Becoming a proficient Looker Developer requires a combination of technical skills, business acumen, and hands-on experience. Looker Developers play a critical role in transforming raw data into actionable insights, building interactive dashboards, and collaborating with stakeholders to make data-driven decisions.
This 6-month roadmap will guide you step-by-step through the journey of mastering Looker, from learning the fundamentals to achieving advanced skills in LookML, SQL, and dashboard development. Whether you’re starting from scratch or looking to deepen your skills, this comprehensive plan will help you become a confident and skilled Looker Developer.
Month 1: Foundation in Data and BI Concepts
Goal: Understand the fundamentals of data analytics, business intelligence (BI), and Looker’s role in BI architecture.
Key Focus Areas:
- Introduction to Data Analytics: Start by understanding the importance of data in decision-making and the role of BI tools like Looker. Familiarize yourself with basic concepts such as data warehousing, ETL (Extract, Transform, Load) processes, and data modeling.
- Business Intelligence Overview: Learn how BI tools help businesses convert raw data into valuable insights. Explore the general BI landscape, understanding how Looker compares to other tools like Tableau and Power BI.
- Looker Fundamentals: Get an introduction to Looker’s interface, including data exploration, dashboard creation, and the structure of LookML (Looker Modeling Language).
Tasks:
- Study foundational concepts in data analytics and BI through free resources or online courses (e.g., Coursera, edX).
- Read Looker documentation to understand the platform’s basic functionalities.
- Explore Looker’s Explore feature and try building simple visualizations.
Resources:
- Looker Documentation: docs.looker.com
- Google Cloud Training Courses: Looker Fundamentals (Basic and Advanced)
Month 2: Mastering SQL
Goal: Become proficient in SQL, the foundational language for querying and manipulating databases.
Key Focus Areas:
- Introduction to SQL: SQL (Structured Query Language) is the backbone of any data analysis role. Learn the basics of SQL, including SELECT, WHERE, JOIN, GROUP BY, and HAVING statements.
- Database Management: Understand relational databases, data types, indexes, and how to optimize queries for performance.
- Advanced SQL: Dive deeper into SQL concepts, such as subqueries, window functions, and performance tuning.
Tasks:
- Practice writing SQL queries on datasets to retrieve, filter, and aggregate data.
- Explore complex SQL concepts such as window functions, nested queries, and optimizing query performance.
- Start using cloud-based databases such as Google BigQuery, Amazon Redshift, or Snowflake to get comfortable with cloud data environments.
Resources:
- SQLZoo: Free interactive SQL tutorials
- Mode Analytics SQL Tutorial
- Kaggle Datasets: Practice SQL on real-world datasets
End of Month 2 Goal:
By the end of Month 2, you should be comfortable writing SQL queries and optimizing them for efficient data retrieval. You should also have a solid understanding of relational databases and how they store and retrieve data.
Month 3: Introduction to LookML
Goal: Begin learning LookML, Looker’s modeling language, and understand how to build scalable data models.
Key Focus Areas:
- Understanding LookML: LookML is a high-level modeling language that abstracts SQL into reusable components like dimensions and measures. Begin by understanding the syntax and structure of LookML.
- Dimensions and Measures: Learn how to define dimensions (attributes or fields) and measures (aggregations like sum, average, count) in LookML.
- Joins and Explores: Understand how Looker uses LookML to define relationships between datasets using joins, and how users explore these datasets via Explores.
Tasks:
- Start building basic LookML models by defining dimensions and measures in a view file.
- Practice creating LookML models using your SQL skills from Month 2.
- Explore joins and relationships between different tables using LookML.
Example LookML Task:
- Create a View file for an “Orders” table, defining dimensions such as
order_id,customer_id,order_date, and measures liketotal_sales.
Resources:
- Looker Documentation on LookML: Learn how to define dimensions, measures, and joins.
- LookML Quickstart: Looker’s official guide to getting started with LookML.
End of Month 3 Goal:
By the end of Month 3, you should have built several LookML models, understand how to define dimensions and measures, and create basic joins between datasets. You should be able to navigate and explore LookML code confidently.
Month 4: Building Dashboards and Reports
Goal: Create interactive dashboards in Looker that provide actionable insights for business users.
Key Focus Areas:
- Creating Visualizations: Learn how to use Looker’s visualization tools to build charts, tables, and other graphical elements.
- Building Dashboards: Understand the process of creating multi-component dashboards, adding filters, and organizing visualizations to present data effectively.
- Drill-downs and Filtering: Add interactivity to your dashboards by allowing users to drill down into data and apply filters.
Tasks:
- Build dashboards that include bar charts, line graphs, heatmaps, and other visualizations.
- Incorporate filters that allow users to segment data by date, region, or category.
- Create drill-downs so users can explore granular data when needed (e.g., clicking on a total sales figure to see individual transactions).
Example Dashboard Task:
- Create a Sales Performance Dashboard that tracks monthly sales, top-selling products, and regional performance. Add filters to segment data by sales region and product category.
Resources:
- Looker Documentation on Dashboards: Learn how to create and customize dashboards.
- Looker Blocks: Pre-built templates and visualizations you can use for inspiration.
End of Month 4 Goal:
By the end of Month 4, you should be able to build fully functional dashboards with multiple visualizations and filters. You should also understand how to structure dashboards to make them intuitive and user-friendly for business stakeholders.
Month 5: Advanced LookML and Performance Optimization
Goal: Dive deeper into LookML, focusing on advanced features and optimizing performance for large datasets.
Key Focus Areas:
- Advanced LookML Concepts: Learn advanced LookML features such as derived tables, persistent derived tables (PDTs), and aggregate awareness.
- Query Optimization: Focus on performance optimization techniques to ensure dashboards and queries run efficiently, even with large datasets.
- Caching and Performance Tuning: Learn how Looker handles caching and how to leverage Persistent Derived Tables (PDTs) for pre-computing complex queries.
Tasks:
- Create derived tables in LookML to handle complex joins or calculations.
- Use PDTs to precompute results and improve performance for slow-running queries.
- Monitor and optimize query performance by reviewing SQL queries generated by LookML and identifying potential bottlenecks.
Example Task:
- Create a PDT that aggregates sales data by month and region, improving the performance of a sales dashboard that tracks historical trends.
Resources:
- Advanced LookML Guide: A deep dive into derived tables, PDTs, and caching strategies.
- SQL Performance Tuning: Learn tips for optimizing queries for large datasets.
End of Month 5 Goal:
By the end of Month 5, you should have a solid understanding of advanced LookML features and be capable of optimizing dashboards and queries for performance. You should also know how to use PDTs and derived tables to handle complex data needs.
Month 6: Integration, Collaboration, and Certification Preparation
Goal: Focus on integration, collaboration, and preparing for Looker certification.
Key Focus Areas:
- Looker API and Integration: Learn how to integrate Looker with other tools and platforms using the Looker API. This will enable you to automate reports, create custom workflows, and embed Looker dashboards into external applications.
- Collaboration and Version Control: Use Git and version control tools to collaborate with other developers on LookML projects.
- Looker Certified LookML Developer Preparation: Start preparing for the Looker Certified LookML Developer exam. Review key concepts, complete practice exams, and identify areas where you need further study.
Tasks:
- Write API scripts to automate tasks like sending scheduled reports or pulling data from Looker.
- Collaborate on LookML projects using Git for version control. Practice working in a team environment, managing changes to LookML models, and ensuring code quality.
- Begin studying for the Looker Certified LookML Developer exam, using resources like Looker’s documentation, practice tests, and study guides.
Example Task:
- Use the Looker API to embed a dashboard in an internal web application, allowing users to access key performance metrics without leaving the app.
Resources:
- Looker API Documentation: Learn how to interact with Looker programmatically.
- Looker Certification Guide: Official resources to help you prepare for certification.
- Git for LookML: A guide to using version control in Looker development.
End of Month 6 Goal:
By the end of Month 6, you should be comfortable integrating Looker with external systems, collaborating with other developers, and managing LookML projects using version control. You should also be ready to take the Looker Certified LookML Developer exam, having completed all necessary preparation.
Conclusion: Your Path to Becoming a Looker Developer
By following this 6-month roadmap, you’ll develop the skills needed to become a proficient Looker Developer. Each month focuses on a critical aspect of Looker development, from learning SQL and LookML to building dashboards and optimizing performance. This plan ensures a well-rounded understanding of the platform and prepares you for advanced responsibilities, including integration with other systems and team collaboration.
At the end of this journey, you’ll be ready to pursue the Looker Certified LookML Developer Certification, opening up a wide range of career opportunities in data analytics, business intelligence, and beyond.
Stay consistent, practice regularly, and you’ll find yourself mastering Looker in no time!