Media — Streaming Engagement Data Ingestion for Demand Forecasting

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This DAG ingests viewing and engagement data from multiple sources to forecast demand. It ensures data integrity and provides actionable insights for marketing and content teams.

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Overview

The purpose of this DAG is to facilitate the ingestion of viewing and engagement data essential for demand forecasting in the media industry. It sources data from various systems, including content management systems, audience databases, and streaming APIs. The ingestion pipeline begins with data extraction from these diverse sources, followed by normalization to ensure consistency across datasets. Once normalized, the data is stored in a centralized data warehouse, which serves as a foundation

The purpose of this DAG is to facilitate the ingestion of viewing and engagement data essential for demand forecasting in the media industry. It sources data from various systems, including content management systems, audience databases, and streaming APIs. The ingestion pipeline begins with data extraction from these diverse sources, followed by normalization to ensure consistency across datasets. Once normalized, the data is stored in a centralized data warehouse, which serves as a foundation for further analysis. Quality control measures are implemented throughout the process to verify data integrity, including checks for completeness and accuracy. The processed data is then made available via an API, allowing marketing and content teams to access valuable insights. Key performance indicators (KPIs) such as data accuracy, ingestion speed, and API response time are monitored to ensure optimal performance. This DAG not only enhances the accuracy of demand forecasts but also empowers media organizations to make informed decisions, ultimately driving revenue growth and improving audience engagement.

Part of the Market & Trading Intelligence solution for the Media industry.

Use cases

  • Improves demand forecasting accuracy for media content.
  • Enhances decision-making capabilities for marketing teams.
  • Drives audience engagement through targeted content strategies.
  • Increases operational efficiency with automated data ingestion.
  • Facilitates real-time insights for agile business responses.

Technical Specifications

Inputs

  • Content management system data logs
  • Audience engagement databases
  • Streaming API data feeds

Outputs

  • Normalized data in data warehouse
  • Forecast reports for marketing teams
  • API endpoints for data access

Processing Steps

  1. 1. Extract data from content management systems
  2. 2. Fetch audience engagement data from databases
  3. 3. Retrieve data from streaming APIs
  4. 4. Normalize and clean the ingested data
  5. 5. Store the processed data in the data warehouse
  6. 6. Implement quality control checks on data
  7. 7. Expose data through API for end-user access

Additional Information

DAG ID

WK-1504

Last Updated

2025-10-03

Downloads

95

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