Rules-Based Approach

Embracing automation

Automating complex, time-consuming and previously manual processes dramatically reduces the time and cost of essential tasks such as data validation, data cleansing, data integration, and data enrichment. Even specialised jobs such as Map Generalisation or Positional Accuracy Improvement can be automated with dramatic results. The power and flexibility of the rules engine means that complex or subtle decision making does not need to be sacrificed in order to achieve automation. The rules engine allows these decisions to be encoded as rules and therefore automated.

Technology lock-in becomes a thing of the past. Some organisations find themselves tied to legacy applications simply because the cost of re-writing bespoke validation or processing code is prohibitive. We believe in a data agnostic approach which works across any technology.

Creating a single, central rules catalogue means rules are applied consistently throughout your organisation, with updates delivered to all users whether on server or desktop, browser or mobile device. In addition, data validation rules can run at the point of collection, on a surveyor’s mobile device, tablets or desktops as well as on your central enterprise servers.

Our rules-engine provides a user interface to define declarative rules that describe either how your data should be (for validation) or how it must be transformed (for enhancement) and it will then apply these rules to data read from one or many systems. Whilst traditional approaches to validation rules require you to define every possible error condition to find, this fail-safe approach works by defining the characteristics of ‘good’ data. As all the data, regardless of source, is treated in the same way, users can be confident in the resulting data. This allows us to design simple solutions to difficult scenarios and avoid unnecessary technical complexity.

Create a knowledge base to speed up design and innovate

The rules-based approach is a form of knowledge management, where your rules are the encoding of your expert’s knowledge, experience and skills as a set of central, user-manged rules and knowledge base. This allows your experts to have more time to focus on design and innovation and to allow their expertise to be applied by others.

Our rules-engine plays a key role in data management, supporting wider techniques such as machine learning, where it is used to clean data and generate information used to train machine learning models. This provides a powerful combination of both explicitly defined and implicitly learnt rules.

Our rules-based approach enables you to easily manage, share and discuss rules with everyone in your team. Instant editing using the simple web user interface requires no coding, no programmers and no waiting for a gap in a developer’s schedule to have your changes made. As a result, you can focus on what you do best and your organisation becomes more agile and adaptive – plus our user-managed approach also makes sure that you own that knowledge, not a third-party developer.

Using our technology, you can integrate specific datasets from different organisations or departments into a single coherent database safe in the knowledge that it is cross-verified for consistency. You can automatically cleanse, match and merge the data into a more powerful integrated whole.

Our rules engine is scalable and designed to deal easily and efficiently with large and ever-growing volumes of complex and disparate spatial and non-spatial data structures, queries and rules. Its capability extends far beyond the performance limits of traditional relational databases or applications. For example, a data inference rule will enable rapid contextual checking of a number of nearby relevant features so you’ll know not only where a building is located on a particular road, but whether it is a legal land parcel, a sub-let, occupied or empty.