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Unifying  Data  Operations to Power Proactive Threat Response

Impact Delivered

  • 65% Reduced code complexity
  • 80% Increased development speed
  • 60% Cut development costs
  • 100% Boosted data reliability and quality
  • The Customer

    The Customer

    The customer is a leading unified talent platform provider specializing in comprehensive learning and human capital management software. Their AI-powered talent experience platform brings together technology, data, and content to promote growth, agility, and success on a large scale. With over 7,000 customers and 100 million users across 180 countries and 50 languages, they are renowned for their robust data analytics that support business intelligence tools.

  • The Challenge

    The Challenge

    challenge_img.png

    Some of the key challenges encountered include:

    Data analytics at this organization involves collecting data from multiple sources, staging, transforming into OLAP format, and storing it in a data warehouse for BI tool consumption, using technologies like Fivetran, DBT, Snowflake, and Tableau. However, CSOD encounters challenges such as scheduling delays that disrupt subsequent jobs, unverified data quality, and complex data transfers across networks that compromise data integrity. Additionally, the absence of tracking mechanisms for data operations and quality leads to reactive rather than proactive issue resolution.

  • The Solution

    The Solution

    To address these challenges, CriticalRiver implemented a comprehensive solution using Apache Airflow, highlighted by several key components:

    • CSOD Airflow Framework: Standardized pipeline deployment across all functions.
    • Direct S3 Ingestion: Eliminated reliance on Fivetran, streamlining data flows.
    • Custom Logging: Enhanced task logging for improved data management.
    • Data Quality Checks: Integrated Great Expectations for stringent quality control.
    • Observability Dashboard: Enabled continuous monitoring of pipeline health.
    • Tool Integration: Optimized the use of DBT for transformations and Tableau for visualization.
  • Solution Components

    Solution Components

    Apache Airflow, CriticalRiver’s CSOD Airflow Framework, Integration with DBT, and Tableau.

  • The Results

    The Results

    • Standard Coding Practices: Simplified code across all pipelines, reducing technical debt.
    • Simplified Development: Streamlined pipeline development with a unified design language.
    • Speed & Productivity: Increased development speed with configuration templates reducing repetitive coding.
    • Scalability & Extendability: Enabled easy expansion and configuration of pipelines.
    • Performance: Enhanced processing through parallel executions and controlled DBT activities.
    • Pipeline Audit: Implemented real-time observability and proactive issue resolution.
    • Cost Reduction: Decreased development time and resources with efficient frameworks.
    • Improved Quality: Ensured high-quality, reliable, and scalable pipeline construction.

    This transformation not only optimized CSOD’s data analytics capabilities but also positioned them for scalable growth and enhanced digital agility.

Impact Delivered

  • 65% Reduced code complexity
  • 80% Increased development speed
  • 60% Cut development costs
  • 100% Boosted data reliability and quality

The Customer

The customer is a leading unified talent platform provider specializing in comprehensive learning and human capital management software. Their AI-powered talent experience platform brings together technology, data, and content to promote growth, agility, and success on a large scale. With over 7,000 customers and 100 million users across 180 countries and 50 languages, they are renowned for their robust data analytics that support business intelligence tools.

The Challenge

challenge_img.png

Some of the key challenges encountered include:

Data analytics at this organization involves collecting data from multiple sources, staging, transforming into OLAP format, and storing it in a data warehouse for BI tool consumption, using technologies like Fivetran, DBT, Snowflake, and Tableau. However, CSOD encounters challenges such as scheduling delays that disrupt subsequent jobs, unverified data quality, and complex data transfers across networks that compromise data integrity. Additionally, the absence of tracking mechanisms for data operations and quality leads to reactive rather than proactive issue resolution.

The Solution

To address these challenges, CriticalRiver implemented a comprehensive solution using Apache Airflow, highlighted by several key components:

  • CSOD Airflow Framework: Standardized pipeline deployment across all functions.
  • Direct S3 Ingestion: Eliminated reliance on Fivetran, streamlining data flows.
  • Custom Logging: Enhanced task logging for improved data management.
  • Data Quality Checks: Integrated Great Expectations for stringent quality control.
  • Observability Dashboard: Enabled continuous monitoring of pipeline health.
  • Tool Integration: Optimized the use of DBT for transformations and Tableau for visualization.

Solution Components

Apache Airflow, CriticalRiver’s CSOD Airflow Framework, Integration with DBT, and Tableau.

The Results

  • Standard Coding Practices: Simplified code across all pipelines, reducing technical debt.
  • Simplified Development: Streamlined pipeline development with a unified design language.
  • Speed & Productivity: Increased development speed with configuration templates reducing repetitive coding.
  • Scalability & Extendability: Enabled easy expansion and configuration of pipelines.
  • Performance: Enhanced processing through parallel executions and controlled DBT activities.
  • Pipeline Audit: Implemented real-time observability and proactive issue resolution.
  • Cost Reduction: Decreased development time and resources with efficient frameworks.
  • Improved Quality: Ensured high-quality, reliable, and scalable pipeline construction.

This transformation not only optimized CSOD’s data analytics capabilities but also positioned them for scalable growth and enhanced digital agility.

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