Enabling a digital lifestyle using data analytics and machine learning

To enhance customer experience for its 60 million customers, Globe Telecom looked into the use of machine learning to deliver real-time targeted marketing and optimised products and services, while maintaining compliance with the latest industry data regulations in the country.

Developing a scalable data platform to support evolving IoT-based insurance propositions

Developing a scalable data platform to support evolving IoT-based insurance propositions

The
resulting NGP enables Octo Telematics to store, process, and analyse data
generated by over 5.3 million drivers totaling 175 billion driven miles, and
that increases by over 11 billion additional data points daily. It also allows
for complete flexibility in the selection of sensors, analysis and output of
data for all insurance and automotive services.

From genomic data to precision medicine via machine learning

From genomic data to precision medicine via machine learning

Inova had generated petabytes of genomic and patient data, and needed to provide a way to process that data into a single data infrastructure. It could take weeks and months to pull data together for researchers with its previous data warehouse. 

Harnessing data for improved customer service and smart urban planning

Harnessing data for improved customer service and smart urban planning

The EDH was used to combine network topology (GIS) data with terabytes of DSL performance (time series) and electrical line test data to grade the quality of every line in the network. This helped indicate if slow speed was a network issue or a customer issue. Using this network analysis, the probability of a successful outcome of an engineer dispatch could be predicted, reducing wasted in-person engineer visits.

How DBS transformed into a data-driven organisation

How DBS transformed into a data-driven organisation

The enterprise data hub, built in partnership with Cloudera, enabled DBS to scale out more economically, experiment more, and think about the types of data in terms of billions of events rather than millions of events. It allowed DBS to answer questions before they’re asked to more
effectively engage customers and deliver better service.