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Data Enrichment: Inferring data where partial data exists

Organisations with large amounts of legacy data, such as water companies and transportation agencies, are especially prone to this challenge.

We work with clients to enhance the value of their data by determining missing features or completing missing attributes.

We work with your experts – the creators and users of the data – to distil the experience, knowledge and expertise in their heads into consistent, objective and repeatable rules. For example, “a house of this age, size and location will have a sewer pipe of this size and construction located to the rear of the property.”

Our knowledge management approach of encoding expertise enables clients to infer what their missing data should be with a high degree of certainty. Results can then be confirmed, as required, by surveying a small sample rather than the entire estate.

We cost-effectively improve the value of your data, and the confidence users have in it. Our data solutions really make your data smarter.

Data Enhancement: Combining data sets and using third party data sets

Data enhancement releases greater value from existing data investments. We ensure you make the best use of your existing data assets to keep your core spatial data current and accurate. This may include combining the best parts of different datasets to create something new or using third party and public data to augment your core information giving you a faster route to reliable, trustworthy data.

Perhaps the customer addresses in your billing system are the most accurate in your business, but your asset database has the best view of your network. Taking an automated, rules-based approach, you can combine the best of both datasets, even if the data exists in different formats, within different systems, in different data silos. You can then fill any gaps with data you purchased from a third-party provider.

Our solutions help reduce your “time to value”, helping you to achieve and maintain usable, trustworthy data with minimum time and cost.

The Little Book of Spatial Data Management

In our free Little Book of Spatial Data Management, we look at how effective stewardship is essential to maintain the value of your geospatial data and how a consistent, repeatable, rules-based process can dramatically reduce the cost and complexity of data management.

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Additional Resources

Data Validation

Our automated, rules-based approach validates data at the point of collection, in the field on a mobile device, or before it is ac...

Data Validation Data Validation

Data Quality

Our approach is designed to help you discover and precisely define your data quality requirements, to check how your data conforms...

Data Quality Data Quality

Data Cleansing

Understanding the condition of your data is important, but fixing it is vital. Poor data quality can mean bad business decisions a...

Data Cleansing Data Cleansing
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