Workflows and Features Overview
We’re focused on enabling you to master your enterprise data — from mapping your global business domains to building analytics products faster.
Modeling Your Enterprise Data
You now have the ability to manage and work with all three layers of data modeling on one platform.
Create Conceptual Models, Semantic Layer on the Fly
Efficiently capture your business reality with our enterprise-friendly ER diagrams. Define your entities, identify connections, and collaborate in real-time. Leverage Ellie's drag-and-drop capabilities for seamless model creation.
Our integrated Glossary links all data models, promoting an intuitive understanding of how data models from various business domains are interconnected.
Rely on Logical Data Models to Plan Physical Implementation
Craft detailed data structures on our logical data modeling canvas. Define primary and foreign keys, attributes, entities, and relationships.
Link logical entities with business glossary terms — enabling connections across your modeling layers. Automatically generate logical models from your conceptual
model designs, increasing efficiency and reducing potential errors.
Support for Building Collaborative Data Products Using Physical Models
You can arrive at a physical model from a conceptual model or logical model, bringing business needs and data products to one data management platform.
Link tables to entities in your organizational glossary. Once you have a physical model, you can generate a SQL presentation of the model. Implementing data products has never been easier.
Reverse Engineering Your Source Data for Faster Access
Data architects often find themselves in between operational data structures and analytics data structures. The goal is to model raw source data to suit analytics products.
But you have to have a way to understand your source, and the easiest way to do so is metadata and to identify connections.
With Ellie you can reverse engineer your source, visualize it as an ER diagram, and build analytics data models from it.
Version Control to Augment Your Data Models Over Time
Model versioning enables users to create and manage versions of their data models.
Save a version of your model to compare it with previous models to track changes. This provides better control over data models and fosters collaborative work within your team.
Plus, you save a version of a model as a new one, essentially creating a branch of the model.
Create Conceptual Models, Semantic Layer on the Fly
Efficiently capture your business reality with our enterprise-friendly ER diagrams. Define your entities, identify connections, and collaborate in real-time. Leverage Ellie's drag-and-drop capabilities for seamless model creation.
Our integrated Glossary links all data models, promoting an intuitive understanding of how data models from various business domains are interconnected.
Rely on Logical Data Models to Plan Physical Implementation
Craft detailed data structures on our logical data modeling canvas. Define primary and foreign keys, attributes, entities, and relationships.
Link logical entities with business glossary terms — enabling connections across your modeling layers. Automatically generate logical models from your conceptual
model designs, increasing efficiency and reducing potential errors.
Support for Building Collaborative Data Products Using Physical Models
You can arrive at a physical model from a conceptual model or logical model, bringing business needs and data products to one data management platform.
Link tables to entities in your organizational glossary. Once you have a physical model, you can generate a SQL presentation of the model. Implementing data products has never been easier.
Reverse Engineering Your Source Data for Faster Access
Data architects often find themselves in between operational data structures and analytics data structures. The goal is to model raw source data to suit analytics products.
But you have to have a way to understand your source, and the easiest way to do so is metadata and to identify connections.
With Ellie you can reverse engineer your source, visualize it as an ER diagram, and build analytics data models from it.
Version Control to Augment Your Data Models Over Time
Model versioning enables users to create and manage versions of their data models.
Save a version of your model to compare it with previous models to track changes. This provides better control over data models and fosters collaborative work within your team.
Plus, you save a version of a model as a new one, essentially creating a branch of the model.
Enterprise Data management
Enterprise data is more difficult, with every additional tool bringing less value. We’re hoping to make data management much easier for all enterprises.
Enterprise Models with Reusable, Connected Business Entities
Keep your enterprise terminology organized with Ellie’s comprehensive business glossary.
Track customizable metadata, attributes, and relationships across models with ease.
Link your entities to logical and physical models, enhancing comprehension and connecting business context with technical designs.
Map Business Domains with Folders, Sub-Glossaries
The folder structure starts with the 'organization' folder. You can have models and entities here that are widely applicable to your business.
Each folder within the organization can have subfolders. But the key to mapping domains is the ability for each folder to have its own dedicated glossary.
This gives you greater control over entity definitions and meanings within specific domains, projects, or teams.
Leverage Advanced Search for Faster Access to Entities
You can use custom search rules and filters to take advantage of custom metadata in Ellie, making it intuitive to find what you need in Ellie.
Ellie currently supports custom metadata for glossary entities. This is a functionality that we’ll soon add to other Ellie artifacts — collections
and models.
Enterprise Models with Reusable, Connected Business Entities
Keep your enterprise terminology organized with Ellie’s comprehensive business glossary.
Track customizable metadata, attributes, and relationships across models with ease.
Link your entities to logical and physical models, enhancing comprehension and connecting business context with technical designs.
Map Business Domains with Folders, Sub-Glossaries
The folder structure starts with the 'organization' folder. You can have models and entities here that are widely applicable to your business.
Each folder within the organization can have subfolders. But the key to mapping domains is the ability for each folder to have its own dedicated glossary.
This gives you greater control over entity definitions and meanings within specific domains, projects, or teams.
Leverage Advanced Search for Faster Access to Entities
You can use custom search rules and filters to take advantage of custom metadata in Ellie, making it intuitive to find what you need in Ellie.
Ellie currently supports custom metadata for glossary entities. This is a functionality that we’ll soon add to other Ellie artifacts — collections
and models.
Analytics Engineering Made Easy
Decipher source data using genAI, explore it visually using ER diagrams & prepare staging models twice as fast.
Making Sense of Your Source Data for Analytics Products
Analytics engineers often have to make assumptions about data.
Ellie’s structured workflow combines the speed of genAI and human input to “reverse engineer” your data warehouse.
Our AI agent then generates a description for each table and each column in the table.
You’ll always have a business expert who can understand the meaning of source data.
Using dbt or Github for analytics? Get a Head Start with Ellie
Ellie’s visual interface doesn't exist in isolation. You can push what you do in Ellie to dbt to create the "source" and "stage" layers of your dbt project.
Push your updates to your Github repository for a head start on your analytics project, with a clear understanding of source data.
All the documentation you need for your project is automatically created.
Decipher Your OBT (One Big Table), Make Data Discovery Faster
Most visual data analytics tools start at the business intelligence layer, missing opportunities for impactful data use.
We’re building a beta-stage rule-based engine to help analytics engineers and business analysts decode OBTs (One Big Table) layer by layer.
Each layer organizes attributes logically, supported by LLMs to generate metadata for deeper insights.
Making Sense of Your Source Data for Analytics Products
Analytics engineers often have to make assumptions about data.
Ellie’s structured workflow combines the speed of genAI and human input to “reverse engineer” your data warehouse.
Our AI agent then generates a description for each table and each column in the table.
You’ll always have a business expert who can understand the meaning of source data.
Using dbt or Github for analytics? Get a Head Start with Ellie
Ellie’s visual interface doesn't exist in isolation. You can push what you do in Ellie to dbt to create the "source" and "stage" layers of your dbt project.
Push your updates to your Github repository for a head start on your analytics project, with a clear understanding of source data.
All the documentation you need for your project is automatically created.
Decipher Your OBT (One Big Table), Make Data Discovery Faster
Most visual data analytics tools start at the business intelligence layer, missing opportunities for impactful data use.
We’re building a beta-stage rule-based engine to help analytics engineers and business analysts decode OBTs (One Big Table) layer by layer.
Each layer organizes attributes logically, supported by LLMs to generate metadata for deeper insights.
User Access Roles
Integrations & Open API Access
Plus, use our API to build connections with ease.
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