Learn how Data Agility helped Comcare to document their Claims Data Architecture, to improve their understanding of their claims data.
Real-World Examples of Predictive Analytics in Government
Learn how Data Agility designed a solution for genetics and genomic data for the Department of Health in Victoria.
Designing a solution for genetics and genomics in public health Victoria
Learn how Data Agility designed a solution for genetics and genomic data for the Department of Health in Victoria.
How Organisations Maximise the Value of Their Historical Data
Learn the 5 key elements every data strategy should have: the vision, principles, governance model, target state and ultimate plan.
How to Make the Jump to Predictive Analytics from Your Business Intelligence Solutions
Learn the 5 key elements every data strategy should have: the vision, principles, governance model, target state and ultimate plan.
The 5 Key Elements Of A Data Strategy
Learn the 5 key elements every data strategy should have: the vision, principles, governance model, target state and ultimate plan.
Using data analytics to be more client centric
The Department of Health and Human Services needed a better way to manage their data, apply it and meet the needs of the future. We applied our Enterprise Data and Analytics framework to develop a solution for them.
Applying data through analytics
AusPost needed a strategy for applying their IM data through analytics. Here’s how we created an Analytics Strategy for them.
The best real-world applications of predictive analytics in business
With the exponential increase in data, many organisations are faced with the ever increasing challenge of storing, processing and making sense of their data. Cloud-based data lakes help address these problems by providing organisations with the capability to capture any type of data, whether structured or unstructured, and make this data available for use for a range of applications. This includes your traditional reporting from structured data warehouses to big data analytics.
Most popular insights.
Top Causes of Poor Data Quality and How to Fix Them – Technology
Learn the root causes of poor data quality related to technology and how you can address them to ensure your organisation gets access to high-quality data that is reliable and serves its purpose.
5 Common Problems that Data Scientists Face
Learn how to write a data strategy for your organisation and how to move from the ‘thinking’ stage to the ‘doing’ stage of the project.
Machine learning and ethics
Advancements in artificial intelligence (AI) and machine learning (ML) have grown exponentially over the past years.As the capacity to gather copious amounts of data has increased, the curation and development of highly targeted algorithms have also developed rapidly....