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.
Data review and roadmap
Learn how we were engaged by the Fair Work Commission to conduct a review of how they manage a wide range of data related to cases across multi jurisdictions and internal business units, and to create a comprehensive roadmap for the Commission.
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.
5 reasons the Azure Data Lake can be invaluable to your organisation
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.
Infrastructure reporting project for RPV
RPV needed a solution that would report on project data that could be used by multiple stakeholders relating to rail infrastructure projects being delivered across Victoria. They engaged Data Agility to support them with this project.
7 mistakes organisations make when developing a data strategy
We review the 7 most common mistakes we see organisations make when it comes to developing their data strategy.
What should be in your data strategy
Today we look at what should be in your data strategy, who should be involved and why you need to consider your budget and timelines.
Using a data strategy to achieve long term business objectives
Learn how we solved Sustainability Victoria’s challenge to create a robust data system that could support evidence-based planning for hazardous waste management in Victoria.
Most popular insights.
Are You Collecting The Data You Need?
Are you collecting the data you need? Collecting more data does not necessarily lead to more useful information or better decision-making. In fact, the overcollection of data can lead to wasted resources.
Data Thinking for Organisational Transformation
Data thinking can be applied across the four pillars approach of transformation — Data, People, Process and Technology. In part 2 of our article series, we explore data thinking across all areas of organisational transformation.
The Key to Successful Organisational Transformation
Whatever the driving reasons behind your organisation’s transformation program, a dedication to data will help you realise your targeted future state. In part 1 of our Organisational Transformation series, we highlight why organisations should lead with this approach.