Apply Scripting for Business Intelligence Development and Automation

This standard defines the competencies required for using scripting to enhance efficiency in Business Intelligence (BI) operations and to support real-time decision-making. It encompasses skills for automating data processes, managing complex data analyses, and streamlining BI workflows to ensure accurate, timely, and efficient outcomes across diverse BI activities.

The standard covers key programming competencies integral to BI, including for Extract, Transform, Load (ETL) processes, automation of repetitive tasks, and data manipulation; and for advanced statistical modelling and data analysis. It also includes using scripting to handle large data sets, automate reporting, reduce manual intervention, and enable real-time analytics that support data-driven decision-making across an organisation.

This standard is intended for BI professionals responsible for developing and implementing scripts to optimise BI solutions, automate data workflows, and integrate data insights seamlessly into business operations.

1. Develop efficient, scalable, and reusable scripts to automate Business Intelligence (BI) tasks, including data extraction, transformation, loading (ETL), statistical modelling, and predictive analytics.
2. Optimise BI scripts for performance, scalability, and efficiency, including handling large datasets effectively while minimising processing time and resource consumption.
3. Use version control systems to track, manage, and maintain BI scripts, enabling collaboration, rollback functionality, and improved maintainability.
4. Create modular, reusable script components to streamline development, reduce redundancy, and enhance maintainability across BI projects.
5. Identify, troubleshoot, and resolve BI script issues, applying structured debugging techniques, logging, error handling, and dependency management to maintain accuracy and reliability.
6. Test and validate BI scripts using automated and manual testing frameworks, to validate correct functionality, performance, and seamless integration with BI workflows.
7. Document scripts, workflows, and methodologies using structured formats to maintain collaboration, maintainability, and knowledge sharing in line with organisational standards.

1. Industry-standard scripting languages for BI and their application in ETL processes, automation, and data analysis.
2. Advanced data analysis and predictive analytics techniques, including statistical modelling, machine learning integration, and time-series forecasting to support business intelligence operations.
3. Scripting methodologies for ETL (Extract, Transform, Load) and data manipulation, including batch processing, real-time data streaming, and API-based data extraction.
4. Principles of developing modular, reusable BI script components, for efficiency, maintainability, and integration with enterprise data workflows.
5. How to align BI scripting outputs with organisational and end-user needs, including custom calculations, dynamic reporting automation, and role-based data access.
6. Techniques for optimising BI scripts for performance and scalability, including indexing strategies, parallel processing, caching, and asynchronous execution.
7. Industry best practices for debugging and troubleshooting BI scripts, including structured logging, exception handling, dependency resolution, and monitoring tools.
8. Use of version control systems for tracking, managing, and maintaining BI scripts, including branching strategies, collaborative workflows, and rollback mechanisms.
9. Testing methodologies for BI scripts, including unit testing, integration testing, regression testing, and automated testing frameworks for validating script accuracy and efficiency.
10. Techniques for documenting BI scripts and workflows using industry-standard practices, including commenting standards, API documentation tools, and knowledge-sharing platforms.
11. Best practices for implementing automated alerting mechanisms in BI scripts, enabling proactive monitoring of reporting thresholds and real-time anomaly detection.
12. Deployment and CI/CD (Continuous Integration/Continuous Deployment) strategies for BI scripts, to provide efficient updates, rollback capabilities, and integration with cloud-based BI platforms.