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Take cost-effective control of your geospatial data throughout its lifecycle

Effective stewardship is essential to maintain the value of your geospatial data.

But, it can be difficult; data is often held in departmental silos with different standards, tools and owners. Business requirements change too, as does the world the data describes.

Using enterprise-wide, cross-platform automation, we make data management a consistent, repeatable, rules-based process that dramatically reduces the cost and complexity of data management.

What is data management?

Data management, or stewardship, is the process of ensuring that a business' data meets its requirements for accuracy, currency and compliance with standards.

Effective management covers the entire data lifecycle from inception to obsolescence and generally follows the three C’s of data management: Control, Consistency and Compliance.

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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Why is effective data management difficult to achieve?

There are a number of reasons why it's challenging to maintain data quality.

  1. Data management must be a continual process to be effective. Your data is constantly changing (through data edits or bulk import of new data), as is the world it represents. Tasks like data cleansing cannot be effective as a one-off project.
  2. Business requirements change too. Data standards evolve, so does business strategy. As a result, businesses upgrade their systems and enter new data-sharing partnerships.
  3. Data is often held in silos. Even within a single organisation, different departments often use different tools and adhere to different data standards. Data is collected for different purposes, over a different time period and with differing levels of accuracy.
  4. Manually managing data to maintain a consistent, always-ready, quality level is hard and can be expensive and time consuming.

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For help getting your data into shape and keeping it that way.

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The 1Spatial data management approach

We believe that effective data management is best achieved through user-controlled, enterprise-wide automation.

A rules-based approach ensures that processes are:

  • easily automated
  • repeatable across the enterprise and
  • repeatable across different technology platforms.

By turning expert knowledge into user-managed rules, we also ensure that the best judgements are applied objectively and consistently.

Our technology is designed to manage complex, multivariable rules on data, irrespective of size.

The rules engine that sits at the heart of our technology was developed by drawing on over 45 years’ experience in the management of geospatial data.

Find out more about our rules-based approach that is disrupting data management.

Location Master Data Management

We are a leader in Location Master Data Management software and solutions. By auditing and cleansing, synchronising, updating and analysing different location data sets, our technology delivers significant cost and time savings, and crucially, data that you can trust and rely upon. Find out more about our location master data management approach.

Advantages of our rules-based approach

  • Saves time and money
  • Enterprise-wide and technology-neutral
  • Objective and consistent
  • Collaborative and quick
  • Enables knowledge management

Ordnance Survey

Maintaining confidence in data to underpin new product offerings at Ordnance Survey

“The individuals that we have worked with at 1Spatial have demonstrated a deep understanding of our requirements as well as a profound grasp of data management and data integrity issues in a broader context.”

Malcolm Havercroft Head of Operations for Data Collection & Management, Ordnance Survey GB
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Find out more

Data Quality

Making your spatial data fit for its intended use is central to effective data stewardship.

Data Quality Data Quality

Rules-Based Approach

Our rules engine lies at the heart of our approach to spatial data management.

Rules-Based Approach Rules-Based Approach

3D

Organisations who deal with 3D data can also benefit from 1Spatial’s automated rules-based approach to data quality.

3D 3D
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