Olga Deryabina
Member since 2025
Diamond League
19254 points
Build Streaming Data Pipelines on Google Cloud
Earned Ağu 8, 2025 EDT
Build a Data Mesh with Knowledge Catalog
Earned Ağu 2, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned Tem 25, 2025 EDT
Share Data Using Google Data Cloud
Earned Tem 24, 2025 EDT
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama
Earned Tem 20, 2025 EDT
Streaming Analytics into BigQuery
Earned Tem 11, 2025 EDT
BigQuery Verilerinden Analiz Elde Etme
Earned Tem 7, 2025 EDT
Build a Data Warehouse with BigQuery
Earned Tem 1, 2025 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Haz 14, 2025 EDT
Introduction to Data Engineering on Google Cloud
Earned Haz 11, 2025 EDT
Build a Certification Study Guide: PDE Exam Prep
Earned Haz 5, 2025 EDT
In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
Learn more
Complete the introductory Build a Data Mesh with Knowledge Catalog skill badge to demonstrate skills in the following: building a data mesh with Knowledge Catalog to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in tagging assets, assigning IAM roles, and assessing data quality in Knowledge Catalog.
Learn more
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
Learn more
Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
Learn more
Giriş düzeyindeki Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Dataprep by Trifacta ile veri temizleme, Dataflow'da veri ardışık düzenleri çalıştırma, Managed Service for Apache Spark'ta küme oluşturma ve Apache Spark işleri çalıştırma ve makine öğrenimi API'lerini (Cloud Natural Language API, Google Cloud Speech-to-Text API ve Video Intelligence API dahil olmak üzere) çağırma.
Learn more
Earn a skill badge by completing the Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.
Learn more
Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.
Learn more
Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
Learn more
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
Learn more
In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
Learn more
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
Learn more
