Introduction to Data Analytics on Google Cloud

SKU: GCPIDA

197.490 kr.

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This course is an introduction to data analytics on Google Cloud.

The course covers the basics of data analysis, including collection, storage, exploration, visualization, and sharing. It also introduces learners to Google Cloud's data analytics tools and services.

Through video lectures, demos, quizzes, and hands-on labs, the course demonstrates how to go from raw data to impactful visualizations and dashboards.

Forkröfur

Before starting this learning path, you should already have:

  • Basic familiarity with SQL
  • Basic understanding of data concepts such as data types (relational, non-relational) and storage (data lakes, data warehouses

Target audience

The target audience is aimed at introductory level data analysts.

Nemandi mun læra eftirfarandi

By the end of this course, learners will be able to:

  • Describe the data analytics workflow on Google Cloud and summarize the different types of analytics.
  • Identify Google Cloud data analytics products and describe how each is used to work with data.
  • Describe data sources, data structures, and data storage options in Google Cloud.
  • Use BigQuery, Looker, and Looker Studio to answer data questions and influence business decisions

Samantekt

Understand the Data Analytics Lifecycle on Google Cloud

  • Detail and describe the data analytics workflow on Google Cloud.
  • Compare and contrast data sources and storage methods available in Google Cloud.
  • Compare how different data types can be used for data analytics.

Explore Data and Extract Insights by Using BigQuery

  • Describe BigQuery and the BigQuery solution architecture.
  • Derive insights from data by using BigQuery.
  • Use the BigQuery user interface to run basic queries.

Make Data-Driven Decisions by Using Looker

  • Manipulate a Looker Explore to answer data-driven questions.
  • Create a situation-appropriate visualization to highlight the answer for a datadriven question.
  • Choose between Looker and Looker Studio for data visualization and sharing.
  • Share visualizations with others.

Exams and Assessments

No formal examinations for this course. There will be a module review and summary following the practical hands-on lab, quiz and slide-deck deliveries. This will further enforce learning and support additional resource finds, for continued learning and development.

Hands-on Learning

Within this course there are opportunities for learners to engage in hands-on labs to support module learning.

In addition, each module will also have a quiz, to support knowledge capture.