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Jakub Wienke

Member since 2021

Silver League

2000 points
Achieving Advanced Insights with BigQuery Earned Kas 29, 2021 EST
Creating New BigQuery Datasets and Visualizing Insights Earned Kas 28, 2021 EST
Exploring and Preparing your Data with BigQuery Earned Kas 19, 2021 EST
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama Earned Kas 17, 2021 EST
BigQuery Verilerinden Analiz Elde Etme Earned Kas 8, 2021 EST
Data Catalog Fundamentals Earned Kas 7, 2021 EST
Build a Data Warehouse with BigQuery Earned Kas 7, 2021 EST

The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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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, Dataproc'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. Beceri rozeti, Google Cloud ürün ve hizmetlerindeki uzmanlık düzeyiniz karşılığında Google Cloud tarafından verilen özel bir dijital rozettir. Bilgilerinizi, etkileşimli ve uygulamalı bir ortamda kullanma becerinizi test eder. Ağınızla paylaşabileceğiniz bir beceri rozeti kazanmak için bu beceri rozeti kursunu ve son değerlendirme niteliğindeki yarışma laboratuvarını tamamlayın.

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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 Looker Studio'da rapor oluşturma Beceri rozeti, Google Cloud ürün ve hizmetlerindeki uzmanlık düzeyinizin tanınması amacıyla Google Cloud tarafından verilen özel bir dijital rozettir. Rozeti alabilmek için bildiklerinizi etkileşimli ve uygulamalı bir ortamda başarıyla kullanabilmeniz gerekir. Ağınızla paylaşabileceğiniz bir beceri rozeti kazanmak için bu beceri rozeti kursunu ve son değerlendirme niteliğindeki yarışma laboratuvarını tamamlayın.

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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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Complete the intermediate Build a Data Warehouse with BigQuery skill badge 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. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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