
Learn advanced data visualization using the two most popular visualization tools – Tableau and Google’s Looker
β±οΈ Length: 17.3 total hours
β 4.66/5 rating
π₯ 9,767 students
π September 2025 update
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Course Overview
- Dive deep into a strategic comparative analysis of two industry titans: Tableau and Google Looker. This course transcends basic feature demonstrations to explore the philosophical underpinnings and core architectures differentiating these powerful enterprise data visualization platforms.
- Understand their unique strengths and typical use-cases, enabling informed decisions on tool selection and implementation within diverse organizational structures.
- Explore real-world enterprise scenarios where each tool excels, covering data governance, scalability, user adoption, and integration with existing data ecosystems.
- Gain insights into how businesses leverage Tableau for agile exploration and Looker for robust, governed data applications, understanding their roles in modern data strategies.
- Uncover advanced deployment considerations, security protocols, and performance optimization techniques for enterprise-scale implementations.
- Analyze total cost of ownership, licensing, and long-term maintenance, equipping you for strategic IT and data infrastructure planning.
- Develop a nuanced perspective on data storytelling, harnessing distinct capabilities to communicate complex insights effectively.
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Requirements / Prerequisites
- A foundational understanding of data concepts, including databases, tables, columns, and data types, is highly recommended.
- Familiarity with basic analytical thinking and problem-solving approaches will enhance your learning experience.
- Access to a computer with a stable internet connection and sufficient processing power for running visualization software trials (Tableau Desktop trial, Google Looker access via browser).
- While not strictly mandatory, prior exposure to SQL or any programming language can be beneficial, especially for deeper dives into data modeling with Looker’s LookML.
- An eagerness to explore, experiment, and critically evaluate different approaches to data visualization and business intelligence.
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Skills Covered / Tools Used
- Advanced Data Architecture Understanding: Delve into Tableau’s direct query approach versus Looker’s LookML modeling layer, understanding their impact on data consistency, governance, and development workflows.
- Enterprise Deployment & Administration: Learn Tableau Server/Cloud administration, user management, and project organization, alongside Looker’s instance management, user roles, and content strategies.
- Performance Tuning & Optimization: Master techniques for optimizing dashboard performance in both Tableau (e.g., extracts, query optimization) and Looker (e.g., PDTs, query caching, model optimization).
- Data Governance & Security Best Practices: Implement robust data security at row and object levels in Tableau, and leverage Looker’s permission sets for data integrity and compliance.
- Strategic Tool Selection & Integration: Critically assess business requirements to recommend optimal visualization tools or hybrid approaches, considering data scale, user skills, and organizational culture.
- Advanced Data Storytelling & Presentation: Craft compelling narratives from both platforms, focusing on visual best practices, interactivity, and stakeholder-specific communication.
- Extensibility & API Integration: Explore functionality extension through Tableau’s extensions/API and Looker’s API for embedding and custom applications.
- Tools Used: Tableau Desktop, Tableau Cloud/Server, Google Looker platform (including LookML development environment), and various database connections (e.g., PostgreSQL, BigQuery).
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Benefits / Outcomes
- Become a Dual-Tool Expert: Emerge as a highly sought-after professional proficient in both Tableau and Google Looker, significantly enhancing your marketability in the competitive data analytics landscape.
- Drive Strategic Business Decisions: Leverage the distinct capabilities of each tool to generate deeper insights, enabling your organization to make more data-driven and impactful strategic choices.
- Lead Data Visualization Initiatives: Gain the confidence and expertise to lead complex data visualization projects, from initial data modeling and design to deployment and ongoing maintenance, using either platform.
- Optimize Enterprise BI Infrastructure: Acquire the knowledge to contribute to the design, optimization, and governance of your organization’s business intelligence infrastructure, ensuring efficiency and scalability.
- Enhance Data Culture & Adoption: Understand how to tailor visualization solutions to different user personas, fostering wider data literacy and encouraging greater adoption of analytical tools across your enterprise.
- Strategic Career Advancement: Position yourself for leadership roles in data analytics, business intelligence, or data product management, equipped with a comprehensive understanding of leading visualization technologies.
- Informed Technology Recommendation: Be able to confidently evaluate and recommend the most suitable visualization solution(s) for specific business challenges, backed by a thorough comparative analysis.
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PROS
- Provides a unique comparative perspective, allowing learners to understand the nuances and ideal use-cases for each powerful tool.
- Equips participants with dual expertise in the two most prominent enterprise-grade visualization platforms, a significant career advantage.
- Focuses on enterprise-level considerations, including governance, security, and scalability, preparing learners for real-world corporate challenges.
- The comprehensive 17.3-hour length allows for in-depth coverage without being overly long, ensuring practical and actionable knowledge.
- High student rating (4.66/5) and large enrollment (9,767 students) indicate strong course quality and learner satisfaction.
- The September 2025 update ensures the content is current with the latest features and industry best practices.
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CONS
- Effectively mastering two complex tools simultaneously requires a significant commitment of time, practice, and continuous application beyond the course material.
Learning Tracks: English,Office Productivity,Other Office Productivity
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