Real-time Data Pipeline Development for Enhanced Influencer Campaign Analytics

As an SME in the Social Media & Influencer industry, we recognize the growing need for real-time insights into influencer campaign performance. Our current data processing system is batch-oriented and lacks the agility needed to keep pace with the rapidly changing social media landscape. To address this, we are initiating a project to develop a real-time data pipeline using Apache Kafka, Spark, and Databricks. This pipeline will enable us to process and analyze data as events occur, delivering actionable insights to brands on influencer performance and audience engagement. The project will also incorporate Airflow for orchestrating workflows and dbt for transforming data within Snowflake. By enhancing our analytics capabilities, we aim to improve campaign outcomes, optimize influencer selection, and provide unprecedented transparency to our clients. This initiative is crucial for maintaining a competitive edge and meeting the increasing demand for real-time data from brands.