AI & Data

Google BigQuery Training

Google BigQuery is a data warehouse available in Google Cloud.

Duration
6h
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Who it's for

Ideal for teams that…

1 Solution architects and data warehouse specialists
2 Data analysts and professionals working with data processing
3 Data engineers responsible for building and maintaining infrastructure
4 People familiar with SQL basics
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

Understand the basics of Google BigQuery – a rapidly growing data warehouse in Google Cloud Platform

✓

Learn core skills in writing queries, creating and managing datasets and tables, and designing ETL/ELT processes with Google Cloud tools

✓

Visualize data stored in the warehouse using Looker Studio and Google Sheets, and connect BigQuery with tools such as Power BI and Tableau

✓

Explore real-world applications of BigQuery in data science and get introduced to machine learning with BigQuery ML

Program · 7 modules

What we actually do

M01
Module 1 – Introduction to Google Cloud Platform
  • · BigQuery as part of Google Cloud Platform (GCP)
  • · Complementary GCP services: Cloud Storage, Cloud SQL, Cloud Functions, DataPrep, etc.
  • · Projects
  • · Billing accounts
  • · User permissions
  • · Introduction to data warehouses – concepts and assumptions
M02
Module 2 – Basics of Working with Google BigQuery
  • · Datasets, tables, and queries – data management in BigQuery
  • · BigQuery query editor interface
  • · Cloud Shell – working in the CLI environment
  • · Basic SELECT queries
  • · Filtering (WHERE), sorting (ORDER BY)
  • · Aggregations (COUNT, SUM) with GROUP BY and HAVING
M03
Module 3 – Creating and Managing Datasets and Tables
  • · Creating and configuring datasets
  • · Data types and column modes
  • · Working with arrays and structs
  • · Partitioning data
  • · Querying wildcard tables
M04
Module 4 – Loading Data into Google BigQuery
  • · ETL / ELT processes in BigQuery
  • · Using BigQuery Public Datasets
  • · Importing data from Google Cloud Storage
  • · Loading data from MySQL and PostgreSQL
  • · Loading data from Google Drive and Google Sheets
  • · Using the BigQuery API for data logging
  • · Data Transfer Service
  • · Scheduled Queries
M05
Module 5 – Writing SQL Queries in BigQuery (Practice)
  • · JOINs for combining data from multiple tables
  • · Saved Queries for teamwork and collaboration
M06
Module 6 – Data Visualization and Reporting
  • · Exporting and analyzing data in Google Sheets
  • · Building dashboards in Looker Studio with BigQuery
  • · Power BI
  • · Tableau
M07
Module 7 – Practical Applications in Daily Work
  • · Python
  • · pandas
  • · Jupyter Notebooks
  • · Service accounts and external tools (e.g. DataGrip)
  • · Regression models
  • · Time series forecasting
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.

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