Telecom Fiji speeds up decision-making with Oracle Autonomous Database

While most tourists come to the remote South Pacific archipelago of Fiji to get away from the rest of the world, the customers of Telecom Fiji Ltd. are demanding to be more connected—via streaming content, fast web browsing, social media access, and a wide range of other voice, data, and internet services.

But the telecom operator’s ability to delight those business, government, and residential customers was limited by its inefficient data management capabilities. Telecom Fiji’s IT staff used to spend hours manually aggregating and correlating customer and other data, a process that introduced errors, slowed down reporting, and ultimately got in the way of timely business decision-making.

Telecom Fiji is leveraging AI-powered algorithms from Oracle’s cloud-based Autonomous Data Warehouse and Oracle Analytics to integrate and sift through terabytes of data from multiple sources to produce actionable insights in minutes rather than weeks.

Using the front-end Oracle Analytics platform, Telecom Fiji is creating dashboards to visually present detailed data on sales and marketing performance, product performance, service-usage trends, service-delivery performance, and other key indicators. And because Oracle Autonomous Data Warehouse is self-managing, it frees the operator’s IT staff to come up with innovative ways to use those analytics. “Then they will be performing more of an advisory role to management,” says Shalvin Narayan, head of IT. “It did surpass my expectations because the amount of functionality and performance it was providing, with respect to the amount of investment, was marvelous.”

Oracle Autonomous Data Warehouse provisions easily and quickly (in just minutes) to improve time to market; its self-tuning accelerates query response time; and its self-patching capability eliminates downtime for maintenance. It also auto scales capacity on demand to maximize performance and minimize costs. Telecom Fiji says it would have had to spend hundreds of thousands of dollars to acquire and integrate equivalent data warehouse and analytics capabilities in its data center.