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Research Paper | Information Technology | United States of America | Volume 12 Issue 9, September 2023 | Popularity: 3.1 / 10
Mastering Data Quality Management in Google Cloud: Strategies for Clean and Reliable Data Pipelines
Tulasiram Yadavalli
Abstract: Data quality is essential for creating clean, reliable data pipelines. In Google Cloud, tools like Dataflow, Cloud Dataprep, and BigQuery help ensure that data is validated, cleansed, and transformed efficiently. These tools are designed to address common challenges in data management, such as incomplete data, duplicates, or incorrect formats. This article discusses best practices for data quality management on Google Cloud, including validation techniques, cleansing strategies, and transformation processes. It looks at how these strategies improve the reliability and usability of data, offering scalable solutions to data integrity issues. With the increasing reliance on data-driven decision-making, mastering data quality management is critical for modern businesses to ensure data consistency and accuracy across their pipelines.
Keywords: Data quality, Google Cloud, Dataflow, Cloud Dataprep, BigQuery, data cleansing, data validation, data transformation, data pipelines, cloud computing
Edition: Volume 12 Issue 9, September 2023
Pages: 2232 - 2236
DOI: https://www.doi.org/10.21275/SR230915093726
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