Google BigQuery Training

Catalogue index: IFS/62

  • In stock
  • Delivery: free
  • Dedicated training:
  • Producer:
  • Training level:
    • Średniozaawansowany
  • Type of training:
    • stacjonarnie; online
PLN993.33 net / particip. PLN14,899.95  net for 1 workshop PLN1,221.80 gross incl. 23% VAT / particip.

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Features

Features
Certification:
  • TAK
Dedicated training:
Number of training hours:
  • 16
Producer:
Training language:
  • polski
Training level:
  • Średniozaawansowany
Type of training:
  • stacjonarnie; online

Description

Company Description

InfoShare Academy is a leading IT academy offering comprehensive educational programs in new technologies for companies. Since 2015, we have supported organizations in developing technology teams through dedicated courses in Machine Learning, DevOps, Data Engineering, Python, UX/UI Design, AWS, and Kubernetes. Our training is based on practical skills and real business cases. We collaborate with over 300 industry practitioners, ensuring that our programs are tailored to current market needs. We specialize in reskilling and upskilling employees. With us, you will build effective teams implementing new technologies that will accelerate innovation and strengthen your company's competitiveness in the market. Check out our training offerings designed for companies, created to develop your employees' competencies in the IT field.

Training Description

Google BigQuery is a data warehouse available in Google Cloud. It provides storage and management of large amounts of data. BigQuery is characterized by high scalability and the fact that management does not require maintaining expensive infrastructure.

Who is this training for
  • For solution architects and data warehouse specialists
  • For data analysts and data processing professionals
  • For data engineers responsible for creating and maintaining infrastructure
  • For individuals who know the basics of SQL
Objectives
  • Master the fundamentals of Google BigQuery – a dynamically evolving data warehouse that is part of Google Cloud (Google Cloud Platform)
  • Learn the basics of working in BigQuery – writing queries, creating and managing datasets and tables, designing ETL and ELT processes using tools available in Google Cloud
Benefits
  • Learn how to visualize data collected in the data warehouse in Looker Studio and Google Sheets, as well as how to connect BigQuery with popular tools such as PowerBI and Tableau
  • Discover practical applications of BigQuery in data science and learn how to easily start machine learning with BigQuery ML features.
Training Program

  1. Module 1 – Introduction to Google Cloud Platform

    • Google BigQuery as part of Google Cloud Platform (GCP)

    • Complementary GCP services used together with BigQuery (Google Cloud Storage, Cloud SQL, Cloud Functions, DataPrep, and others)

    • Overview of basic GCP components needed to work with BigQuery (project, billing account, user permissions)

    • Introduction to data warehouses – the idea of operation, key concepts, and assumptions

  2. Module 2 – Basics of working with Google BigQuery

    • Datasets, tables, and queries – how to work with data in BigQuery

    • Query editor in the Google BigQuery interface

    • Cloud Shell – working with data in the CLI (command line) environment

    • Retrieving data using basic SELECT queries

    • Manipulating query results using filtering (WHERE), sorting (ORDER BY)

    • Aggregating data (COUNT, SUM) using GROUP BY and HAVING

  3. Module 3 – Creating and managing datasets and tables

    • Creating and configuring datasets

    • Creating a table based on schema and CREATE OR REPLACE TABLE queries

    • Basic data types and column modes

    • Working with arrays and structs in BigQuery

    • Partitioning data and querying multiple tables using wildcards

  4. Module 4 – Loading data into Google BigQuery

    • Introduction to ETL and ELT processes using BigQuery data warehouse

    • Public datasets (BigQuery Public Datasets)

    • Importing data from Google Cloud Storage to BigQuery

    • Loading data from external data sources – MySQL, PostgreSQL

    • Loading data from Google Drive and Google Sheets

    • Logging data in BigQuery using BigQuery API

    • Automating data loading using Data Transfer Service and Scheduled Queries

  5. Module 5 – Writing SQL queries in BigQuery – practical exercises

    • Joining data from multiple tables using JOINs

    • Common Table Expressions using WITH in BigQuery

    • Working with data arrays using ARRAY_AGG and UNNEST functions

    • Formatting date and time – working with TIMESTAMP, DATETIME, and DATE data

    • Saved Queries – saving queries and collaborating in teams

  6. Module 6 – Data visualization and reporting using BigQuery

    • Exporting and analyzing data from BigQuery in Google Sheets

    • Creating dashboards in Looker Studio based on data from Google BigQuery

    • Integrating BigQuery with other data visualization tools (PowerBI, Tableau)

  7. Module 7 – Practical applications of BigQuery in daily work

    • BigQuery API and Google Cloud Client Libraries in popular programming languages

    • Connecting Google BigQuery with popular Data Science tools (Python, pandas, Jupyter)

    • Creating a service account and using data in BigQuery in external programs like DataGrip

    • Introduction and discussion of BigQuery ML machine learning functionalities – examples of applications in linear regression and time series forecasting

Duration

16 h/2 days

Price includes
  • Certificate of completion
  • Monthly access to training recordings (in case of online format)
  • Customization of the training program to client needs

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