Enhanced Data Infrastructure for Real-Time Influencer Analytics

In the fast-paced world of social media, staying ahead of trends and influencer impacts is crucial for maintaining a competitive edge. Our enterprise company, a leader in social media and influencer marketing, is embarking on a transformative project to overhaul our data engineering capabilities. We aim to design a scalable, real-time data infrastructure to enable precise and immediate influencer analytics. The project will focus on integrating Apache Kafka for event streaming, orchestrating data workflows with Airflow, and leveraging Spark for data processing. We will implement a data mesh architecture to decentralize and democratize our data resources, ensuring each team can access and utilize data effectively. Utilizing Snowflake and BigQuery, we will establish a robust storage and querying foundation to support complex analytical needs. Through this initiative, we intend to deploy MLOps practices to incorporate machine learning models that enhance our analytics accuracy over time. Data observability will play a vital role in monitoring the health and performance of our data pipelines, ensuring reliability and efficiency. This project will position us to deliver unparalleled insights to our clients, transforming how brands connect with influencers and audiences alike.