An Australian Energy Company
- BryteFlow unlocks large volumes of complex enterprise data (including SAP) on an AWS Data lake for this leading Australian energy company.
- Provides easy access to data for Reporting, Analytics and Machine Learning.
- Allows data from multiple data silos to be integrated.
- Delivers query results many times faster than in an on-premises environment.
- Enables faster time-to-market for customer-centric innovations.
- Provides a single source of truth for all data requirements.
- Increases accessibility of data, facilitating innovation around data and new customer experiences.
- Provides power, flexibility and scalability around handling big data -all at a much reduced cost.
The client is at the forefront of Australia’s energy market, serving 4.2 million retail customers. The company relies on a range of energy sources , from traditional fuels such as coal and gas to renewables such as wind and sun. It analyses data collected on consumption patterns, environmental trends, and more to understand and better serve its customers.
Until 2016, the company used on-premises hardware to run its operations and big data projects. However, as the volume and complexity of data increased in line with business growth, the existing infrastructure was struggling to support the increasing data demands. The General Manager of Data and Analytics says, “We just couldn’t access data and crunch the numbers fast enough on premises and we couldn’t find an infrastructure configuration that would support what we needed to do.”
The client faced several issues:
- The existing infrastructure could not handle the rapidly increasing analytical demand.
- Fragmented storage slowed access to critical data, stifling innovation.
- Cost of physical infrastructure & FTE overload was a big issue.
- It was difficult to get access to SAP data and integrate it with other enterprise data.
- Multiple data silos meant there were multiple versions of the “truth”.
- More time was spent in wrangling data rather than analysing it.
Convinced that the cloud was the best option for the business, the company approached Amazon Web Services (AWS) who introduced Bryte as their specialized advanced technology partner to help build an enterprise analytics environment with centralized data access.
- The BryteFlow software was used to create an automated data lake for the client based on three core AWS products: Amazon Redshift, Amazon Simple Storage Service (Amazon S3), and Amazon Elastic MapReduce (Amazon EMR) and allowed easy integration with AWS services like Amazon Aurora and Sage Maker.
- The BryteFlow software was used to continuously replicate on-premises data to a data lake on Amazon S3 and a data warehouse on Amazon Redshift with minimal impact on the sources.
- BryteFlow (configured for Amazon EMR) enabled data transformations to extract raw data from different sources and prepare it for mining.
The company’s new enterprise analytics environment has been a game-changer for its data operations:
- BryteFlow software has helped in achieving flawless and accurate data replication on AWS Cloud with low latency. which could never be achieved earlier, due to the large volumes and complexity of the data.
- The company has cut down on data costs enormously.
- Query results are many times faster than in an on-premises environment (at times from days to minutes).
- An ability to handle query sizes that was never possible before.
- The company’s data is now accessible to functional teams across the organization by consolidating all workloads and databases into one powerful engine.
- The data lake has facilitated faster time-to-market for new and highly personalized customer offerings. The company is currently undertaking a bill segregation project that breaks down a customer’s monthly bill to show energy consumed per household appliance. It is also exploring a facilitation role in peer-to-peer trading of solar energy, another project made possible with its new analytics environment.
- SAP data can easily be integrated with other enterprise data sets.
- Data access has beenspeeded up from several days to mere hours.
- It has enabled fast and efficient response to consumer requests.
- Increasing volumes of data and users can be easily handled now.
- Scalability and flexibility for new use cases for the data is helping in adopting new data-led initiatives.