Requirements
- Basic understanding of tables, columns, and joins
- Comfort with Excel-level data concepts (filters, pivots are a plus)
- Basic SQL is helpful (we’ll guide you where needed)
- Laptop + stable internet connection
- Access to a sample dataset/warehouse (provided for practice)
- Willingness to do weekly hands-on assignments
Features
- Live Project-Based Training
- Expert-Led Sessions
- Flexible Learning Options
- Interactive Learning
- Comprehensive Study Material
- Globally Recognized Certification
- One-on-One Mentorship
Target audiences
- Data analysts and BI analysts
- MIS/Reporting professionals
- SQL developers moving into BI
- Data engineers supporting analytics teams
- Product analysts and growth analysts
- Finance/operations analysts building reports
- Freshers aiming for BI roles
- Teams migrating to Google Looker / governed BI
If you’re expected to deliver dashboards that match business numbers without constant fixing, our Looker Training in Noida at Ascents Learning is designed for that exact outcome. We focus on the real skill behind Looker—LookML modeling—so you can build a governed reporting layer that stays consistent across teams.
This Looker Training in Noida takes you from the basics of explores and looks to the work that matters in a job: creating views, writing dimensions and measures, setting up joins correctly (so counts don’t inflate), and using derived tables when business logic gets complex. On the delivery side, you’ll build dashboards with filters, drill-downs, scheduled deliveries, and alerts—so stakeholders can self-serve reports without depending on you for every update.
What you’ll learn in this Looker course
- Looker fundamentals: projects, content structure, explores, dashboards
- LookML: views, explores, joins, timeframes, measures
- Derived tables basics + modeling best practices
- Dashboard building: tiles, filters, drill paths, sharing & scheduling
- Validation, QA checks, and performance-friendly modeling tips
Who should join
Data analysts, MIS/reporting professionals, SQL developers, BI teams, and freshers in Noida who want strong BI fundamentals and portfolio-ready projects.
Curriculum
- 15 Sections
- 56 Lessons
- 22 Hours
Expand all sectionsCollapse all sections
- Module 1: Looker Basics + BI Workflow5
- 1.1What Looker is (semantic layer + governed BI)CopyCopyCopyCopyCopyCopyCopy
- 1.2Looker vs Looker Studio (where each fits)CopyCopyCopyCopyCopyCopyCopy
- 1.3Typical analytics workflow: warehouse → model → explore → dashboardCopyCopyCopyCopyCopyCopyCopy
- 1.4Key terms: Explore, View, Model, LookML, Dimensions, MeasuresCopyCopyCopyCopyCopyCopyCopy
- 1.5Tour Looker UI, open an Explore, run basic queries, save looksCopyCopyCopyCopyCopyCopyCopy
- Module 2: Setup, Projects, and Looker IDE5
- 2.1Looker instance structure, folders, spaces, content governanceCopyCopyCopyCopyCopyCopyCopy
- 2.2Looker Projects: why they matterCopyCopyCopyCopyCopyCopyCopy
- 2.3Looker IDE basics: files, folders, validation, content checkCopyCopyCopyCopyCopyCopyCopy
- 2.4Git connection basics (concept + workflow)CopyCopyCopyCopyCopyCopyCopy
- 2.5Create/open a project, run validation, fix simple errorsCopyCopyCopyCopyCopyCopyCopy
- Module 3: Connecting Data (Warehouse + Connections)4
- 3.1Connections: how Looker talks to DB/warehouseCopyCopyCopyCopyCopyCopyCopy
- 3.2Understanding schemas, tables, views in a warehouseCopyCopyCopyCopyCopyCopyCopy
- 3.3Connection best practices (naming, permissions, read-only users)CopyCopyCopyCopyCopyCopyCopy
- 3.4Test connection (demo environment), preview tables, identify keysCopyCopyCopyCopyCopyCopyCopy
- Module 4: LookML Foundations (Model + View + Explore)4
- Module 5: Dimensions & Measures That Make Sense4
- 5.1Dimension types: string, number, yesno, date/timeCopyCopyCopyCopyCopyCopyCopy
- 5.2Measures: count, sum, avg, count_distinctCopyCopyCopyCopyCopyCopyCopy
- 5.3Formatting, labels, value_format, group_labelCopyCopyCopyCopyCopyCopyCopy
- 5.4When to create measures vs calculations in ExploreCopyCopyCopyCopyCopyCopyCopy
- Module 6: Time Intelligence (Dates Done Properly)4
- Module 7: Joins & Relationships (Avoid Wrong Numbers)4
- 7.1Primary key, foreign key thinkingCopyCopyCopyCopyCopyCopyCopy
- 7.2Join types: left_outer, inner, full_outer (when to use)CopyCopyCopyCopyCopyCopyCopy
- 7.3Relationship parameter: one_to_one, one_to_many, many_to_oneCopyCopyCopyCopyCopyCopyCopy
- 7.4Fanout problem and how to catch itCopyCopyCopyCopyCopyCopyCopy
- Module 8: Explores That Users Love (Clean, Governed, Fast)4
- 8.1Explore design principles: default fields, hiding noiseCopyCopyCopyCopyCopyCopyCopy
- 8.2Field organization: group labels, views labelingCopyCopyCopyCopyCopyCopyCopy
- 8.3Always_filter, always_join, access_filter conceptsCopyCopyCopyCopyCopyCopyCopy
- 8.4Drill fields and link featuresCopyCopyCopyCopyCopyCopyCopy
- Module 9: Derived Tables (SQL Derived Table + PDT Intro)3
- Module 10: Reusable LookML Patterns (Write Less, Scale More)3
- Module 11: Building Dashboards (Not Just Pretty Tiles)4
- Module 12: Governance + Metric Definitions (Single Source of Truth)4
- 12.1Defining “Revenue”, “Active Users”, “Conversion” properlyCopyCopyCopyCopyCopyCopyCopy
- 12.2Avoiding duplicate metrics across teamsCopyCopyCopyCopyCopyCopyCopy
- 12.3Naming/label rules and documentation in LookMLCopyCopyCopyCopyCopyCopyCopy
- 12.4Content governance: spaces, folders, accessCopyCopyCopyCopyCopyCopyCopy
- Module 13: Access Control (Roles, Groups, Row-Level Control)4
- Module 14: Performance + QA (Make It Reliable)4
- Module 15: Capstone Project (End-to-End Delivery)0
FAQ
This course focuses on Google Looker (LookML + governed BI), not only Looker Studio.
Not strong, but basic SQL helps. We cover the SQL you’ll actually use in LookML work.
Yes—dashboards, explores, and a capstone delivery.
Yes, LookML is the core of the training.
Yes, if you’re comfortable with basic data concepts and ready for hands-on work.
Typical business reporting setups: sales, ops, support, or finance-style analytics.
Definitely—especially for modeling, governance, and performance decisions.
Yes—roles/groups basics and practical governance patterns.
We cover embedding concepts and common approaches (implementation depends on your stack).
You’ll be able to model data in LookML, publish governed explores, and ship dashboards confidently.
