Data Management

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.

Take cost-effective control of your 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.

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

OSGB now has an automatically orchestrated data maintenance and production system with a single database at the centre. It enables the automated control of data quality, giving OSGB high levels of confidence in the accuracy of their data. As a result, they can protect their existing revenue stream by maintaining customer satisfaction as well as having a platform from which to launch new data-dependent products and services.

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What is data management?

Data management, or stewardship, is the process of ensuring that an organisation’s 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.

Why is effective data management difficult to achieve?

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.

Business requirements change too. Data standards evolve, so does business strategy. Organisations upgrade their systems and enter new data-sharing partnerships.

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.

Manually managing data to maintain a consistent, always-ready, quality level is hard and can be expensive and time consuming.

The 1Spatial 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 and repeatable, across the enterprise and 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.

Advantages of our approach:

  • saves time and money
  • enterprise-wide and technology-neutral
  • objective and consistent
  • collaborative and quick
  • enables knowledge management

Contact us

For help getting your data into shape and keeping it that way, please contact us.

Automated data validation, cleansing, transformation and enhancement for your data.

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Ensure compliance of your data for use across the enterprise.

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Efficiently and consistently plan, maintain and publish your data, whilst automating your production workflows.

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