Exploring ​and ​Preparing ​your ​Data with BigQuery

Por: Coursera . en: , ,

Descripción del Curso

***NEW! Specialization Completion Challenge, receive Qwiklabs credits valued up to $120! See below for details.***

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.

SPECIALIZATION COMPLETION CHALLENGE
As if learning new skills wasn’t enough of an incentive, we're excited to announce a special completion challenge for 'From Data to Insights on Google Cloud Platform’ specialization.

Here’s how it works: Our completion challenge runs through 11:59pm PT May 5, 2019. Complete any course in this Specialization anytime in this period and we'll send you 30 Qwiklabs credits for each course completed (upto $120 value given there are 4 courses in the specialization).

You can use these credits to take additional labs and earn badges, which you can then add to your resume and social profiles.

>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

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