Loading color scheme

Videos

YouTube


Semantic Modeling & Knowledge Graphs

Semantic View and the FactEngine Advantage

FactEngine and Boston provide a Semantic View over your Semantic Layer. Watch the FactEngine Advantage in action.

Relational Knowledge Graphs Explained

A dive into the theory behind Relational Knowledge Graphs. The relational-graph/graph-relational paradigm is cementing and this video explains Relational Knowledge Graphs to the uninitiated. More than a multi-model database that stores graph type data in JSON in some field in some table in a relational database, the Relational Knowledge Graph paradigm treats the whole database as if it were a graph database.

Schema-Aware Semantic Search with FactEngine

Natural Language Queries converted to Database Queries using FactEngine. FactEngine employs Schema-Aware Semantic Search to effect natural language queries over a database. Database query options include SQL, Cypher or TypeQL.

Relational Knowledge Graph - Beginning To End - Creating/querying a database using Boston/FactEngine

A video demonstrating the principals of a Relational Knowledge Graph. A knowledge graph is created, beginning to end, in Boston as a Property Graph Schema, creating the database at the same time. Data is added to the database and queried with FactEngine.

Semantic Search with FactEngine

Schema Aware Semantic Search with FactEngine described in detail. Natural Language Semantic Search (Schema Aware) is now available in FactEngine.

FactEngine And GPT3 - Natural Language Queries over your Database

FactEngine's unique query technology is exploited by marrying FactEngine with a LLM (Large Language Model), GPT3 (Generative Pretrained Transformer), to bring you best-in-class Natural Language to Database Query Language transformation, with FactEngine catering for SQL, Cypher or TypeQL.

Freeform Natural Language Queries in FactEngine

A video introducing Freeform Natural Language Queries in FactEngine, available to select customers now.

Boston FEKL Uploader (FactEngine Knowledge Language)

A video showing the new FactEngine Knowledge Language (FEKL) loader to automatically create an Object-Role Model in the Boston conceptual modelling software from a series of natural language FEKL statements.

FactEngine Introduction - Natural Language Queries over your database.

A brief introduction to FactEngine within Boston to do natural language queries over your database.

Metadata Storytelling Using AI - Object-Role Modeling and Boston

Metadata Storytelling overview of the structure and purpose of a conceptual model using artificial intelligence. Boston's October '23 release includes a Virtual Business Analyst that uses AI to provide narrative of a database. The same Virtual BA can be used to ask intelligent questions about the model in natural language.

Object-Role Modeling Made Easy. Learn Object-Role Modeling.

A crash course in Object-Role Modeling. Learn the fundamentals of Object-Role Modeling. =====Udemy Course - Mastering Object-Role Modeling======= Sign up to the Mastering Object-Role Modeling course on Udemy to speak with ORM professionals at their own level. https://www.udemy.com/course/master...

Programming The Large Language Model

Workflow Orchestration with the Observational State Machine (OSM). - AI orchestrated workflow for customer engagement, finance, health care, industry/manufacturing, legal, robotics. The OSM orchestrates workflows while performing RAG (Retrieval Augmented Generation), linear or non-linear workflow navigation while conforming to polices set established within the task set for the OSM. Workflows are defined using Pseudocode In JSON (PI-JSON) (C) Copyright Victor Morgante, implemented within tasks defined for the OSM. Legals: The OSM is the invention of Victor Morgante (FactEngine) and Julian Fransisco (Bloombox) and sold by FactEngine under licence. Please reach out to us if you require consumer/customer engaged workflow management within your organisation.


Aerospace and Object-Role Modeling

Aerospace & Object-Role Modeling

A video showing how Object-Role Modeling is used in the aerospace industry. Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity. Errata: Verbalisation read out should read: For each SubserviceType, exactly one of the following holds: - some StandardSubserviceType is that SubserviceType - some MissionSpecificSubserviceType is that SubserviceType

Aerospace And Object Role Modeling Pt 1

A video on the user of Object-Role Modeling in the Aerospace industry. Pt 2 at: https://www.youtube.com/watch?v=WHw... Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and is provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity.

Metadata Lineage in Boston

An introduction to Metadata Lineage in the Boston conceptual modelling software. Tracking the lineage of where the definition of model elements of your enterprise model emanates is an important process and tying it directly to your conceptual modelling tool of choice. Metadata Lineage empowers you to find the information you need to maintain your conceptual models. Metadata lineage includes the documentation and tracking of metadata of conceptual models to source documentation, such as cardinality rules and model element definitions. Throughout the lifecycle of a conceptual model Metadata Lineage enables quality data governance and understanding of your conceptual models. Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and is provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity.

Knowledge Extraction & Metadata Lineage with Fact Engine Knowledge Language

Watch how to do Knowledge Extraction and Metadata Lineage with Fact Engine Knowledge Language (FEKL). You'll see how to: 1. Dynamically load models into Boston using FEKL; 2. Metadata Lineage in Boston; 3. Knowledge Extraction in Boston;


Data Warehousing - Data Vault

Data Vault Schema Generation - Boston

Generating a Data Vault schema using the Boston conceptual modelling software, where a schema as either an Object-Role Model, Entity Relationship Diagram or Property Graph Schema is converted to a Data Vault schema.

Semantic Modelling for the Enterprise

A video showing Enterprise Modeling under the new paradigm of relational knowledge graphs and graph/relational paradigm. FactEngine Knowledge Language (FEKL) plays a key role in the Boston conceptual modelling software and FactEngine. The modern data layer is a Semantic View, providing a business language view over your data warehouse/lake along side traditional Entity Relationship Diagram and Property Graph Schem views. Links ================= Knowledge Extraction and Metadata Lineage: https://youtu.be/0tg5MeAF04w?si=11q... Keyword Extraction: https://youtu.be/AgcJvHIWiuI?si=Hyi... Derivations: Derivations containing basic math functions are implemented in Boston/FactEngine. We are currently working on more advanced functions/date-functions.


Object-Role Modeling

 

Creating An Object-Role Model with Boston

Creating and Object-Role Model in the Boston conceptual modeling software.

Boston Generating Documentation from Object-Role Models

A video showing how to generate Microsoft Word documentation of a model stored in the Boston conceptual modelling software. Object-Role Modeling is renowned for the 'verbalisation' of models in natural language. This can be exploited to generate documentation of a model for review and sign-off by stakeholders for model development.

Rapid Fact Type & Keyword Extraction Using GPT3

A video showing how to exploit a large language model (LLM) atificial intelligence (AI) to do Keyword Extraction and to find Fact Types within a document.

Derived Fact Types and Computed Columns

A look at Derived Fact Types in Object-Role Modeling and Computed Columns in database tables/node types.

Boston FEKL Uploader (FactEngine Knowledge Language)

A video showing the new FactEngine Knowledge Language (FEKL) loader to automatically create an Object-Role Model in the Boston conceptual modelling software from a series of natural language FEKL statements.

Boston - Selecting A FactType

How to select a Fact Type in the Boston Object-Role Modeling software.

Highlighting/Selecting a Fact Type in Boston

A video showing how to select a Fact Type in an Object-Role Model view in the Boston conceptual modelling software.

Fact Type Readings - Part 1

This video describes how to establish Fact Type Readings on Fact Types within an Object Role Model using the Boston conceptual modelling tool.

Creating A Fact Type Using The Toolbox in Boston

This video shows how to create a Fact Type using the Toolbox in Boston v2.8

Creating Fact Types In Boston

This video demonstrates the various ways to create Fact Types within the Boston conceptual modelling tool. Boston is a Fact-Based Modelling tool based on ORM (Object-Role Modelling)

Fact Type Readings in Boston

This video demonstrates how to create a Fact Type Reading for a Fact Type in Boston.

Object-Role Modelling - Internal Uniqueness Constraints / Objectification

This video demonstrates how to create Internal Uniqueness Constraints against Fact Types in Boston. The video also shows how to Objectify a Fact Type in Boston.

Boston - Frequency Constraints - Object-Role Modelling

Frequency Constraints in Object-Role Modelling described.

Metadata Storytelling Using AI - Object-Role Modeling and Boston

Metadata Storytelling overview of the structure and purpose of a conceptual model using artificial intelligence. Boston's October '23 release includes a Virtual Business Analyst that uses AI to provide narrative of a database. The same Virtual BA can be used to ask intelligent questions about the model in natural language.

Object-Role Modeling Made Easy. Learn Object-Role Modeling.

A crash course in Object-Role Modeling. Learn the fundamentals of Object-Role Modeling. =====Udemy Course - Mastering Object-Role Modeling======= Sign up to the Mastering Object-Role Modeling course on Udemy to speak with ORM professionals at their own level. https://www.udemy.com/course/master...


FactEngine All

91 videos 7273 views 71 subscribers
FactEngine

Programming The Large Language Model

Workflow Orchestration with the Observational State Machine (OSM). - AI orchestrated workflow for customer engagement, finance, health care, industry/manufacturing, legal, robotics. The OSM orchestrates workflows while performing RAG (Retrieval Augmented Generation), linear or non-linear workflow navigation while conforming to polices set established within the task set for the OSM. Workflows are defined using Pseudocode In JSON (PI-JSON) (C) Copyright Victor Morgante, implemented within tasks defined for the OSM. Legals: The OSM is the invention of Victor Morgante (FactEngine) and Julian Fransisco (Bloombox) and sold by FactEngine under licence. Please reach out to us if you require consumer/customer engaged workflow management within your organisation.

Semantic Modelling for the Enterprise

A video showing Enterprise Modeling under the new paradigm of relational knowledge graphs and graph/relational paradigm. FactEngine Knowledge Language (FEKL) plays a key role in the Boston conceptual modelling software and FactEngine. The modern data layer is a Semantic View, providing a business language view over your data warehouse/lake along side traditional Entity Relationship Diagram and Property Graph Schem views. Links ================= Knowledge Extraction and Metadata Lineage: https://youtu.be/0tg5MeAF04w?si=11q... Keyword Extraction: https://youtu.be/AgcJvHIWiuI?si=Hyi... Derivations: Derivations containing basic math functions are implemented in Boston/FactEngine. We are currently working on more advanced functions/date-functions.

Boston Configuration File Access

A video on how to access the Boston configuration file. Security permissions apply if when running Boston through a browser on an intranet/extranet or the internet.

Jupyter Notebooks over an Intranet, Extranet or the Internet

A brief video showing how to run a Jupyter Notebook over an Intranet, Extranet or the Internet. Work with FactEngine for setting up security for your Jupyter Notebook implementation.

Object-Role Modeling Made Easy. Learn Object-Role Modeling.

A crash course in Object-Role Modeling. Learn the fundamentals of Object-Role Modeling. =====Udemy Course - Mastering Object-Role Modeling======= Sign up to the Mastering Object-Role Modeling course on Udemy to speak with ORM professionals at their own level. https://www.udemy.com/course/master...

Data Vault - Advanced Topics in Boston & FactEngine

How Boston and FactEngine reintroduce the Business Vault to a Data Vault

FactEngine And FactEngine Query Language (FEQL). Natural Language Queries.

A quick video on FactEngine and the FactEngine Query Language, FEQL. Natural Language and Controlled Natural Language queries over your database.

Knowledge Extraction & Metadata Lineage with Fact Engine Knowledge Language

Watch how to do Knowledge Extraction and Metadata Lineage with Fact Engine Knowledge Language (FEKL). You'll see how to: 1. Dynamically load models into Boston using FEKL; 2. Metadata Lineage in Boston; 3. Knowledge Extraction in Boston;

Metadata Storytelling Using AI - Object-Role Modeling and Boston

Metadata Storytelling overview of the structure and purpose of a conceptual model using artificial intelligence. Boston's October '23 release includes a Virtual Business Analyst that uses AI to provide narrative of a database. The same Virtual BA can be used to ask intelligent questions about the model in natural language.

Metadata Lineage in Boston

An introduction to Metadata Lineage in the Boston conceptual modelling software. Tracking the lineage of where the definition of model elements of your enterprise model emanates is an important process and tying it directly to your conceptual modelling tool of choice. Metadata Lineage empowers you to find the information you need to maintain your conceptual models. Metadata lineage includes the documentation and tracking of metadata of conceptual models to source documentation, such as cardinality rules and model element definitions. Throughout the lifecycle of a conceptual model Metadata Lineage enables quality data governance and understanding of your conceptual models. Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and is provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity.

openCypher Over Any Relational Database = Mindful

FactEngine's new MindfulDB offering is tooling for openCypher queries over any relational database, restricted to read-only and no metagraph queries at this stage. Turn any relational database schema into a property-graph schema and run openCypher queries against it. No requirement for special node and/or edge tables...take your existing relational database schema, just the way it is, and run open standard graph queries against your existing database. Watch as FactEngine explains why this is a zero risk offering over your existing database/data -warehouse and/or semantic layer.

The FactEngine Advantage

The FactEngine Advantage brings to you: - Rapid deployment; - A great idea; - Data governance process continuity; - Flexibility; - Business Intelligence at the cutting edge; and - Cost savings and reasonable pricing.

Boston running on PostgreSQL

A video demonstating Boston running over PostgreSQL database. Corporate customers can serve their conceptual models via an enterprise class database, both over the cloud and to the desktop. Speak to FactEngine for more details.

Relational Knowledge Graphs Explained

A dive into the theory behind Relational Knowledge Graphs. The relational-graph/graph-relational paradigm is cementing and this video explains Relational Knowledge Graphs to the uninitiated. More than a multi-model database that stores graph type data in JSON in some field in some table in a relational database, the Relational Knowledge Graph paradigm treats the whole database as if it were a graph database.

Boston - Model Database Options

Boston - Model database options, where clients have specific database requirements beyond the standard MS Jet datase Boston ships with. V7.0 (June 2023) Release - Boston will support SQLite, and beyond June FactEngine will be releasing Boston over Postgres, ORACLE and SQL Server. Please contact FactEngine for your custom database needs for Boston model storage. Delivery dates may vary.

Aerospace And Object Role Modeling Pt 1

A video on the user of Object-Role Modeling in the Aerospace industry. Pt 2 at: https://www.youtube.com/watch?v=WHw... Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and is provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity.

Aerospace & Object-Role Modeling

A video showing how Object-Role Modeling is used in the aerospace industry. Legals: Images under license. This video affirms no working relationship or endorsement of, for or by any other person or entity and provides the opinions of FactEngine, Australia, only. Any and all logo use here under fair use legislation, and/or as happenstance of presenting commentary, and in no way implies endorsement of, for or by any entity. Errata: Verbalisation read out should read: For each SubserviceType, exactly one of the following holds: - some StandardSubserviceType is that SubserviceType - some MissionSpecificSubserviceType is that SubserviceType

Rapid Fact Type & Keyword Extraction Using GPT3

A video showing how to exploit a large language model (LLM) atificial intelligence (AI) to do Keyword Extraction and to find Fact Types within a document.

Earhart Document Search & Query - Explanatory Video

A video introducing and showcasing the Earhart Document Search & Query tool.

Data Vault Schema Generation - Boston

Generating a Data Vault schema using the Boston conceptual modelling software, where a schema as either an Object-Role Model, Entity Relationship Diagram or Property Graph Schema is converted to a Data Vault schema.

Derived Fact Types and Computed Columns

A look at Derived Fact Types in Object-Role Modeling and Computed Columns in database tables/node types.

Semantic View and the FactEngine Advantage

FactEngine and Boston provide a Semantic View over your Semantic Layer. Watch the FactEngine Advantage in action.

FactEngine Natural Language Query API

The FactEngine Natural Language API (Web-Focused), available now for your ChatGPT PlugIn development. Convert natural language queries to SQL, Cypher or TypeQL via an API to hook into your ChatGPT Plugin or your online Business Intelligence (BI) tool. NB FactEngine for Neo4j is in Beta.

Research - Ambiguity, Metalogic and Object-Role Modeling.

A general discussion on ambiguity and Object-Role Modeling with a focus on ORM and metalogic and a proposed ORM signature under formal logic. Jump to NORMA view of the problem: https://youtu.be/vT71CblEGuQ?t=7127 Read about the counterexample and the metalogical implications on Medium: https://victormorgante.medium.com/o... FactEngine's position on a Logical Signature of Object-Role Modeling: https://www.youtu.be/vT71CblEGuQ&t=... Files: Boston and NORMA files of the ORM diagram discussed in this video at: https://github.com/FactEngineCommun... Ehrenfeucht Fraisse Games and the Object-Role Modeling metamodel/signature: https://youtu.be/vT71CblEGuQ?t=3804 4-Layer Architecture and the Metamodel of Object-Role Modeling: https://youtu.be/vT71CblEGuQ?t=6486 Ratifying the Object Management Group's (OMG's) 4-Layer Architecture. Errata: KL for total internal uniqueness constraint over a binary fact type should read: ∀S ∀x ∀y [(x,y) ∈ S ∧ ∀z [(z,y) ∈ S → z = x] ∧ ∀w [(x,w) ∈ S → w = y] → x = y]

Creating An Entity-Relationship Diagram in Boston

Creating and Entity-Relationship Diagram in the Boston conceptual modelling software. Learn how to create an ERD in Boston and convert it to an Object-Role Model and/or Propery-Graph Schema

Creating An Object-Role Model with Boston

Creating and Object-Role Model in the Boston conceptual modeling software.

The FactEngine Architecture - Schema-Aware Semantic Search

A video describing the FactEngine architecture to effect Schema-Aware Semantic Search over your data store.

Schema-Aware Semantic Search with FactEngine

Natural Language Queries converted to Database Queries using FactEngine. FactEngine employs Schema-Aware Semantic Search to effect natural language queries over a database. Database query options include SQL, Cypher or TypeQL.

Semantic Search with FactEngine

Schema Aware Semantic Search with FactEngine described in detail. Natural Language Semantic Search (Schema Aware) is now available in FactEngine.

FactEngine And GPT3 - Natural Language Queries over your Database

FactEngine's unique query technology is exploited by marrying FactEngine with a LLM (Large Language Model), GPT3 (Generative Pretrained Transformer), to bring you best-in-class Natural Language to Database Query Language transformation, with FactEngine catering for SQL, Cypher or TypeQL.

Engaging Superuser Mode in Boston

A video on how to engage Superuser Mode in the Boston conceptual modelling software. NB Use Superuser Mode with caution and only on advice of FactEngine.

Uploading Configuration/Reference Tables in Boston

A video demonstrating how to upload Configuration/Reference Table data into the Boston conceptual modelling software.

Freeform Natural Language Queries in FactEngine

A video introducing Freeform Natural Language Queries in FactEngine, available to select customers now.

Boston FEKL Uploader - Pages

Automatic creation of Pages using Controlled Natural Language within the FEKL (FactEngine Knowledge Language) Uploader in the Boston conceptual modelling software, when creating an Object-Role Model using controlled natural language.

Boston FEKL Uploader (FactEngine Knowledge Language)

A video showing the new FactEngine Knowledge Language (FEKL) loader to automatically create an Object-Role Model in the Boston conceptual modelling software from a series of natural language FEKL statements.

Highlighting/Selecting a Fact Type in Boston

A video showing how to select a Fact Type in an Object-Role Model view in the Boston conceptual modelling software.

General Concepts in Boston

Creating General Concepts in Boston which can later then be converted into either an Entity Type or a Value Type to suit your Object-Role Model.

Use Case Diagrams & Object-Role Modeling - Genuine Unified Modelling

Use Case Diagrams introduced in Boston in the July '22 release. This represents the first time process and data modelling have been unified under a common metamodel of object-role modelling and in a commercial product. Process modelling married to Object-Role Modeling has been the holy grail of the Object-Role Modeling community for over 10 years. 4-Layer architecture dates its promotion back to the early 2000s. Now both are real and FactEngine feels our customers will love it!

Property Graph Schema to Object-Role Model - Automatic Schema Conversion

A video of the Boston conceptual modelling software automatically converting a- Property Graph Schema to an Object-Role Model and an Entity-Relationship Diagram. Do you model in Boston as a Property Graph Schema and then convert to ORM or an ERD. Boston's polyglot modelling is made for the new wave of Relational Knowledge Graphs and where graph databases are increasingly supporting features more commonly found in relational databases.

Relational Knowledge Graph - Beginning To End - Creating/querying a database using Boston/FactEngine

A video demonstrating the principals of a Relational Knowledge Graph. A knowledge graph is created, beginning to end, in Boston as a Property Graph Schema, creating the database at the same time. Data is added to the database and queried with FactEngine.

Controlled Natural Language Queries over a Neo4j database. Neo4j & FactEngine.

FactEngine and Boston will allow natural language queries over a Neo4j database in the v6.2.3 release in June 2022. Boston enables a polyglot semantic layer over your knowledge graph database and then generate Cypher, SQL or TypeDB queries from the controlled natural language of FactEngine. This demonstration cements Object-Role Modeling's place in polyglot modelling, allowing Property Graph Schema and Relational Shema views over your knowledge graph. Stay tuned for more announcements.

Keyword Extraction Tool in the Boston Conceptual Modelling Tool

New to Boston v6.2 is a keyword extraction tool that can be used to extract keywords from a corpus saved as a text (.txt) file. This tool is helpful to find keywords that may become Entity Types or Value Types within your conceptual model, and where Entity Types can later be converted to Fact Types if necessary.

Boston NORMA File Loading - Model Errors

When loading NORMA .orm files into the Boston conceptual modelling software, Boston aims to compensate for errors in the NORMA .orm file. This is the process taken to load such files. Functionality from v6.1 and above.

Boston CRUD Operations - Database Data View

A video introducing the CRUD/Data Management functionality in the Boston conceptual modelling software. Data Management is limited to a few databases at this stage. More database will be added over time.

Boston - Loading a NORMA .orm file and storing As XML

In Boston, and for large models, it can be more convenient to store the model as XML. This makes loading and saving the model quicker. This video shows loading a large model into Boston (v6.0 upgrade) from a NORMA .orm file, and storing the loaded model as XML.

Boston - Selecting A FactType

How to select a Fact Type in the Boston Object-Role Modeling software.

Boston Code Generator - TypeDB Schema Export

A video on how to export a TypeDB define/schema statement for a model in the Boston conceptual modelling software.

Importing NORMA .orm Files into Boston

A video showing how to import NORMA .orm Object-Role Modeling files into the Boston conceptual modelling software. New to version 6.0 of Boston

Boston / TypeDB - Naming Correlation

TypeDB requires Entity, Relation and Attribute names to be in the correct case within TypeDB queries. This video shows you how to establish the correlation between names in Boston/FactEngine and TypeDB.

Boston Generating Documentation from Object-Role Models

A video showing how to generate Microsoft Word documentation of a model stored in the Boston conceptual modelling software. Object-Role Modeling is renowned for the 'verbalisation' of models in natural language. This can be exploited to generate documentation of a model for review and sign-off by stakeholders for model development.

Natural Language Queries - For real this time

Natural Language Graph Queries over a database using FactEngine.

Reverse Engineering a TypeDB database in Boston

A video on how to reverse engineer a TypeDB database into the Boston conceptual modelling software. Once inside the Boston software the database's model can be viewed as a Property Graph Schema, Entity Relationship Diagram or an Object-Role Model.

Boston and FactEngine connecting to a TypeDB Database - Demonstration

A video demonstrating connecting a model in the Boston conceptual modelling software to a TypeDB database and executing natural language queries over a TypeDB database. Object-Role Modelling supports nearly all features of TypeDB, such that a TypeDB database schema can be mapped in Object-Role Modelling. NB While Boston doesn't currently support relations as subtypes of relations, subtype relations can none the less be mapped and queried over. Natural language queries over those relations can then be done. The schema need be implemented in TypeDB.

Diagram Spy And AutoLayout Features - Boston

Outline of the Diagram Spy and AutoLayout features in the Boston conceptual modelling software. NB v5.8, scheduled for September '21 release has 'undo' of AutoLayout.

Role Reassignment - Object-Role Modeling Software - Boston

A video describing how to reassign roles in an Object-Role Model in the Boston conceptual modelling software.

FactEngine Introduction - Natural Language Queries over your database.

A brief introduction to FactEngine within Boston to do natural language queries over your database.

Reverse Engineering a database using the Boston conceptual modelling software.

A video showing how to reverse engineer a database using the Boston conceptual modelling software. Introduction to FactEngine.

Using the Fact Type Reading Editor in the Boston conceptual modelling software

A brief video on how to use the Fact Type Reading Editor in the Boston conceptual modelling software.

The Importance Of Primary Reference Schemes in Object-Role Modeling

Primary Reference Schemes are important in Object-Role Models such that there is an avenue to uniquely identify model element instances in the corresponding physical model. This video describes why Primary Reference Schemes are improtant in Object-Role Modeling.

An overview of the Boston conceptual modelling software

A brief overview of the Boston conceptual modelling software. Boston is used for Object-Role Models, Entity Relationship Diagrams, Property Graph Schema and State Transition Diagrams.
Load more...