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High Tech — Data Normalization and Quality Assurance Pipeline

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This DAG ensures the normalization and quality of ingested data for reliable analyses. It implements lineage tracking and security controls to maintain data integrity and confidentiality.

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Overview

The purpose of this DAG is to standardize and enhance the quality of data ingested into the Knowledge Portal, ensuring that the data is reliable for subsequent analyses. The pipeline begins with the ingestion of various data sources, including ERP transaction logs, customer feedback, and product specifications. Once the data is ingested, it undergoes a series of processing steps designed to normalize the data according to predefined quality standards. This includes applying data validation tests

The purpose of this DAG is to standardize and enhance the quality of data ingested into the Knowledge Portal, ensuring that the data is reliable for subsequent analyses. The pipeline begins with the ingestion of various data sources, including ERP transaction logs, customer feedback, and product specifications. Once the data is ingested, it undergoes a series of processing steps designed to normalize the data according to predefined quality standards. This includes applying data validation tests to check for completeness, accuracy, and consistency. Additionally, lineage tracking techniques are employed to monitor the transformations applied to the data, ensuring that any changes can be traced back to their origin, thereby guaranteeing data integrity. Security controls are also integrated to protect sensitive information throughout the process. The outputs of this DAG include normalized datasets, quality reports, and compliance metrics that provide insights into the data's adherence to quality standards. Key performance indicators (KPIs) for monitoring include the compliance rate with quality standards and the processing time for data normalization. This DAG adds significant business value by enhancing the reliability of data analyses, which is crucial for informed decision-making in the high-tech industry.

Part of the Knowledge Portal & Ontologies solution for the High Tech industry.

Use cases

  • Improved data reliability enhances decision-making capabilities
  • Increased compliance with industry standards and regulations
  • Faster data processing leads to timely insights
  • Enhanced data security protects sensitive business information
  • Streamlined data integration from multiple sources

Technical Specifications

Inputs

  • • ERP transaction logs
  • • Customer feedback data
  • • Product specifications
  • • Market research data

Outputs

  • • Normalized datasets ready for analysis
  • • Quality assurance reports
  • • Compliance metrics dashboards

Processing Steps

  1. 1. Ingest data from multiple sources
  2. 2. Apply data validation tests
  3. 3. Normalize data to standard formats
  4. 4. Implement lineage tracking for transformations
  5. 5. Conduct security checks on sensitive information
  6. 6. Generate quality assurance reports
  7. 7. Output normalized datasets and metrics

Additional Information

DAG ID

WK-1022

Last Updated

2026-01-16

Downloads

47

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