At a recent event, Jon Palin, Chief Product Officer from Objective Corporation, spoke about the challenges and benefits of creating a federated data fabric to power AI/ML programs for government agencies.
The Challenge of Disparate Data
One of the main challenges faced by government agencies when implementing AI/ML programs is the presence of disparate data. Data can be spread out across different departments and systems, and often, there is no standardisation or integration between them. This results in inconsistencies, errors, and data quality issues that can impact the accuracy and effectiveness of AI/ML models.
The Benefits of a Federated Data Fabric
Palin stressed the importance of creating a federated data fabric to address these challenges. A federated data fabric is a network of interconnected data sources that can be accessed and used by different departments and systems, without compromising data privacy or security. It allows for standardisation, integration, and optimisation of data for AI/ML, resulting in more accurate and effective models.
Implementing a federated data fabric requires collaboration and coordination across different departments and stakeholders, as well as a robust data governance framework. However, the benefits of a federated data fabric go beyond AI/ML programs, and can lead to better decision-making, improved citizen services, and increased efficiency and productivity across the organisation.
Objective Corporation has developed the application Objective 3Sixty for such circumstances. To learn more about Objective 3Sixty and how it can empower your department click here.
Watch Jon Palin's Presentation
If you missed Jon Palin's presentation, you can watch a recording of it here. Don't miss out on this valuable insight into the future of AI/ML in government agencies.
