Data Management

Take cost-effective control of your data throughout its lifecycle

Effective data governance and management 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.

Free webinar: An Introduction to Spatial Data Governance and Management

Watch this practical discussion with our panel of data governance and data management experts Seb Lessware (CTO - 1Spatial), Nicola Askham (The Data Governance Coach), and Sheila Steffenson (CEO - 1Spatial Inc USA) as they explain why spatial data governance and data management are vital elements for any successful digital transformation project today.

Watch now

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 management?

Data management is the implementation of those policies and procedures in order to conform to data governance guidelines for data accuracy, quality, currency and compliance. Data management is often seen as the "umbrella term" for all the different disciplines that you could use to manage and improve your data better, of which data governance can be one. According to DAMA, the data management association, data governance is at the centre of data management because it underpins all the other data management activities.

Why is effective data governance and data quality difficult to achieve?

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

1. Data governance and 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.
5. The lack of unique property reference numbers makes it difficult to merge datasets and manage changes in the data.
6. 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.

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.

Automated rules-based data governance and data management

By combining our technology and expertise, we enrich and enhance spatial and non-spatial data, enabling critical decision-making and improved data governance. We help organisations take cost-effective control of their 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.

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.

Our capabilities

• Data assurance and quality - Our no-code rules engine 1Integrate can validate how well your data conforms to business-critical standards or requirements and provides reports to indicate where corrections are needed.
• Data cleansing - Our technology can automatically repair errors, inconsistencies and gaps in your data and create a process for continuous, automated improvement.
• Data enrichment and enhancement - We can help you make most of your data by combining the best of various datasets - even if the data exists in different forms and systems - keeping your data fit for purpose.
• Data governance and data management - We can help you to dramatically reduce the cost and complexity of data management and governance by making data management a consistent, repeatable process.

Benefits of an 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

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.

Further spatial data governance resources

Blog: Why Spatial Data Governance Matters

Trusted data delivers confidence in decisions, enabling organisations to accurately analyse trends, draw logical conclusions and produce powerful forecasts. “Trusted data” means the data is of a high quality, accurate, up to date, accessible, interoperable and in a standardised format to be usable.

Read more 

On-Demand Webinar: An Introduction to Spatial Data Governance and Management

Watch this practical discussion with our panel of data governance and data management experts Seb Lessware (CTO - 1Spatial), Nicola Askham (The Data Governance Coach), and Sheila Steffenson (CEO - 1Spatial Inc USA) as they explain why spatial data governance and data management are vital elements for any successful digital transformation project today.

Watch now