Recent Announcements
Quantexa Upgrade Knowledge Hub Release
Introducing the Quantexa Upgrade Knowledge Hub We are excited to announce the launch of the Quantexa Upgrade Knowledge Hub, a comprehensive collection of articles and best practices designed to make your platform upgrade process more transparent, predictable, and efficient. This new section on the Community site provides a step-by-step journey through every phase of an upgrade, from initial strategic planning through to final release. It's filled with practical advice, templates, and real-world considerations to help you succeed. Make sure you're signed in to the Community to access all the articles. What's Included in the Knowledge Hub? The Knowledge Hub is structured into clear, chronological sections that mirror the lifecycle of an upgrade project. Planning for Success This initial section covers all the strategic planning required before you begin. It guides you through defining your scope, choosing an upgrade approach, estimating effort, resourcing your team, and creating a robust testing strategy. The Preparation Stage Once your plan is in place, this section details the critical steps to prepare for execution. Learn how to set up tracking, gather your dependencies, establish a parallel development strategy, understand support channels, and turn your plan into actionable JIRA tickets. The Execution Stage This section provides the hands-on technical guidance for performing the upgrade itself. It covers how to execute an incremental upgrade hop-by-hop, practical considerations for testing, and a checklist for coordinating the final merge of your code. Version-Specific Guidance Dive into practical reviews and "what to watch out for" articles for specific Quantexa versions, including a detailed look at the 2.6 upgrade and the key migrations involved. Other Key Topics Explore important related subjects, such as the strategic benefits of migrating from DSL to QSL for graph scripting and how to reduce technical debt by removing Data Pack customizations using Fusion Extensibility. How Will This Knowledge Hub Help Your Team? This collection of resources is essential for anyone involved in a Quantexa upgrade: Upgrade & Delivery Leads can use it to structure their entire project plan and ensure no steps are missed. Developers & Data Engineers can follow the practical, hands-on guidance for technical migrations and testing. Architects & Product Owners can gain awareness of the strategic decisions, effort, and best practices involved in maintaining a current and healthy platform.
Testing Starter Pack Release
I'm pleased to announce the release of the Testing Starter Pack, which sets out the main principles and considerations when testing your Quantexa deployment. Release Details This release contains articles on the recommended testing approach for deploying your Quantexa solution, with specific articles that go into greater detail on regression, functional, and non-functional testing considerations. High-Level Testing Methodology This guide outlines the best practice testing approach for Quantexa deployments based on Quantexa's delivery experience and learnings. It covers the importance of taking a risk-based approach to testing, automating your tests, using appropriate data, and testing as early as possible in your development cycle. Functional Testing Recommendations for Quantexa Functional testing is all about ensuring your solution does what's needed. This article focuses on testing areas of the Platform that help meet business requirements, including Data Ingestion, Entity Resolution, Scoring, Alerting, UI features, and security privileges. Non-Functional Testing Recommendations for Quantexa Non-functional testing evaluates how well a system works. The page offers Quantexa’s recommendations following a risk-based approach to target what to test, where to focus, and how to ensure the platform meets relevant Non-Functional Requirements in the most valuable way, with particular focus on technical security, performance, and robustness. Deployment Regression Testing This article guides you through what to consider when you regression test your Quantexa deployment. It focuses on understanding changes and their impact, and which changes you need to consider for regression. Video Overview For a quick walk-through of featured articles in this release, take a moment to watch the following video.Document Model Design Resources
We're pleased to share our articles on Document Model Design in Quantexa. Going from data discovery and high-level designs to detailed Document models. Make sure you're signed in to the Commnity to access the articles. Defining a detailed Document model design | Quantexa Community: To develop the ETL for building Quantexa Documents from ingesting the raw data, the Engineers need a detailed model design referred to as a Document model. This article provides guidance on how to define such models in readiness for handover to development. Designing Document Model for complex transactional data | Quantexa Community: This article delves into how to design a Document model for varied transactional data. Showing the use of aggregated models and handling different nuances in transactional data through an example. How will the articles help your team and deployment? These articles are helpful for stakeholders who want to have awareness of the design process and what are the next steps after data discovery and Entity-Document model design. For those who want to know how a detailed model can be designed and can follow the guidance to make detailed models for their projects.Data Ingest Fundamentals Resources
We’re excited to introduce Data Ingest Fundamentals, a new series of articles designed to guide you through every stage of bringing data into Quantexa. This introductory set of articles covers everything from understanding data quality and designing effective document models to configuring and testing ETL pipelines, and ultimately visualizing your data in the UI. This release provides step-by-step guidance to accelerate your integration, improve data accuracy, and unlock maximum value from your Quantexa solution. Whether you're starting fresh or optimizing existing pipelines, these resources will help you confidently deliver reliable, high-quality data into Quantexa. We’ll continue to expand Data Ingest Fundamentals with additional articles that explore other key aspects of data ingestion, so bookmark this page to receive updates when new articles are published. Make sure you're signed in to the Commnity to access the articles. Articles in the series: Data Ingestion Best Practice: How Do I Ingest Data into Quantexa Understanding Incremental Mode: An Introductory Guide Data Ingestion Best Practice: How to Test my ETL Pipeline Data Ingestion Best Practice: How to Display My Data in the UI Data Ingestion Best Practice: How to Configure my ETL Pipeline Related articles: Designing a New Document Model Handling Duplicated Transactions What Makes a Good Compound
Scoring Concepts Resources
This series of articles explores the foundational concepts behind building a performant and high-quality Batch Scoring solution in Quantexa. Each article breaks down a key component of the scoring process — from network generation and scoreable models to alerting and network pruning — offering practical guidance and design considerations. How will the articles help your team and deployment? Whether you're new to Batch Scoring or refining an existing implementation, this content provides a clear, structured approach to best-practice design. By understanding and applying these concepts, teams can ensure their scoring solutions are efficient, scalable, and investigator-friendly — ultimately driving better outcomes from their Quantexa deployments. Make sure you're signed in to the Community to access the articles. Articles in the series: Scoring Concepts: Run Date Scoring Concepts: In-Scope Customers Scoring Concepts: Scoring Levels and Scorecards Scoring Concepts: Scenarios & Risk Factors Scoring Concepts: Alerting and Re-alerting Scoring Concepts: Write-Once Steps Scoring DAG Design in Assess
