(GCP– PDE) Preparing and Using Data for Analysis

Modern analytics depends on well-prepared, well-secured data that can be efficiently used across BI, reporting, and machine learning workflows. This course will teach you how to prepare, optimize, and secure data.

What you'll learn

Organizations often struggle to prepare data for analytics and machine learning in a way that balances performance, governance, and security across diverse tools and workloads. In this course, (GCP-PDE) Preparing and Using Data for Analysis, you'll gain the ability to prepare, optimize, and secure data for high-performance BI, reporting, and AI/ML workflows on Google Cloud. First, you'll explore how to connect BigQuery to analytical tools, precalculate fields, build aggregates, and troubleshoot slow queries to ensure fast and reliable dashboards. Next, you'll discover how to apply data masking, row-level and column-level security, and Cloud DLP techniques to protect sensitive information while enabling controlled analysis. Finally, you'll learn how to prepare data for machine learning and RAG workflows, including feature engineering, BigQuery ML, embeddings, and unstructured data processing. When you're finished with this course, you'll have the skills and knowledge of data preparation and analytical optimization needed to build production-ready analytical and AI pipelines and answer questions regarding this topic on the Professional Data Engineer certification.

Homepage

https://www.pluralsight.com/courses/google-cloud-pde-data-preparing-using-analyzing

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