Course
digicode: IDAGC
Introduction to Data Analytics on Google Cloud («IDAGC»)
This course covers the basics of data analysis, including collection, storage, exploration, visualization, and sharing on Google Cloud. It also introduces learners to Google Cloud's data analytics tools and services.
Duration
1 day
Price
850.–
Course documents
Official Google Cloud courseware
Course facts
- Describing the data analytics workflow on Google Cloud and summarizing the different types of analytics
- Identifying Google Cloud data analytics products and describing how each is used to work with data
- Describing data sources, data structures, and data storage options in Google Cloud
- Using BigQuery, Looker, and Looker Studio to answer data questions and influence business decisions
- Data analytics workflow
- Data sources
- Storage methods
- Google Cloud data analytics products
- Data types
- Detailing and describing the data analytics workflow on Google Cloud
- Comparing and contrasting data sources and storage methods available in Google Cloud
- Comparing how different data types can be used for data analytics
- BigQuery services, capabilities, and organization
- Data storage
- Basic SQL
- Answering data-driven questions
- Describing BigQuery and the BigQuery solution architecture
- Deriving insights from data by using BigQuery
- Using the BigQuery user interface to run basic queries
- Lab 1: BigQuery Qwik Start: Console
- Lab 2: Introduction to SQL for BigQuery and Cloud SQL
- Lab 3: BigLake: Qwik Start
- Lab 4: Analyze data with Gemini Assistance
- Looker data exploration terms and concepts
- Looks and dashboards
- Visualizations
- Report sharing
- Looker Studio
- Manipulating a Looker Explore to answer data-driven questions
- Creating a situation-appropriate visualization to highlight the answer for a data-driven question
- Choosing between Looker and Looker Studio for data visualization and sharing
- Sharing visualizations with others
- Lab 1: Looker Data Explorer—Qwik Start
- Lab 2: Looker Data Studio—Qwik Start
- Basic familiarity with SQL
- Basic understanding of data concepts such as data types (relational, non-relational) and storage (data lakes, data warehouses)