 The SQL explorer supports full SQL syntax, letting you run advanced analyses directly within the platform.  You can build explorations from query results and use them alongside template-based explorations without switching tools.

SQL explorer overview

 To demonstrate the use of the SQL explorer for ad hoc analysis, consider a scenario in which you need to locate users who use the iOS platform along with their name and subscription ID.  To build such an exploration, follow these steps Go to + > SQL .

Build a SQL exploration

 The SQL Explorer UI has the following configurations Catalog Query Builder Visualization module The Catalog for an application is a repository of metadata objects arranged in folders.  Users can see portions of the Catalog based on their permissions.

Understand your SQL exploration

Create beelines from a retention chart

ai_cta

ai_identity

ai_chat

ai_product


Data set that refers to a person or a role and contains at least one address via which the person or role can receive messages.

recipient

analytics-docs

Analytics docs

Introduction to Optimizely Analytics

Product tour: UI overview

Quick start guide for Administrators

Terms and Concepts

Data security FAQ

Optimizely Opal Chat for Analytics

Getting Started

Get started with Warehouse-Native Experimentation Analytics

Experiment analysis

Create a connection

Create a decision dataset in Analytics

Create metrics

Conversion metric

Numeric aggregation metric

Ratio metric

Create an Experiment Scorecard in Optimizely Analytics

CUPED (Controlled-experiment Using Pre-Experiment Data)

Warehouse-Native Experimentation Analytics

Connect to data warehouses

Datasets

Data modeling in Analytics

Model Analytics entities

Event taxonomy

Curate nested JSON fields in dataset columns

Work with Data

Optimizely Analytics MCP server overview

Optimizely Analytics MCP server quickstart

Install Optimizely Analytics MCP server

Optimizely Analytics MCP server example prompts

Optimizely Analytics MCP server

Explorations

Exploration generation with Opal

Advanced Concepts

Drafts and Edits

Event Segmentation

Experiment Scorecard

Funnel

Impact

Influence

NetScript

Paths

Retention

Universal Exploration

Explore Data

Cohorts

Reusable metrics

Derived columns

Model Behavioral Semantics

Favorites

Compose with blocks

Types of blocks

Blocks

Dashboard overview

View and favorite dashboards

Supported tiles

Dashboard creation walkthrough

Agent Visibility Analytics dashboard in Optimizely Analytics

Dashboards

Visualization

Filtering

Aggregation functions

Segmentation

Parameters

Data Visualization and Filtering

Share and collaborate

Share and Collaborate

Alerting with rules

Alert inbox

Configuring Rules

Catalog

Actor lookup

Actor Lookup

Organization

Create and manage applications

User authentication

Application settings

Users and groups management

Authorization and access control

Administration

Glossary of terms

Reference

Analytics