This page gives you an at-a-glance overview of the resources available on the Quantexa Documentation site, which will be useful in the setup, configuration and use of The Quantexa Platform.
How to guides and best practice
To help you get set up and use the platform as effectively as possible, we have a series of how to and best practice content, including:
Project Example
An example project with accompanying documentation that provides guidance and best practices for particular features of The Quantexa Platform. This includes Smoke Tests, Scoring, and Task Loading. Project Example also includes migration branches that provide examples of how to perform product upgrades for each Quantexa release. Read more about Project Example.
Data Fusion Tutorial
A step-by-step guide to the process of setting up Data Ingestion in the platform using Data Fusion. Data Fusion is a framework for data modeling and ingestion used within the transformation and load stages of ETL. It provides a simpler way to generate the components required to support Network Generation, a reduced reliance on Scala skills, and an intuitive, configuration-driven interface. Read more about Data Fusion.
API reference
A complete list of the API (or Application Programming Interface) types used in The Quantexa Platform - including REST, Scala Client and Protobufs (Protocol Buffers) - with detailed sub-sections including full lists of the specific APIs for different services and features. Read more about API reference.
JSON Configuration
A reference for our JavaScript Object Notation (JSON), a syntax for storing and exchanging data. JSON can easily be sent to and from a server, and used as a data format by any programming language. Read more about JSON Configuration.
Supported software
A table listing the versions support for different third-party software, including browsers, development tools such as Scala, Apache Spark and Kubernetes and software used within the platform itself including Elasticsearch, Gradle and Node.js. Read more about supported software.
Helm Charts
A collection of YAML manifests that describe and deploy Quantexa App Tier resources into Kubernetes. The Chart is highly dynamic, and facilitates provisioning and management of resources. Read more about Helm Charts.
Parsers
An out-of-the-box solution for cleansing and parsing the data types typically used for Entity Resolution in Quantexa deployments. Standard Parsers also provide standard Case Class Models for the output of cleansing and parsing, so they are compatible with Quantexa’s standard Compound generation functions. Types of Parsers include: Account, Business and Individual. Parsing itself is the process of analyzing the grammatical structure of an input string and extracting information into standardized fields. Read more about Parsers.
Data Packs
A collection of resources which provide the following for the third-party or open source data sources most often used on Quantexa deployments:
- Pre-written data models
- ETL code
- Data Generators
- UI components
Read more about Data Packs.
Detection Packs
A Scoring solution that enables projects to progress more quickly from resolved Entities and generated egocentric Networks to Alerts ready for investigation. Using Detection Packs avoids the time and cost associated with writing the same Scores and Pipelines multiple times on different projects. This out-of-the-box Scoring solution provides a set of baseline Scores, so individual projects can focus on developing the complex Scores that match their specific needs. Read more about Detection Packs.
QPython
A library of helper functions for analyzing Quantexa-processed data using Python, including Scoring graphs, Batch Resolver outputs, and Scoring outputs, and for integrating the analytical results with The Quantexa Platform. Read more about QPython.
ER Accelerate
A package of Quantexa’s Entity Resolution (ER) capability into a UI-driven, low-code format to empower developers to create Decision Intelligence (DI). ER Accelerate supports developers through this journey in the following ways:
- A lower barrier to entry by reducing the skill set required to interact with Quantexa products.
- Faster time-to-value through streamlined deployment and configuration.
- Improved DI through utilizing Quantexa’s Entity tuning best practices.
This capability is currently only available through the Early Access Program (EAP). You can register interest or read more about ER Accelerate.
Find out more
There are details on other information you can find on the Documentation site in the discussions area of Community, including core concepts and getting started with The Quantexa Platform.
You can find details of everything mentioned on this page on our Documentation site. If you are unable to access the documentation site, please contact your Quantexa point of contact or the Community team at community@quantexa.com.
