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Take cost-effective control of your data throughout its lifecycle

Effective data governance and stewardship are essential to maintain the value of your 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 governance and management a consistent, repeatable, rules-based process that dramatically reduces the cost and complexity of managing your data.

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What is data governance?

Data governance is a framework that enables organisations to monitor, manage and maintain data quality, integrity and reliability on a continual basis. It consists of a set of policies, processes, and people (roles and responsibilities) that ensure the optimal management of data throughout its lifecycle – from data gathering, storage, management and processing through to the disposal of data.

Data governance facilitates the three C’s of data management: Control, Consistency and Compliance.

How does data governance differ from data stewardship or management?

Data management, or data stewardship, is the implementation of those policies and procedures in order to conform to data governance guidelines for data accuracy, currency and compliance.

Why is effective data governance difficult to achieve?

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

  1. Data governance (and 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.
  5. Where organisations need to manage geospatial data (for instance in a digital transformation project) it is important to be aware of the unique characteristics of this type of data.
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

How 1Spatial can help

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

This ensures that data governance becomes a repeatable process, rather than an event. By turning expert knowledge into user-managed rules, this approach ensures that the best judgements are applied objectively and consistently, while at the same time minimising user-based errors.

A rules-based approach ensures that processes are:

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

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 governance.

Location Master Data Management

Pioneers in location master data management, we enrich and enhance location data, enabling critical decision making and improved data governance. Our powerful technology helps organisations take cost-effective control of their spatial and non-spatial data throughout its lifecycle, making it fit for purpose, compliant, and of a consistent quality. We do this by automating the data validation, auditing, cleansing, synchronising and maintenance of data across the entire data ecosystem, enabling better decisions and greater insights. Our solutions deliver significant cost and time savings, and crucially, data that you can trust and rely upon.

Benefits of 1Spatial's automated approach to data governance

  • Saves time and money
  • Enterprise-wide and technology-neutral
  • Objective and consistent
  • Collaborative and quick
  • Enables knowledge management
  • Reduces user errors
  • Turns a one-off project into a cost-effective and ongoing process

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.


Data maintenance

Spatial data is increasingly important for competitive advantage. But that data is frequently held in different places, in different formats and with different degrees of accuracy.

Organisations need a single source of spatial truth, a central data set they can trust. With an automated approach to data governance and maintenance, data quality is enforced along the way, instead of being treated as an after-thought.

1Spatial’s data maintenance solutions report regularly so that you always know the state of your data. Any errors that can’t be fixed automatically are flagged for immediate attention, improving your overall stewardship and ensuring your data is fit for purpose.


Automated data integration contributes to $5 billion saving for US Census

“This is a large, complex and mission-critical spatial database that is growing at 10-15% annually. There are huge demands from the user community for spatial and temporal accuracy and quality, together with stringent processing deadlines. We believe that 1Spatial’s solution will meet our expectations to build an agile, service orientated architecture, whilst reducing our storage requirements.”

Tim Trainor Geography Division Chief, US Census Bureau

Find out more

Data Quality

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

Data Quality Data Quality

Data Validation

Our rules-based data validation approach allows you to define and manage rules against the data being tested.

Explore data validation Explore data validation

Data Cleansing

Automate complex, time-consuming and manual processes to clean and correct your data automatically.

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