

  3.6. Apache NiFi
    • Feature/Setting: Configure Processors for automated field log ingestion, transformation, routing to HDFS or relational databases.

  3.7. MuleSoft
    • Feature/Setting: Set up automated flows using DataWeave for realtime ETL and automating integration with SAP or Salesforce.

  3.8. IBM App Connect
    • Feature/Setting: Automate trigger from email/file; built-in mapping nodes for data transformation and automated push to CMMS or EAM.

  3.9. TIBCO Cloud Integration
    • Feature/Setting: Automate event-based flows for preprocess and transformation, forwarding via REST API.

  3.10. Smartsheet
    • Feature/Setting: Use Data Shuttle or automated update requests for automated data forwarding to enterprise databases.

  3.11. Salesforce Flow
    • Feature/Setting: Automate field event handling, transformation logic, and record updates for survey/inspection logs.

  3.12. Google Apps Script
    • Feature/Setting: Script triggers on new Google Sheets rows for automated validation, preprocessing, and automator-driven forwarding.

  3.13. Alteryx
    • Feature/Setting: Run scheduled Alteryx Designer workflows for automated preprocessing and automated batch uploads.

  3.14. DataRobot MLOps
    • Feature/Setting: Automate integration with field datasets and automated preprocessing for model readiness.

  3.15. Airbyte
    • Feature/Setting: Automated pipelines for extracting, transforming, and loading field logs to data warehouse.

  3.16. Talend Data Fabric
    • Feature/Setting: Develop automated jobs for ETL processes specifically built for mining engineering data.

  3.17. Azure Logic Apps
    • Feature/Setting: Automate “When a blob is added or modified” in Azure Storage and automated forwarding to SQL DB.

  3.18. UiPath
    • Feature/Setting: Setup unattended automator workflows processing PDFs, CSVs, and automating data-forwarding to ERPs.

  3.19. Oracle Integration Cloud
    • Feature/Setting: Automate event-driven orchestrations for data transformation and ERP upload.

  3.20. Esri ArcGIS Online
    • Feature/Setting: Automate Survey123 triggers for data preprocessing and automated updating of geodatabases.

Benefits

  4.1. Automatedly minimizes human error and reduces cycle times for data handling.
  4.2. Automates compliance with regulatory and project data standards.
  4.3. Automator-driven increases in workforce productivity and data accessibility.
  4.4. Enables real-time analytics through instant automated data updating.
  4.5. Standardizes reporting and provides a scalable automation foundation for future digitalization in mining engineering.