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
Dubai teams move fast—dashboards get built quickly, but keeping numbers consistent across sales, finance, and operations is the real challenge. Our Looker Training in Dubai at Ascents Learning is designed to solve that exact problem by focusing on LookML, governed metrics, and production-style modeling.
In this Looker Training in Dubai, you’ll learn how Looker works end-to-end: connecting to a warehouse, building views and explores, writing dimensions and measures, and setting up joins correctly so your totals don’t inflate. We also cover derived tables for complex reporting, plus dashboard building with filters, drill-downs, scheduled deliveries, and alerts—so your reporting becomes self-serve for stakeholders.
The training is hands-on: weekly assignments, real business scenarios, and a capstone project where you deliver a complete Looker model + dashboard that can be shown in interviews.
What you’ll learn
- Looker fundamentals: projects, explores, content structure
- LookML modeling: views, explores, joins, measures, timeframes
- Derived tables basics and modeling best practices
- Dashboards: tiles, filters, drill paths, scheduling & sharing
- Validation and QA checks for accurate reporting
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)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 1.2Looker vs Looker Studio (where each fits)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 1.3Typical analytics workflow: warehouse → model → explore → dashboardCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 1.4Key terms: Explore, View, Model, LookML, Dimensions, MeasuresCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 1.5Tour Looker UI, open an Explore, run basic queries, save looksCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 2: Setup, Projects, and Looker IDE5
- 2.1Looker instance structure, folders, spaces, content governanceCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 2.2Looker Projects: why they matterCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 2.3Looker IDE basics: files, folders, validation, content checkCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 2.4Git connection basics (concept + workflow)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 2.5Create/open a project, run validation, fix simple errorsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 3: Connecting Data (Warehouse + Connections)4
- 3.1Connections: how Looker talks to DB/warehouseCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 3.2Understanding schemas, tables, views in a warehouseCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 3.3Connection best practices (naming, permissions, read-only users)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 3.4Test connection (demo environment), preview tables, identify keysCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 4: LookML Foundations (Model + View + Explore)4
- 4.1LookML file types and structureCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 4.2Model file: connection, includes, exploresCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 4.3View file: dimensions, measures, timeframesCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 4.4Explore: what users see and queryCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 5: Dimensions & Measures That Make Sense4
- 5.1Dimension types: string, number, yesno, date/timeCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 5.2Measures: count, sum, avg, count_distinctCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 5.3Formatting, labels, value_format, group_labelCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 5.4When to create measures vs calculations in ExploreCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 6: Time Intelligence (Dates Done Properly)4
- 6.1date vs datetime fieldsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 6.2timeframes and common reporting needsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 6.3Period comparisons basics (what’s possible + workarounds)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 6.4Handling fiscal calendars (approach + modeling hints)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 7: Joins & Relationships (Avoid Wrong Numbers)4
- 7.1Primary key, foreign key thinkingCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 7.2Join types: left_outer, inner, full_outer (when to use)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 7.3Relationship parameter: one_to_one, one_to_many, many_to_oneCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 7.4Fanout problem and how to catch itCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 8: Explores That Users Love (Clean, Governed, Fast)4
- 8.1Explore design principles: default fields, hiding noiseCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 8.2Field organization: group labels, views labelingCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 8.3Always_filter, always_join, access_filter conceptsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 8.4Drill fields and link featuresCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 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
- 11.1Looks vs Dashboards vs TilesCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 11.2Dashboard filters (field filters, filter-only fields)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 11.3Cross-filtering, drill-down workflowCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 11.4Layout + storytelling: what stakeholders expectCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 12: Governance + Metric Definitions (Single Source of Truth)4
- 12.1Defining “Revenue”, “Active Users”, “Conversion” properlyCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 12.2Avoiding duplicate metrics across teamsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 12.3Naming/label rules and documentation in LookMLCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 12.4Content governance: spaces, folders, accessCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 13: Access Control (Roles, Groups, Row-Level Control)4
- 13.1Roles & groups overviewCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 13.2Model access vs content accessCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 13.3Row-level security concepts (user attributes + access_filter)CopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 13.4Safe patterns for region/team-based data accessCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- Module 14: Performance + QA (Make It Reliable)4
- 14.1Query performance basics: what affects runtimeCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 14.2Caching behavior overviewCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 14.3Common modeling mistakes that slow queriesCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 14.4QA checklist: validation, content checks, testing totalsCopyCopyCopyCopyCopyCopyCopyCopyCopyCopy
- 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.
