Exploring and Preparing your Data with BigQuery

Overview This Exploring and Preparing your Data with BigQuery provides an introduction to data warehousing with a focus on using …

Exploring and Preparing your Data with BigQuery

Exploring and Preparing your Data with BigQuery

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Exploring and Preparing your Data with BigQuery Overview

This Exploring and Preparing your Data with BigQuery provides an introduction to data warehousing with a focus on using Google BigQuery. Through a series of guided lessons, you will learn how to explore, manage, and analyse large datasets efficiently. By the end of this course, you will be able to leverage the power of BigQuery to drive decision-making in your organisation.

Learning Outcomes

  • Understand the basic concepts and benefits of data warehousing and how it integrates with BigQuery.
  • Navigate the BigQuery interface confidently to create and manage datasets.
  • Execute simple to complex queries to extract insights from large datasets.
  • Apply best practices in data exploration to identify trends and patterns.
  • Construct and manage virtual data models using views in BigQuery.
  • Visualise data effectively to communicate findings clearly.
  • Develop skills to optimise data queries to reduce costs and improve performance.
  • Gain practical experience through hands-on labs to build and refine SQL queries.
  • Learn to secure datasets and manage data access effectively.
  • Prepare for advanced topics in data analysis and warehouse management.

Who Is This Course For

This course is designed for data professionals, including analysts, engineers, and scientists, who wish to enhance their skills in managing and analysing large datasets using Google BigQuery. It is also suitable for IT professionals who are involved in data-driven decision making and are looking to adopt more efficient tools for data management and analysis.

Eligibility Requirements

This course is best suited for individuals with a basic understanding of databases and a keen interest in data analysis. Prior experience with SQL or any programming language will be beneficial but not mandatory. Enthusiasm for digging into data and transforming it into actionable insights is essential.

Entry Requirements

  • Age Requirement: Applicants must be 16 or older, making the course accessible to both young learners and adults.
  • Academic Background: No prior qualifications required, open to all backgrounds.
  • Language Proficiency: A good understanding of English is essential, as all lessons are in English.
  • Numeracy Skills: Basic writing and numeracy skills are needed to follow the course content.

Why Choose Us

  • Affordable, engaging & high-quality e-learning study materials;
  • Tutorial videos/materials from the industry-leading experts;
  • Study in a user-friendly, advanced online learning platform;
  • Efficient exam systems for the assessment and instant result;
  • The UK & internationally recognised accredited
  • Access to course content on mobile, tablet or desktop from anywhere, anytime;
  • The benefit of career advancement opportunities;
  • 24/7 student support via email.

Career Path

This course will ptovides participants with the skills to advance their careers in data analysis and data engineering.  Mastery of BigQuery opens doors to roles focused on big data solutions, business intelligence, and data warehousing projects. This course lays the foundation for further specialisation in machine learning and large-scale data processing roles.

Course Curriculum

Unit 01: Introduction
Section 01: Welcome to This Course 00:01:00
Section 02: How to Get Maximum Value from This Course 00:06:00
Section 03: Course Structure & Coverage 00:02:00
Section 04: Technology in This Course 00:02:00
Unit 02: Introducing Data Warehouse & BigQuery
Section 01: Data Warehouse 00:07:00
Section 02: Start With BigQuery 00:05:00
Section 03: BigQuery Web User Interface 00:04:00
Unit 03: First Exploration
Section 01: First Data 00:04:00
Section 02: Basic Exploration 00:16:00
Section 03: Functions 00:14:00
Section 04: Common Data Types 00:07:00
Section 05: Different Query 00:01:00
Section 06: Exploring Common Data Types 00:25:00
Section 07: Converting Data Types 00:07:00
Unit 04: Data Flow Basic
Section 01: Data Quality 00:06:00
Section 02: Clean & Transform 00:13:00
Section 03: Store Data 00:06:00
Section 04: Upgrading From Sandbox Account 00:01:00
Section 05: Clean & Transform With Dataprep 00:25:00
Section 06: Scheduled Query 00:04:00
Section 07: Analyze Data 00:05:00
Section 08: Data Visualization 00:06:00
Unit 05: Diving into BigQuery
Section 01: Essential BigQuery 00:15:00
Section 02: Load Data into BigQuery (Part 1) – The Basic 00:36:00
Section 03: Tip: Mock Data 00:01:00
Section 04: Load Data into BigQuery (Part 2) – Handling Errors 00:22:00
Section 05: Load Data into BigQuery (Part 3) – Efficient Load 00:14:00
Section 06: Load Data into BigQuery (Part 4) – From Your Data to BigQuery 00:23:00
Section 07: Load Data into BigQuery (Part 5) – In Microservice Architecture 00:20:00
Section 08: Tip: Message Broker Overview 00:08:00
Section 09: Load Data into BigQuery (Part 6) – Recurring Load 00:12:00
Unit 06: Virtual Data using View
Section 01: BigQuery View 00:06:00
Unit 07: Data Visualization
Section 01: What We Will Learn 00:01:00
Section 02: Google Sheets & BigQuery 00:10:00
Section 03: Google Data Studio 00:13:00
Unit 08: Intermediate Query
Section 01: Using Join – Theory 00:04:00
Section 02: Using Join – Hands On 00:16:00
Section 03: Union & Intersect 00:06:00
Section 04: Basic Statistical Functions 00:05:00
Assignment
Assignment – Exploring and Preparing your Data with BigQuery 00:00:00
Order Certificate
Order Certificate 00:00:00

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