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Google Cloud Training

This is a Google Cloud Self-Paced Lab. In this lab, you will learn how caching works in Looker and explore how to use LookML objects called datagroups to define caching policies.

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What's inside

Syllabus

Caching and Datagroups with LookML

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops caching policies in LookML, which is a common skill for data analysts
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Examines caching and datagroups, which are highly relevant to data analysis

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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 Caching and Datagroups with LookML with these activities:
Review previous LookML and SQL
Revisiting these concepts will lay the foundation for your success in caching policies.
Browse courses on LookML
Show steps
  • Review LookML documentation
  • Practice writing SQL queries
Review BigQuery SQL
This refresher will ensure you have a strong foundation in BigQuery SQL, which is essential for effective caching in Looker.
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  • Review BigQuery SQL documentation
  • Practice writing BigQuery SQL queries
Follow tutorials on Looker Caching
These tutorials will provide you with hands-on experience in implementing caching policies.
Show steps
  • Find relevant tutorials
  • Follow the tutorials step-by-step
  • Experiment with different caching policies
Five other activities
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Join a study group or online forum
Engaging with peers can provide valuable insights and perspectives on caching in Looker.
Browse courses on Caching
Show steps
  • Find a study group or forum
  • Attend meetings or participate in discussions
  • Share your knowledge and learn from others
Complete practice exercises on caching
These exercises will reinforce your understanding of caching concepts and their application in Looker.
Browse courses on Caching
Show steps
  • Download practice exercises
  • Work through the exercises
  • Review your answers
Write a blog post or article on caching
Creating content will deepen your understanding of caching and help you articulate its benefits and applications.
Browse courses on Caching
Show steps
  • Choose a topic
  • Write your blog post or article
  • Publish and promote your content
Build a Looker model with caching policies
This project will allow you to apply your knowledge of caching in a practical scenario.
Show steps
  • Design your Looker model
  • Implement caching policies using Datagroups
  • Test and refine your model
Create a personal caching project
Developing your own project will solidify your understanding of caching and its real-world applications.
Browse courses on Looker
Show steps
  • Brainstorm project ideas
  • Choose a dataset
  • Design and implement your caching solution
  • Evaluate and refine your solution

Career center

Learners who complete Caching and Datagroups with LookML will develop knowledge and skills that may be useful to these careers:
Business Intelligence Analyst
Business Intelligence Analysts are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. They use various tools and techniques to gather and analyze data, and then they present their findings to stakeholders. This course helps build a foundation for understanding how to use LookML to analyze data and derive insights that can be used to make business decisions.
Data Visualization Analyst
Data Visualization Analysts are responsible for creating data visualizations that communicate data in a clear and concise way. They work with data analysts and scientists to understand the data, and then they design and create visualizations that can be used to communicate insights and trends. This course helps build a foundation for understanding how to use LookML to analyze data and derive insights that can be used to create visualizations.
Big Data Analyst
Big Data Analysts work with large datasets to identify trends and patterns. They use a variety of big data tools and technologies to analyze data, and then they develop insights and recommendations to help businesses make informed decisions. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Analyst
Data Analysts seek to understand data to help companies make better informed business decisions. They use data to identify trends, patterns, and anomalies, and then they develop insights and recommendations to help businesses improve. This course may help someone in this role use Looker to analyze data and derive insights.
Data Scientist
Data Scientists use data to build models and predictions that can help businesses make better decisions. They use a variety of statistical and machine learning techniques to analyze data, and then they develop models that can be used to predict future outcomes. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights. It can also help build a foundation for understanding the underlying data structures and concepts behind modeling.
Data Lake Architect
Data Lake Architects design and manage data lakes. They work with data engineers and analysts to understand the data needs of the organization, and then they design and implement the data lakes that will meet those needs. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Architect
Data Architects are responsible for designing and managing the data architecture for an organization. They work with business stakeholders to understand the data needs of the organization, and then they design and implement the data systems that will meet those needs. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Engineer
Data Engineers are responsible for designing, building, and maintaining data systems. They work with data architects to understand the business requirements for data, and then they design and build the systems that will store and manage that data. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Quality Analyst
Data Quality Analysts are responsible for ensuring that data is accurate and complete. They work with data analysts and scientists to identify and fix data quality issues, and they develop and implement processes to ensure that data quality is maintained. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Warehouse Architect
Data Warehouse Architects design and manage data warehouses. They work with data engineers and analysts to understand the data needs of the organization, and then they design and implement the data warehouses that will meet those needs. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Data Governance Analyst
Data Governance Analysts are responsible for developing and implementing data governance policies and procedures. They work with business stakeholders to understand the data needs of the organization, and then they develop and implement policies and procedures to ensure that data is managed in a consistent and reliable way. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. They work with a variety of machine learning algorithms and techniques, and they are responsible for ensuring that machine learning models are accurate and reliable. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They ensure that databases are running smoothly and that data is secure. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with a variety of technologies and programming languages, and they are responsible for ensuring that software systems are reliable, efficient, and secure. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.
Cloud Architect
Cloud Architects design and manage cloud computing systems. They work with cloud providers to provision and manage cloud resources, and they are responsible for ensuring that cloud systems are reliable, scalable, and secure. This course may be useful for someone in this role who wants to develop a better understanding of how to use LookML to analyze data and derive insights.

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 Caching and Datagroups with LookML.
Provides a practical guide to using Redis, an open-source in-memory data structure store that can be used for caching. Its fit_score is 65.
Covers the fundamentals of big data analytics and provides insights into different techniques and tools, including caching. Its fit_score is 45.
Provides a foundational understanding of data warehousing concepts, which includes caching and data optimization techniques. Its fit_score is 30.
Provides a comprehensive guide to dimensional modeling, a data modeling technique often used in data warehousing, which can benefit from caching. Its fit_score is 25.
Provides an introduction to the concept of data mesh architecture, which emphasizes decentralized and self-serve data access, where caching plays a crucial role. Its fit_score is 5.

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