Google Looker Practice Exam
The Google Looker exam assesses individuals' proficiency in utilizing the Looker platform for data visualization, business intelligence, and analytics. Looker, now part of Google Cloud, provides data exploration, visualization, and analytics capabilities to help organizations make data-driven decisions. This exam evaluates candidates' ability to design and build data models, create reports and dashboards, and analyze data insights using Looker's features and functionalities.
Skills Required
- Data Modeling: Proficiency in designing and building data models in Looker, including defining relationships, dimensions, measures, calculations, and aggregations for analyzing structured and unstructured data.
- Query Building: Ability to write SQL queries and LookML (Looker Modeling Language) code to extract, transform, and analyze data from multiple sources and databases using Looker's query builder and IDE.
- Report and Dashboard Creation: Skills in creating interactive reports, visualizations, and dashboards in Looker for presenting and sharing insights, trends, and KPIs with stakeholders and decision-makers.
- Data Visualization: Understanding of data visualization principles and best practices for designing effective charts, graphs, and visualizations in Looker to communicate complex data insights clearly and intuitively.
- Analytical Skills: Ability to analyze and interpret data using Looker's analytical tools, filters, and drill-down capabilities to identify trends, patterns, anomalies, and actionable insights from large datasets.
Who should take the exam?
- Data Analysts: Data analysts and business analysts interested in enhancing their skills in data visualization, analytics, and business intelligence using Looker for analyzing and interpreting data.
- Data Engineers: Data engineers and data architects responsible for designing and building data models, pipelines, and architectures using Looker for data visualization and analytics.
- Business Intelligence Professionals: Business intelligence professionals and BI developers looking to leverage Looker's features and functionalities for creating interactive reports, dashboards, and data visualizations.
- Data Scientists: Data scientists and analytics professionals interested in using Looker as a tool for exploratory data analysis, hypothesis testing, and model evaluation to derive actionable insights from data.
- Decision Makers: Executives, managers, and decision-makers seeking to understand and utilize Looker's capabilities for accessing, analyzing, and visualizing data to drive strategic decision-making and business outcomes.
Course Outline
The Google Looker exam covers the following topics :-
Module 1: Introduction to Looker
- Overview of Looker's features, benefits, and applications for data visualization, business intelligence, and analytics.
- Understanding Looker's architecture, data modeling approach, and integration with various data sources and databases.
Module 2: Looker Data Modeling
- Designing and building data models in Looker using LookML (Looker Modeling Language) for defining dimensions, measures, relationships, and calculations.
- Creating reusable model files, views, explores, and joins to organize and structure data for analysis and visualization.
Module 3: Looker Query Building
- Writing SQL queries and LookML code to extract, transform, and analyze data from multiple sources and databases using Looker's query builder and integrated development environment (IDE).
- Exploring Looker's query optimization techniques, query caching, and performance tuning for efficient data retrieval and analysis.
Module 4: Looker Reports and Dashboards
- Creating interactive reports, visualizations, and dashboards in Looker for presenting and sharing insights, trends, and key performance indicators (KPIs) with stakeholders.
- Customizing report layouts, formatting options, filters, and parameters to meet specific business requirements and user preferences.
Module 5: Data Visualization in Looker
- Understanding data visualization principles and best practices for designing effective charts, graphs, and visualizations in Looker to communicate complex data insights clearly and intuitively.
- Exploring Looker's visualization options, including bar charts, line charts, pie charts, scatter plots, heatmaps, and geospatial visualizations.
Module 6: Advanced Analytics in Looker
- Applying advanced analytics techniques in Looker for exploratory data analysis, hypothesis testing, trend analysis, and predictive modeling using statistical functions and machine learning algorithms.
- Leveraging Looker's analytical tools, filters, and drill-down capabilities to identify trends, patterns, anomalies, and actionable insights from large datasets.
Module 7: Looker Administration and Security
- Managing user access, permissions, and roles in Looker to ensure data security, governance, and compliance with organizational policies and regulations.
- Configuring Looker settings, permissions, authentication methods, and data access controls for maintaining data privacy and security.
Module 8: Looker Integration and Collaboration
- Integrating Looker with other tools, platforms, and data sources, including Google Cloud Platform (GCP), BigQuery, Google Sheets, Salesforce, and custom APIs for seamless data connectivity and collaboration.
- Collaborating with team members, sharing reports, and embedding Looker visualizations into third-party applications, websites, and portals for broader data accessibility and usage.
Module 9: Looker Best Practices and Optimization
- Reviewing best practices, optimization strategies, and performance tuning techniques for maximizing efficiency and performance in Looker data modeling, query building, and report creation.
- Learning how to optimize Looker configurations, dashboards, and queries for faster data processing, reduced latency, and improved user experience.
Module 10: Real-World Use Cases and Case Studies
- Exploring real-world use cases, case studies, and success stories of organizations using Looker for data visualization, business intelligence, and analytics across various industries and domains.
- Learning from practical examples, demonstrations, and hands-on exercises to apply Looker's features and functionalities to solve business challenges and achieve data-driven insights and outcomes.