Designed by Agile Lab, Witboost is a versatile platform that addresses a wide range of sophisticated data engineering challenges. It enables businesses to discover, enhance, and productize their data, fostering the creation of automated data platforms that adhere to the highest standards of data governance. Want to know more about witboost? Check it out here or contact us!
This repository is part of our Starter Kit meant to showcase witboost's integration capabilities and provide a "batteries-included" product.
The Practice Shaper is the main and most impactful witboost setting that models witboost entities (domains, systems, components, templates) as nodes of a fully-configurable property graph.
This enables data-oriented organizations to shape witboost based on their unique use cases, structure, and needs.
Thanks to the Practice Shaper, a company can approach any project scenario in data (Data Landscape), such as Data Mesh, Business Intelligence, Machine Learning and others, by defining which practices are enabled and regulated, with the possibility to define technological and methodological guardrails.
Refer to the witboost documentation to learn more about Practice Shaper and Data Landscapes.
The Practice Shaper property graph is composed of:
- type nodes - vertices representing abstract concepts (classes)
- instance nodes - concrete entities each instantiating one of the available type nodes
- relations - they are used to define relationships between nodes. For example, an instance node will always express an
instanceOf
relation towards a type node
Type nodes and the relations among them are defined by the Platform Team when configuring a Data Landscape.
Instance nodes and their relationships with type nodes (and other instance nodes) are generated by end users as they interact with the platform, within the context of a data landscape.
Both type and instance nodes are registered as witboost entities: their definition is provided by a catalog info YAML file (hosted in a Git repository), and they are part of the witboost catalog.
A sample Practice Shaper graph composed of data landscapes, domain types, system types, and component types, with their relationships:
Data Landscape | Description | Installation guide |
---|---|---|
Data Mesh | The Data Mesh is a decentralized approach to data architecture that emphasizes domain-oriented ownership, self-serve data infrastructure, and treating data as a product. It shifts the responsibility for data management and governance from a centralized data team to the various business domains that generate and use the data | Go to the guide |
Lakehouse Medallion | Medallion architecture, also known as the Lakehouse architecture, is a data architecture pattern that organizes data into different layers, or medallions, to enhance data processing efficiency, reliability, and governance. It typically involves three layers: Bronze, Silver, and Gold | Go to |
This project is available under the Apache License, Version 2.0; see LICENSE for full details.
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