Is Aize a cloud technology?
Yes, the product is run in Aize’s Azure tenant, and delivers core digital twin capabilities in addition to maintenance, integrity and other capabilities to unlock tangible and sizeable business value for the users.
Why SaaS over a bespoke solution?
Users of Aize’s product benefits from frequently improved functionality tied to the product roadmap. As such it is more dynamic and constantly improving which is different from bespoke applications or applications developed primarily for showcasing a specific underlying capability
Why does a SaaS solution need more SaaS?
The Aize software product is a SaaS product, making internal use of various SaaS and PaaS backend services to enable the product – as any other modern SaaS application.
What is Cognite's role in Aize?
Cognite supplies 3D visualization technology as “PaaS” into Aize’s backend as a separate service, chosen for its performance on large models. Cognite’s 3D technology is one of seven key backend services in Aize’s product. As with other backend services the 3D capacity is integrated with the product and cannot be split out as a separate module. It is a part of the product and critical to unlock the user value.
Is Cognite a must?
The product, which uses customer data as raw ingredients, is a consumer of data from the customer, and agnostic to the architecture chosen by BP. Aize does not run on a CDF platform-service as a part of the product stack. Thus CDF is not a requirement to run the product.
Where does Aize get its data from?
The Aize product reads meta data from the customer’s data sources, be it databases, data lakes, data platforms, or any other reachable endpoint capable of delivering data relevant to the customer’s assets.
Is Aize an information source or an information carrier?
Data from source systems is not ingested into the product. This means there is no replication nor does the product act as a master repository. However, certain data might be locally cached for performance reasons.
What metadata are used to create a data model?
Aize builds a data model from meta data such as location registers and tag overviews that is used internally in the product. This model can of course be exposed via APIs or exported/ingested back to customer.
How does Aize fit BP's enterprise model?
The internal data model in the product backend is a separate “local” Aize backend service, independent from any Cognite technology. Aize’s data model can be accessed by BP through e.g. APIs or as write-backs to BPs enterprise model for use by others.
How time-consuming is data contextualisation?
Contextualisation/mapping is today predominantly a manual process, taking 1-4 weeks for a larger asset depending of the state of the source system data. Over time this effort will be reduced but not likely to take less than 1 week in the foreseeable future.
How does Aize speed up data contextualisation?
Presence of an enterprise data platform with contextualised data, e.g. Cognite CDF data platform, will help in reducing this down to 1-2 weeks. However, some manual oversight we believe will typically always be required. The critical factor is though always data quality as it drives user trust and value of the product functionality. The difference in a week or two for onboarding, mapping and contextualisation is modest compared to a product that creates value for years thereafter.
Can Aize make use of other customer data models?
If well-structured models exist describing/modelling the customers data sources, these will be used, to expedite and enrich Aize’s internal product data model.