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Walkthrough: Data Architecture Diagram - Exploring and Preparing your Data with BigQuery

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Walkthrough: Data Architecture Diagram - Exploring and Preparing your Data with BigQuery
From Data to Insights with Google Cloud Platform Specialization
Welcome to the Coursera specialization, From Data to Insights with Google Cloud Platform brought to you by the Google Cloud team. I’m Evan Jones (a data enthusiast) and I’m going to be your guide.
This first course in this specialization is Exploring and Preparing your Data with BigQuery. Here we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Cloud Dataprep to analyze and transform your datasets.
This course should take about one week to complete, 5-7 total hours of work. By the end of this course, you’ll be able to query and draw insight from millions of records in our BigQuery public datasets. You’ll learn how to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery. Lastly, you’ll get to practice writing and troubleshooting SQL on a real Google Analytics e-commerce dataset to drive marketing insights.
Bigquery, Google Cloud Platform, Cloud Computing, SQL
The instructor is knowledgeable and passionate about the course content, and explain the idea clearly. It's one of the best and fun online courses I have ever taken. Great course!,This is a brilliant course for anyone who is in the analytics field and is new to GCP and wants to learn. I love easily Google teaches the concepts with very simple examples!
Walkthrough: Data Architecture Diagram - Exploring and Preparing your Data with BigQuery
Copyright Disclaimer under Section 107 of the copyright act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.
Walkthrough: Data Architecture Diagram - Exploring and Preparing your Data with BigQuery
From Data to Insights with Google Cloud Platform Specialization
Welcome to the Coursera specialization, From Data to Insights with Google Cloud Platform brought to you by the Google Cloud team. I’m Evan Jones (a data enthusiast) and I’m going to be your guide.
This first course in this specialization is Exploring and Preparing your Data with BigQuery. Here we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Cloud Dataprep to analyze and transform your datasets.
This course should take about one week to complete, 5-7 total hours of work. By the end of this course, you’ll be able to query and draw insight from millions of records in our BigQuery public datasets. You’ll learn how to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery. Lastly, you’ll get to practice writing and troubleshooting SQL on a real Google Analytics e-commerce dataset to drive marketing insights.
Bigquery, Google Cloud Platform, Cloud Computing, SQL
The instructor is knowledgeable and passionate about the course content, and explain the idea clearly. It's one of the best and fun online courses I have ever taken. Great course!,This is a brilliant course for anyone who is in the analytics field and is new to GCP and wants to learn. I love easily Google teaches the concepts with very simple examples!
Walkthrough: Data Architecture Diagram - Exploring and Preparing your Data with BigQuery
Copyright Disclaimer under Section 107 of the copyright act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.