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improved

forecast 

ACCURACY

Using big data to drive smarter ways to save energy consumption and improve forecasting accuracy. Future proofing the network and delivering high service levels.


Project Snapshot

AEMO

Location:
Melbourne, Australia

Industry:
Utilities

Project Challenges

Data used in isolation across many systems. Business units working in silos with no consolidation or single source of the truth. Enquiries taking days or weeks to answer.

The Solution

Microsoft Azure’s data platform with rich data components catered for evolving needs. Big data warehouses were designed and built to centralise data for quick access.

Results

Capacity needed to analyse and report from centralised data that forms a consolidated single source of truth quickly. Better decision making and forecasting and reduced costs.

Download case study

The opportunity

The opportunity

Historically, AEMO’s data was used in isolation across its many systems. Different business units acted in silos, generating their own reports without a consolidated, single source of truth, meaning energy grids couldn’t be compared and increases or declines were not noticed. An internal initiative to aggregate data in a pseudo data warehouse was carried out, however the volume of data proved too much as certain queries were taking  

days to execute and ministerials were taking weeks or even months to answer. 

Empired helped AEMO use big data to drive smarter ways to save energy consumption and improve forecasting accuracy across Australia. This solution is key to planning how the network will look in the future and the infrastructure required to ensure continued high levels of service to energy consumers. 

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