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Introduction to Data Analytics on Google Cloud

In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.

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What's inside

Syllabus

Course Introduction

This section welcomes learners to the Introduction to Data Analytics on Google Cloud course. In addition, this section introduces learners to the topics, concepts, and objectives of the course.

Understand the Data Analytics Lifecycle on Google Cloud

In this module, you receive a high-level introduction to a typical Google Cloud data analytics workflow, including what data sources and storage options are available, and examples of what types of data are best suited for data analysis versus machine learning training data.

Explore Data and Extract Insights by Using BigQuery

In this module, you receive a high-level introduction to BigQuery and its solution architecture, and use common SQL commands to locate specific data in BigQuery to answer a data-driven question.

Make Data-driven Decisions by Using Looker

In this module you learn the fundamentals of data exploration and visualization in Looker. In addition, you learn how to share data from Looker and Looker Studio.

Course Summary

This module reviews the topics covered in the course and provides resources for further learning.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores Google Cloud's data analytics workflow, its tools, and data sources

Builds a solid foundation in BigQuery, Looker, and Looker Studio

Meets the needs of beginners seeking to understand data analytics on Google Cloud

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Data Analytics on Google Cloud with these activities:

Review Intro to Data Analytics

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Reinforce pre-requisite knowledge and concepts related to data and data analysis.

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Review textbook and class notes to familiarize yourself with basic data analysis concepts
Revisit any online resources or tutorials covering entry-level data analysis

Data Visualization Practice Exercises

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Enhance data visualization skills and learn best practices for communicating data insights.

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Complete online exercises or tutorials on charting and graphing with Looker
Practice creating visualizations based on provided datasets

Data Analysis Case Study

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Apply data analysis techniques to solve a real-world problem and showcase your understanding.

Browse courses on Case Study Analysis

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Identify a realistic business problem that can be addressed with data analysis
Gather and preprocess data from available sources
Apply appropriate data analysis techniques to extract insights
Create a report or presentation to communicate your findings

Two other activities

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Dashboard for Data-Informed Insights

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Develop interactive dashboards to present data in a visually appealing and accessible manner.

Browse courses on Visualizing Data

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Design the layout and structure of your dashboard
Connect to data sources and configure visualizations
Implement user interface elements for interactivity and filtering
Deploy and share your dashboard with stakeholders

Kaggle Data Analysis Competition

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Test your skills against others and gain practical experience in solving complex data problems.

Browse courses on Kaggle Competition

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Identify an appropriate Kaggle competition
Gather and analyze the provided dataset
Apply advanced data analysis techniques to develop a solution
Submit your solution and compete for recognition and prizes

Career center

Learners who complete Introduction to Data Analytics on Google Cloud will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst is someone who uses data to help make informed decisions. They use their skills in data analysis to identify trends, patterns, and insights that can be used to improve business outcomes. This course can help you develop the skills you need to become a successful Data Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to communicate your findings to stakeholders in a clear and concise way.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist is someone who uses data to build predictive models and solve business problems. They use their skills in machine learning and statistics to develop models that can help businesses make better decisions. This course can help you develop the skills you need to become a successful Data Scientist by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to build and deploy predictive models using Google Cloud ML Engine.

See salaries and explore the career path for Data Scientist

Business Analyst

A Business Analyst is someone who uses data to help businesses understand their operations and make better decisions. They use their skills in data analysis and business process modeling to identify opportunities for improvement and develop solutions to business problems. This course can help you develop the skills you need to become a successful Business Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to use Google Cloud tools to build and deploy business process models.

See salaries and explore the career path for Business Analyst

Operations Analyst

An Operations Analyst is someone who uses data to help businesses improve their operational efficiency and effectiveness. They use their skills in data analysis and process improvement to identify opportunities for improvement and develop solutions to operational problems. This course can help you develop the skills you need to become a successful Operations Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to use Google Cloud tools to build and deploy process improvement plans.

See salaries and explore the career path for Operations Analyst

Financial Analyst

A Financial Analyst is someone who uses data to help businesses understand their financial performance and make investment decisions. They use their skills in data analysis and financial modeling to develop financial forecasts, analyze investment opportunities, and make recommendations to senior management. This course can help you develop the skills you need to become a successful Financial Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to use Google Cloud tools to build and deploy financial models.

See salaries and explore the career path for Financial Analyst

Marketing Analyst

A Marketing Analyst is someone who uses data to help businesses understand their customers and develop effective marketing campaigns. They use their skills in data analysis and marketing research to identify target markets, develop marketing strategies, and measure the effectiveness of marketing campaigns. This course can help you develop the skills you need to become a successful Marketing Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to use Google Cloud tools to build and deploy marketing campaigns.

See salaries and explore the career path for Marketing Analyst

Risk Analyst

A Risk Analyst is someone who uses data to help businesses identify and manage risks. They use their skills in data analysis and risk management to assess the likelihood and impact of risks, and develop strategies to mitigate those risks. This course can help you develop the skills you need to become a successful Risk Analyst by teaching you how to use Google Cloud tools to explore, analyze, and visualize data. You will also learn how to use Google Cloud tools to build and deploy risk management plans.

See salaries and explore the career path for Risk Analyst

Data Engineer

A Data Engineer is someone who designs, builds, and maintains data pipelines. They use their skills in data engineering and software development to develop data pipelines that can collect, process, and store data. This course can help you develop the skills you need to become a successful Data Engineer by teaching you how to use Google Cloud tools to build and deploy data pipelines. You will also learn how to use Google Cloud tools to manage data quality and data security.

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Machine Learning Engineer

A Machine Learning Engineer is someone who builds and deploys machine learning models. They use their skills in machine learning and software development to develop models that can learn from data and make predictions. This course can help you develop the skills you need to become a successful Machine Learning Engineer by teaching you how to use Google Cloud tools to build and deploy machine learning models. You will also learn how to use Google Cloud tools to manage model training and deployment.

See salaries and explore the career path for Machine Learning Engineer

Database Administrator

A Database Administrator is someone who manages and maintains databases. They use their skills in database administration and software development to ensure that databases are available, reliable, and secure. This course can help you develop the skills you need to become a successful Database Administrator by teaching you how to use Google Cloud tools to manage and maintain databases. You will also learn how to use Google Cloud tools to ensure data quality and data security.

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Data Architect

A Data Architect is someone who designs and manages data systems. They use their skills in data architecture and database design to develop data systems that can meet the needs of a business. This course can help you develop the skills you need to become a successful Data Architect by teaching you how to use Google Cloud tools to design and manage data systems. You will also learn how to use Google Cloud tools to ensure data quality and data security.

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Software Engineer

A Software Engineer is someone who designs, develops, and maintains software applications. They use their skills in software development and computer science to develop software applications that meet the needs of a business. This course can help you develop the skills you need to become a successful Software Engineer by teaching you how to use Google Cloud tools to develop and deploy software applications. You will also learn how to use Google Cloud tools to manage software quality and security.

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Cloud Engineer

A Cloud Engineer is someone who designs, builds, and maintains cloud infrastructure. They use their skills in cloud computing and software development to develop cloud infrastructure that can meet the needs of a business. This course can help you develop the skills you need to become a successful Cloud Engineer by teaching you how to use Google Cloud tools to design and build cloud infrastructure. You will also learn how to use Google Cloud tools to manage cloud security and cost.

See salaries and explore the career path for Cloud Engineer

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Data Analytics on Google Cloud .

Data Science from Scratch

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Provides a comprehensive overview of data analytics, from data collection and cleaning to data visualization and machine learning. The book is written in a clear and concise style, and it is suitable for beginners and experienced data analysts alike.

Data Science from Scratch: First Principles with...

Paperback

Data Science from Scratch: First Principles with...

Kindle Edition

Data Science from Scratch: First Principles with...

Paperback

Python for Data Analysis

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Provides a comprehensive overview of Pandas, a popular Python library for data analysis. The book covers all aspects of Pandas, from data loading and cleaning to data visualization and machine learning. The book also provides best practices for using Pandas for data analytics.

Python for Data Analysis

Paperback

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Python for Data Analysis

Kindle Edition

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Machine Learning Con Pytorch Y Scikit Lean

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Provides a comprehensive overview of machine learning with Python. It covers all aspects of machine learning, from data preparation and model selection to model evaluation and deployment. The book also provides best practices for machine learning in Python.

(Español) Machine Learning con PyTorch y Scikit-Learn:...

Paperback

$$$

The Data Science Handbook

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Provides a comprehensive overview of data science, from data collection and cleaning to data visualization and machine learning. The book is written in a clear and concise style, and it is suitable for beginners and experienced data scientists alike.

The Data Science Handbook: Advice and Insights from...

Paperback

R for Data Science

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Provides a comprehensive overview of data analysis using R, a popular programming language for data analysis and visualization. The book covers all aspects of data analysis using R, from data loading and cleaning to data visualization and machine learning. The book also provides best practices for data analysis using R.

R for Data Science: Import, Tidy, Transform,...

Paperback

(Deutsch) R für Data Science: Daten importieren, bereinigen,...

Kindle Edition

$$$

Learning Spark

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Provides a comprehensive overview of Apache Spark, a popular open-source distributed computing framework for big data. The book covers all aspects of Apache Spark, from data loading and processing to data visualization and machine learning. The book also provides best practices for using Apache Spark for big data analytics.

Learning Spark: Lightning-Fast Big Data Analysis

Paperback

Data Mesh

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Provides a comprehensive overview of the data mesh, a new approach to data management and data governance. The book covers all aspects of the data mesh, from its history and definition to its applications and challenges. The book also provides best practices for implementing a data mesh.

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Level

Introductory

Via

Coursera

Institution

Google Cloud

Instructor

Google Cloud Training

Language

English

Good to know

Explores Google Cloud's data analytics workflow, its tools, and data sources

Builds a solid foundation in BigQuery, Looker, and Looker Studio

Meets the needs of beginners seeking to understand data analytics on Google Cloud

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