Implementing a Real-Time Data Pipeline for Enhanced BPO Operations

As a leading player in the Business Process Outsourcing industry, we recognize the imperative to leverage real-time data insights to maintain a competitive edge. Our current data processing systems rely on batch processing, leading to delays in accessing actionable insights. The proposed project involves developing a robust real-time data pipeline that integrates cutting-edge technologies including Apache Kafka for event streaming, Spark for real-time data processing, Airflow for orchestrating workflows, and dbt for data transformation. We also aim to enhance data observability to ensure high data quality and operational efficiency. The integration with Snowflake or BigQuery will enable scalable and efficient data storage and querying. This 12-20 week project focuses on creating a resilient architecture capable of handling large-scale data across various operational processes, enabling immediate feedback and decision-making capabilities. By adopting a data mesh approach, we aim to decentralize data ownership and foster a culture of data-driven decision-making across the organization.