Analyzing and Visualizing Data in Looker (Coursera)

Offered by Google Cloud,
Analyzing and Visualizing Data in Looker (Coursera)

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

What You Will Learn

  • Use dimensions, measures, filters, and pivots to analyze and visualize data
  • Create advanced metrics instantaneously with table calculations
  • Create and share visualizations using Looks and dashboards
  • Utilize folders and boards in Looker to manage and organize content

Syllabus

WEEK 1
Introduction to the Course
This module introduces the course on Looker for business users and data analysts.
Introduction to Looker
This module provides an overview of the Looker user interface and its key components for data explorers.
Core Analytics Concepts
This module reviews the four core analytical concepts for analyzing and visualizing data in Looker.

WEEK 2
Table Calculations
This module reviews how business users and data analysts can use table calculations in Looker to instantenously create new metrics.
Looks and Dashboards
This module covers how to use Looks and dashboards to share visualizations and results with others.
Content Management
This module reviews how to manage and organize Looker content using folders and boards, so that content is easily discoverable and accessible by others.
Course Summary
This module provides a summary of the topics covered in this course.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Analysis and Interpretation of Large-Scale Programs (Coursera) Coursera
Johns Hopkins University

Analysis and Interpretation of Large-Scale Programs (Coursera)

This course is for implementers, managers, funders, and evaluators of health programs targeting women and children in low- and middle-income countries as well as undergraduate and graduate students in health-related fields. Course participants will learn how to 1) transform quantitative components of an evaluation measurement plan into a sound analysis plan to address the evaluation questions, 2) conduct quantitative analyses of primary or secondary surveys or other available data, 3) interpret the meaning of the analysis results and their implications, and 4) disseminate the evaluation findings to program implementers, local and global stakeholders.

Nov 16th 2026
5-12 Weeks
Fundamentos de Excel para Negocios (Coursera) Coursera
Universidad Austral

Fundamentos de Excel para Negocios (Coursera)

Cuando finalices este curso habrás logrado un gran número de habilidades como introducir información, ordenarla, manipularla, realizar cálculos de diversa índole (matemáticos, trigonométricos, estadísticos, financieros, ingenieriles, probabilísticos), extraer conclusiones, trabajar con fechas y horas, construir gráficos, imprimir reportes y muchas más.

Nov 9th 2026
5-12 Weeks
Landing.AI for Beginners: Build Data Visualization AI Models (Coursera) Coursera
Coursera Project Network

Landing.AI for Beginners: Build Data Visualization AI Models (Coursera)

In this 1-hour long project-based course, you'll step into the exciting field of Computer Vision and Generative AI using the LandingLens platform. We'll start by exploring the concept of visual prompting, and initiating a visual prompting project. LandingLens simplifies the model creation, training, and deployment process, making it a user-friendly platform for this endeavor.

Nov 16th 2026
1 Week
Statistical Thinking for Industrial Problem Solving, presented by JMP (Coursera) Coursera
SAS

Statistical Thinking for Industrial Problem Solving, presented by JMP (Coursera)

Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems.

Nov 16th 2026
5-12 Weeks
Data Visualization for Genome Biology (Coursera) Coursera
University of Toronto

Data Visualization for Genome Biology (Coursera)

The past decade has seen a vast increase in the amount of data available to biologists, driven by the dramatic decrease in cost and concomitant rise in throughput of various next-generation sequencing technologies, such that a project unimaginable 10 years ago was recently proposed, the Earth BioGenomes Project, which aims to sequence the genomes of all eukaryotic species on the planet within the next 10 years. So while data are no longer limiting, accessing and interpreting those data has become a bottleneck. One important aspect of interpreting data is data visualization. This course introduces theoretical topics in data visualization through mini-lectures, and applied aspects in the form of hands-on labs.

Nov 16th 2026
5-12 Weeks
Big Data Analysis with Scala and Spark (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Big Data Analysis with Scala and Spark (Coursera)

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.

Nov 9th 2026
4 Weeks
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Nov 9th 2026
4 Weeks