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Nous allons étudier l'architecture interne de BigQuery (stockage segmenté basé sur des colonnes), ainsi que des concepts SQL avancés tels que les champs imbriqués et répétés, en utilisant pour cela des objets ARRAY et STRUCT. Pour finir, nous verrons comment optimiser les performances de vos requêtes et sécuriser vos données à l'aide des vues autorisées.
Une fois que vous aurez terminé ce cours, inscrivez-vous au cours ""Applying Machine Learning to Your Data with Google Cloud"".
Register for this course and see more details by visiting:
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What's inside
Syllabus
Introduction
Présentation des points abordés dans ce cours
Fonctions et clauses avancées
Approfondissez vos connaissances sur SQL dans BigQuery en apprenant des fonctions plus avancées, telles que les fonctions d'approximation statistique, les requêtes de fenêtrage analytique, les fonctions définies par l'utilisateur et les clauses WITH.
Read more
Syllabus
Introduction
Présentation des points abordés dans ce cours
Fonctions et clauses avancées
Approfondissez vos connaissances sur SQL dans BigQuery en apprenant des fonctions plus avancées, telles que les fonctions d'approximation statistique, les requêtes de fenêtrage analytique, les fonctions définies par l'utilisateur et les clauses WITH.
Read more
Conception de schémas et structures de données imbriquées
Découvrez comment les bases de données traditionnelles ont évolué pour s'adapter aux volumes des ensembles de données, et comparez cela avec la manière dont BigQuery a été conçu pour faire face aux limitations de scaling. Examinez en détail les champs imbriqués et répétés, qui sont des composants essentiels des structures de données BigQuery dénormalisées.
Optimiser les performances
Découvrez les opérations de base ayant un impact sur les performances de BigQuery et les moyens d'optimiser les requêtes pour qu'elles s'exécutent plus rapidement.
Insights avancés avec Vertex AI Workbench
Découvrez Vertex AI Workbench, un outil essentiel du kit pour les data scientists, qui favorise la collaboration entre analystes grâce à des notebooks cloud évolutifs.
Accès aux données
Toute organisation se doit d'assurer la sécurité des ensembles de données BigQuery et d'en faciliter le partage. Découvrez les outils Google Cloud et BigQuery mis à votre disposition pour gérer les autorisations et partager vos données.
Résumé du cours
Synthèse des points essentiels abordés durant le cours
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Ce cours s'appuie sur une base solide de SQL et explore les fonctions avancées, les schémas de données imbriqués et l'optimisation des performances, ce qui est standard dans l'industrie des données
Explore les fonctions avancées de SQL dans BigQuery, ce qui est utile pour les analystes de données qui souhaitent approfondir leurs connaissances SQL
Fournit des connaissances approfondies sur la conception et la structure des schémas de données imbriqués dans BigQuery, ce qui est essentiel pour gérer efficacement les ensembles de données volumineux
Enseigne les techniques d'optimisation des performances, aidant les apprenants à améliorer l'efficacité de leurs requêtes BigQuery, ce qui est crucial pour travailler avec de grands ensembles de données
Introduit Vertex AI Workbench, un outil collaboratif pour les data scientists, offrant des avantages pour les équipes travaillant sur des projets d'analyse de données
Fournit des moyens de gérer les autorisations et de partager des données dans BigQuery, ce qui est essentiel pour sécuriser et collaborer sur des ensembles de données sensibles
Save this course
Save Achieving Advanced Insights with BigQuery - Français to your list so you can find it easily later:
Save
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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 Achieving Advanced Insights with BigQuery - Français with these
activities:
Mentor junior SQL learners
Show steps
Solidify your knowledge by mentoring others and helping them grasp SQL concepts.
Show steps
-
Offer guidance and support to students or colleagues who are learning SQL
-
Review their SQL code and provide constructive feedback
-
Share your knowledge and experience in SQL community forums or events
Create SQL code snippets or tutorials
Show steps
Share your SQL knowledge and reinforce your own understanding by creating and publishing content.
Show steps
-
Write blog posts or articles on advanced SQL topics
-
Create and upload video tutorials on SQL functions and clauses
-
Contribute to open-source SQL projects or documentation
Review SQL basics
Show steps
Reinforce your SQL knowledge to prepare for the advanced SQL concepts covered in this course.
Browse courses on
SQL
Show steps
-
Review SQL SELECT statements and clauses
-
Practice writing SQL queries to extract data from sample databases
-
Test your understanding by solving SQL coding challenges
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in SQL study groups
Show steps
Engage with peers to discuss SQL concepts, solve problems, and share knowledge.
Show steps
-
Join online or in-person SQL study groups
-
Collaborate on SQL coding challenges and projects
-
Seek feedback and guidance from experienced SQL practitioners
Explore BigQuery architecture and data structures
Show steps
Gain a deeper understanding of BigQuery's architecture and data structures to optimize your query performance.
Show steps
-
Follow tutorials on BigQuery's columnar storage and data partitioning
-
Learn about nested and repeated fields, and how to query them effectively
-
Explore best practices for schema design and data modeling in BigQuery
Practice SQL functions and clauses
Show steps
Strengthen your understanding of advanced SQL functions and clauses through repetitive exercises.
Show steps
-
Work through guided tutorials on advanced SQL functions
-
Solve practice problems involving window functions, analytic functions, and user-defined functions
-
Participate in online SQL challenges or coding competitions
Volunteer for a data-driven organization
Show steps
Gain practical experience and apply your SQL skills in a real-world setting.
Show steps
-
Identify organizations that use data extensively and offer volunteer opportunities
-
Participate in data analysis projects or SQL-related tasks
-
Work with experienced data professionals and learn from their expertise
Build a SQL-based data visualization dashboard
Show steps
Apply your SQL skills to create an interactive dashboard that visualizes insights from your data.
Show steps
-
Choose a dataset and design a dashboard that meets specific business requirements
-
Write SQL queries to extract and transform data for visualization
-
Use a data visualization tool to create interactive charts and graphs
Mentor junior SQL learners
Show steps
Solidify your knowledge by mentoring others and helping them grasp SQL concepts.
Show steps
Show steps
Show steps
- Offer guidance and support to students or colleagues who are learning SQL
- Review their SQL code and provide constructive feedback
- Share your knowledge and experience in SQL community forums or events
Create SQL code snippets or tutorials
Show steps
Share your SQL knowledge and reinforce your own understanding by creating and publishing content.
Show steps
Show steps
Show steps
- Write blog posts or articles on advanced SQL topics
- Create and upload video tutorials on SQL functions and clauses
- Contribute to open-source SQL projects or documentation
Review SQL basics
Show steps
Reinforce your SQL knowledge to prepare for the advanced SQL concepts covered in this course.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review SQL SELECT statements and clauses
- Practice writing SQL queries to extract data from sample databases
- Test your understanding by solving SQL coding challenges
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in SQL study groups
Show steps
Engage with peers to discuss SQL concepts, solve problems, and share knowledge.
Show steps
Show steps
Show steps
- Join online or in-person SQL study groups
- Collaborate on SQL coding challenges and projects
- Seek feedback and guidance from experienced SQL practitioners
Explore BigQuery architecture and data structures
Show steps
Gain a deeper understanding of BigQuery's architecture and data structures to optimize your query performance.
Show steps
Show steps
Show steps
- Follow tutorials on BigQuery's columnar storage and data partitioning
- Learn about nested and repeated fields, and how to query them effectively
- Explore best practices for schema design and data modeling in BigQuery
Practice SQL functions and clauses
Show steps
Strengthen your understanding of advanced SQL functions and clauses through repetitive exercises.
Show steps
Show steps
Show steps
- Work through guided tutorials on advanced SQL functions
- Solve practice problems involving window functions, analytic functions, and user-defined functions
- Participate in online SQL challenges or coding competitions
Volunteer for a data-driven organization
Show steps
Gain practical experience and apply your SQL skills in a real-world setting.
Show steps
Show steps
Show steps
- Identify organizations that use data extensively and offer volunteer opportunities
- Participate in data analysis projects or SQL-related tasks
- Work with experienced data professionals and learn from their expertise
Build a SQL-based data visualization dashboard
Show steps
Apply your SQL skills to create an interactive dashboard that visualizes insights from your data.
Show steps
Show steps
Show steps
- Choose a dataset and design a dashboard that meets specific business requirements
- Write SQL queries to extract and transform data for visualization
- Use a data visualization tool to create interactive charts and graphs
Career center
Learners who complete Achieving Advanced Insights with BigQuery - Français will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, including finance, insurance, and healthcare. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Quantitative Analyst as it will help build a foundation in statistical analysis and modeling.
Data Scientist
Data Scientist
Data Scientists analyze data and provide data-driven solutions to business problems. Using machine learning algorithms and statistical modeling, they build predictive models, analyze data, and propose solutions. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful for someone who wants to become a Data Scientist as it will help build a foundation in data analysis and modeling.
Risk Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. They work in a variety of industries, including finance, insurance, and healthcare. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Risk Analyst as it will help build a foundation in data analysis and modeling.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve problems in a variety of industries, including transportation, manufacturing, and healthcare. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become an Operations Research Analyst as it will help build a foundation in statistical analysis and modeling.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They use statistical methods to understand the world around us and make predictions. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Statistician as it will help build a foundation in statistical analysis.
Data Architect
Data Architect
Data Architects are responsible for the design and management of data systems. They work with stakeholders to understand data requirements, design data models, and implement data solutions. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Data Architect as it will help build a foundation in data modeling and analysis.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become an Actuary as it will help build a foundation in statistical analysis and modeling.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts use data visualization tools to transform data into visual formats. They help businesses understand their data and make better decisions. The course teaches advanced SQL functions like statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Data Visualization Analyst as it will help build a foundation in data analysis and modeling.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful for someone who wants to become a Business Analyst as it builds a foundation in data analysis and increases their effectiveness in helping businesses understand their data.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make investment recommendations. They work with clients to understand their financial goals and develop investment strategies. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Financial Analyst as it will help build a foundation in data analysis and modeling.
Data Engineer
Data Engineer
Data Engineers are responsible for building and maintaining data pipelines. They wrangle data from disparate sources, prepare it for analysis, and ensure its quality. The course's focus on optimizing performance and handling complex data structures may be helpful to someone who wants to become a Data Engineer. Learning to maximize query performance is an important skill for a Data Engineer working with BigQuery.
Database Architect
Database Architect
Database Architects design, build, and maintain database systems. They require comprehensive understanding of data modeling, database management systems, and SQL. The course teaches advanced SQL functions like statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone looking to become a Database Architect as it builds a foundation in handling complex data structures and optimizing performance.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with stakeholders to understand requirements, design software solutions, and implement and test software. The course covers advanced SQL functions including statistical approximation, windowing analytics, and user-defined functions. This may be helpful to someone who wants to become a Software Engineer as it will help build a foundation in data analysis and modeling.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers apply machine learning algorithms to data to automate tasks and improve processes. They design, build, and evaluate machine learning models using statistical modeling, data analysis, and programming. The course's focus on building a foundation in SQL may be helpful to someone who wants to become a Machine Learning Engineer. Developing an understanding of data structures and query optimization can help fuel effective model development.
Data Analyst
Data Analyst
Data Analysts are tasked with extracting meaning out of data using statistical analysis, modeling, and visualization. They make descriptive and predictive models to help businesses make informed decisions. The course "Achieving Advanced Insights with BigQuery" may be useful to Data Analysts wanting to enrich their SQL knowledge and develop capabilities in optimizing query performance. This course also covers data security and access which are essential to a career as a Data Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/6pammp/achieving
Reading list
We've selected nine 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
Achieving Advanced Insights with BigQuery - Français.
Must-read for anyone who wants to learn about deep learning with Python. It provides a comprehensive overview of deep learning, including its history, algorithms, and applications.
Provides a comprehensive overview of cloud computing. It covers a wide range of topics, from cloud computing concepts and architecture to cloud security and governance. It valuable resource for anyone who wants to learn more about cloud computing or improve their skills in using cloud technologies.
Provides a practical introduction to data science for business professionals. It covers a wide range of topics, from data collection and analysis to model building and deployment.
Provides background and supports course material on storing, processing and querying large datasets on the Google Cloud Platform. It's especially useful for sections on BigQuery.
Ce livre fournit une introduction complète à l'analyse des données volumineuses, couvrant les principes, les applications et les études de cas.
Save
Ce livre fournit une introduction complète au data mining, couvrant les algorithmes, les techniques et les outils pour extraire des informations à partir de grands ensembles de données.
Ce livre fournit des conseils pratiques sur la façon de raconter des histoires avec des données, en utilisant des visualisations efficaces.
Save
Provides extensive coverage of the most popular NoSQL databases in the market, including MongoDB, Apache Cassandra, and Redis.
Ce livre fournit une introduction accessible à l'apprentissage automatique, en utilisant des termes simples et des exemples pratiques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/6pammp/achieving
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Français
Transcript
English
Good to know
Ce cours s'appuie sur une base solide de SQL et explore les fonctions avancées, les schémas de données imbriqués et l'optimisation des performances, ce qui est standard dans l'industrie des données
Explore les fonctions avancées de SQL dans BigQuery, ce qui est utile pour les analystes de données qui souhaitent approfondir leurs connaissances SQL
Fournit des connaissances approfondies sur la conception et la structure des schémas de données imbriqués dans BigQuery, ce qui est essentiel pour gérer efficacement les ensembles de données volumineux
Enseigne les techniques d'optimisation des performances, aidant les apprenants à améliorer l'efficacité de leurs requêtes BigQuery, ce qui est crucial pour travailler avec de grands ensembles de données
Introduit Vertex AI Workbench, un outil collaboratif pour les data scientists, offrant des avantages pour les équipes travaillant sur des projets d'analyse de données
Fournit des moyens de gérer les autorisations et de partager des données dans BigQuery, ce qui est essentiel pour sécuriser et collaborer sur des ensembles de données sensibles
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