Analyzing and Visualizing Data with Looker Course Overview

Analyzing and Visualizing Data with Looker Course Overview

The Analyzing and Visualizing Data with Looker course is designed to empower learners with the skills to utilize Looker for data analysis and visualization effectively. This Looker course covers essential concepts from navigating the interface to leveraging core analytics concepts like dimensions, measures, filters, and pivots. Learners will delve into advanced features such as table calculations and offset functions, enabling them to create dynamic metrics on the fly.

Through interactive lessons, participants will learn to construct insightful dashboards, manage content, and organize reports to facilitate data-driven decision-making. The course also emphasizes practical skills for data delivery, ensuring that insights can be shared efficiently with stakeholders. By the end, those enrolled in this Looker training will be well-equipped to harness the full potential of Looker for robust data analysis and compelling visual storytelling.

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Course Fee 850
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850 (USD)
  • Live Training (Duration : 16 Hours)
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  • Live Training (Duration : 16 Hours)
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  • Classroom Training fee on request

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Course Prerequisites

To ensure the most effective learning experience in the Analyzing and Visualizing Data with Looker course, students should have the following minimum prerequisites:


  • Basic understanding of data analysis concepts such as dimensions, measures, and aggregations.
  • Familiarity with fundamental database concepts, including tables, relationships, and SQL queries.
  • Some experience with data visualization or business intelligence tools (prior experience with Looker is helpful but not mandatory).
  • Comfort with navigating web-based interfaces and applications.
  • An analytical mindset and the ability to think critically about data and how it can be used to support business decisions.

Please note that while these prerequisites are recommended, Koenig Solutions welcomes learners with various backgrounds and will provide the necessary support to help all participants succeed in the course.


Target Audience for Analyzing and Visualizing Data with Looker

The Analyzing and Visualizing Data with Looker course equips participants with key Looker skills for data-driven decision-making.


  • Data Analysts
  • Business Intelligence Professionals
  • Data Scientists
  • Business Analysts
  • Marketing Analysts
  • Product Managers
  • IT Professionals seeking to understand data visualization
  • Data-driven Decision Makers
  • Dashboard and Report Designers
  • Data Consultants
  • BI and Analytics Architects
  • Data Engineers (interested in visualization and analytics aspects)


Learning Objectives - What you will Learn in this Analyzing and Visualizing Data with Looker?

Introduction to the Course's Learning Outcomes and Concepts Covered:

The Analyzing and Visualizing Data with Looker course equips students with the skills to navigate Looker's interface, understand core analytics concepts, manage content, and create insightful dashboards for data-driven decision-making.

Learning Objectives and Outcomes:

  • Familiarize with the Looker interface and its components, understanding its capabilities for data analysis.
  • Navigate Looker to access different data points and functionalities effectively.
  • Comprehend and apply the four core analytical concepts in Looker: dimensions, measures, filters, and pivots.
  • Utilize dimensions to categorize and access various data attributes.
  • Employ measures to perform data aggregation and derive meaningful insights.
  • Analyze data subsets by applying filters to dimensions and measures.
  • Reorganize and group data for enhanced analysis using pivots.
  • Understand and implement table calculations and offset functions to create custom metrics and perform advanced data manipulations.
  • Create, customize, and manage interactive Looker dashboards for visualizing data and sharing insights with stakeholders.
  • Organize Looker content using folders and boards for improved navigability and content discoverability, facilitating efficient collaboration and reporting.

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