Designing a Streaming Data Pipeline with DataFlow and Visualization Dashboard Using Looker
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September 27, 2023
- September 27, 2023
- Case Studies, Data Analytics
- By admin
Due to challenges with batch data processing, the organization is having trouble collecting real-time insights. The company consequently plans to build a streaming data pipeline in order to analyze real-time data from its e-commerce website. The streaming data pipeline would ingest, process, and store the data so that it could be utilized to study customer behavior and improve the user experience.
Cloud Dataflow is a fully managed, cloud-based service provided by Google Cloud Platform (GCP) for building and running large-scale data processing pipelines. It is a serverless data processing service that allows users to build batch and streaming data processing pipelines using the Apache Beam programming model.
It provides reliable, real-time messaging that enables asynchronous communication between distributed systems and applications. Cloud Pub/Sub supports both pub-sub and streaming messaging patterns and can handle millions of messages per second.
BigQuery is a fully-managed, cloud-based data warehousing and analytics platform in GCP. It enables users to analyze massive datasets using SQL queries and provides scalable, high-performance data processing capabilities
Looker is a business intelligence and data analytics platform that allows users to visualize and analyze their data using a web-based interface. it allows them to develop, manage, and share their data models and analytics.
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