Achieving Advanced Insights with BigQuery
This specialization provides an in-depth exploration of Google BigQuery, a powerful cloud-based data warehouse. Learners will gain the skills to analyze large datasets, create complex queries, and develop insights to inform data-driven decisions. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
Deepen your knowledge of SQL on BigQuery by learning about more advanced functions
Walkthrough the evolution of how traditional databases handle dataset scale and compare how BigQuery was developed to address scaling limitations.
Learn the fundamental pieces of work that impact BigQuery performance and how to optimize your queries for speed.
Learn what Google Cloud and BigQuery tools are available to you to permission control and share your data.
(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
This course, Achieving Advanced Insights with BigQuery, provides an in-depth look at the more advanced functions of SQL on BigQuery. Participants will gain an understanding of how traditional databases handle dataset scale and how BigQuery was developed to address scaling limitations. They will also learn the fundamental pieces of work that impact BigQuery performance and how to optimize their queries for speed. Additionally, participants will be introduced to the Google Cloud and BigQuery tools available to them to permission control and share their data.
[Applications]
After completing this course, participants should be able to apply their knowledge of BigQuery to their own projects. They should be able to use advanced SQL functions to query and analyze large datasets, optimize their queries for speed, and use Google Cloud and BigQuery tools to permission control and share their data. Additionally, they should be able to identify the limitations of traditional databases and understand how BigQuery was developed to address them.
[Career Paths]
1. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines and data warehouses. They are also responsible for developing and deploying data models and algorithms to support data-driven decision-making. With the increasing demand for data-driven insights, the demand for Data Engineers is growing rapidly.
2. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover patterns and trends. They use a variety of techniques, such as machine learning, natural language processing, and statistical analysis, to extract insights from data. With the increasing demand for data-driven insights, the demand for Data Scientists is also growing rapidly.
3. Big Data Architect: Big Data Architects are responsible for designing and implementing data architectures that are optimized for scalability, performance, and cost. They are also responsible for developing and deploying data models and algorithms to support data-driven decision-making. With the increasing demand for data-driven insights, the demand for Big Data Architects is also growing rapidly.
4. Big Data Analyst: Big Data Analysts are responsible for analyzing large datasets to uncover patterns and trends. They use a variety of techniques, such as machine learning, natural language processing, and statistical analysis, to extract insights from data. With the increasing demand for data-driven insights, the demand for Big Data Analysts is also growing rapidly.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path focuses on the fundamentals of computer science, including programming, software engineering, and data structures. It also covers topics such as artificial intelligence, machine learning, and cloud computing. As BigQuery is a cloud-based data platform, this degree path is ideal for those looking to gain a deeper understanding of the technology. Additionally, the increasing demand for data-driven insights has made this degree path increasingly popular.
2. Master of Science in Data Science: This degree path focuses on the application of data science principles to solve real-world problems. It covers topics such as data mining, machine learning, and predictive analytics. As BigQuery is a powerful tool for data analysis, this degree path is ideal for those looking to gain a deeper understanding of the technology. Additionally, the increasing demand for data-driven insights has made this degree path increasingly popular.
3. Master of Science in Business Analytics: This degree path focuses on the application of analytics principles to solve business problems. It covers topics such as data mining, machine learning, and predictive analytics. As BigQuery is a powerful tool for data analysis, this degree path is ideal for those looking to gain a deeper understanding of the technology. Additionally, the increasing demand for data-driven insights has made this degree path increasingly popular.
4. Master of Science in Artificial Intelligence: This degree path focuses on the application of artificial intelligence principles to solve real-world problems. It covers topics such as machine learning, natural language processing, and computer vision. As BigQuery is a powerful tool for data analysis, this degree path is ideal for those looking to gain a deeper understanding of the technology. Additionally, the increasing demand for data-driven insights has made this degree path increasingly popular.
Course Syllabus
Advanced Functions and Clauses
Schema Design and Nested Data Structures
Optimizing for Performance
Advanced Insights with Vertex AI Workbench
Data Access
Pros & Cons
Good and informative content
Integrates BigQuery with Jupyter notebooks and Pandas
Excellent instructor
Useful practical course
Performance optimization
Arrays and Structs could be explained better
Audio quality was low
Instructor needs to speak up and slow down
Could have more difficult labs
Window functions have many options
Course Provider
Provider Coursera's Stats at AZClass
Discussion and Reviews
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