Technologies / Data & Analytics

Practical Data Analysis in Google Cloud with BigQuery and Looker

The training focuses on the practical use of the most important Google Cloud Platform analytics tools for processing and visualizing large data sets. The program combines advanced techniques for working with BigQuery as a data warehouse with building interactive dashboards in Looker. Sessions are run as practical workshops in which participants carry out real analytics projects. The training prepares participants to use the Google Cloud ecosystem effectively in Business Intelligence projects.

Why choose this training?

Growing market demands mean that technical skills are becoming a key asset on the job market. The training focuses on the practical use of the most important Google Cloud Platform analytics tools for processing and visualizing large data sets.

The training delivers comprehensive technology knowledge, enabling participants to apply the skills they acquire immediately in their daily professional work.

The training is particularly valuable for: data analysts looking for modern tools to work with large data sets, data engineers developing their skills in the Google Cloud ecosystem, and Business Intelligence specialists moving to cloud platforms.

What makes our approach unique?

At EITT, we believe that the best learning happens through practice. During 3 days of intensive training, participants work on real-world examples and scenarios.

With over 2,500 trainings in our portfolio, EITT is a trusted partner in competency development for organizations of all sizes. Our trainers are practitioners with many years of experience who share up-to-date knowledge and proven solutions.

Looking for a training tailored to your team’s needs? Contact us — we will prepare a program customized to your requirements.

Benefits

Advanced SQL query techniques in BigQuery with partitioning, clustering and analytic functions
Creating interactive dashboards and reports on the Looker platform using LookML
Transforming and preparing data in a cloud environment with Dataform, dbt and Cloud Storage
Query optimization and analytics cost management in Google Cloud Platform
Integrating BigQuery with Vertex AI, Dataflow and other Google Cloud Platform services
Access control and data security mechanisms in analytics projects (IAM, authorized views, data masking)
Using BigQuery ML and Gemini models to boost productivity when working with data
Delivering complete Business Intelligence projects on the Google Cloud ecosystem

Who is this training for?

Data analysts looking for modern tools to work with large data sets

Data engineers developing their skills in the Google Cloud ecosystem

Business Intelligence specialists moving to cloud platforms

Developers interested in integrating applications with GCP analytics services

Product managers who need advanced analytics tools

IT consultants specializing in analytics solutions

Database administrators exploring modern data warehouses

People preparing for Google Cloud Data Analytics certification

Prerequisites

Solid knowledge of SQL and basic database operations
Experience working with analytics or Business Intelligence tools
Basic knowledge of data warehouse concepts and ETL processes
Ability to read and interpret relational database diagrams
Knowledge of the basic principles of data visualization and report building

Training program

The Google Cloud data ecosystem and how its services interconnect
BigQuery as a serverless data warehouse and analytics engine
Looker as a BI and data visualization platform
BigQuery architecture: projects, datasets, tables, jobs
Methods for loading data into BigQuery from various sources

Standard SQL in BigQuery: syntax, data types, operators
Analytic functions (window functions) and complex joins
Query optimization: partitioning, clustering, best practices
Working with semi-structured data: JSON, ARRAY, STRUCT
User-Defined Functions (UDFs) in SQL and JavaScript

Data transformation techniques: CREATE TABLE AS SELECT, MERGE

Introduction to Dataform and dbt integrated with BigQuery
Integration with Cloud Storage for raw and processed data
Dataflow basics as a tool for building ETL/ELT pipelines

Looker platform architecture and configuring the connection to BigQuery
LookML basics: dimensions, measures, views, models
Creating and managing data models in LookML
Explores and defining relationships between tables
Data visualization and building dashboards in Looker
Available visualization types and best practices for using them
Building interactive dashboards: tiles, filters, parameters
Drill-down and drill-through functionality
Sharing, subscriptions and report scheduling
Management and security of analytical data
Access control mechanisms in BigQuery (IAM, authorized views)

Data masking techniques and row-level security
Monitoring resource usage and costs
Introduction to Dataplex as a metadata management tool
Using AI in data analytics on GCP
BigQuery ML: building machine learning models in SQL
Integrating BigQuery with Vertex AI for advanced ML scenarios
Using Gemini models in BigQuery to boost productivity
Generating SQL queries, summarizing data, creating explanations
Practical applications of AI in a data analyst's daily work

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Training Topics

Frequently asked questions

What are the prerequisites for this training?

For Practical Data Analysis in Google Cloud with BigQuery and Looker we recommend: Solid knowledge of SQL and basic database operations; Experience working with analytics or Business Intelligence tools; Basic knowledge of data warehouse concepts and ETL processes.

What is the format and duration of this training?

The training lasts 3 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Data analysts looking for modern tools to work with large data sets; Data engineers developing their skills in the Google Cloud ecosystem; Business Intelligence specialists moving to cloud platforms.