Hearst Television elevates its access to key analytics with cloud BI solution

Lindsay James
Lindsay James
By Lindsay James on 24 July 2015
Hearst Television elevates its access to key analytics with cloud BI solution

This article was first published in the Summer 2015 issue of OnWindows

Hearst Television serves 30 US cities and reaches approximately 18% of US households. The TV station broadcasts 60 video channels, featuring local and national news, weather, information, sports and entertainment programming, and local community service-oriented programmes. The stations also host and operate digital online and mobile platforms that extend the company’s brands and content to local, national and international audiences.

Hearst’s on-premise business intelligence (BI) solution was comprised of data extracted from its operational traffic system to the Decentrix BIAnalytix data warehouse, hosted on a virtual machine.

Data was processed into an Analysis Services OLAP cube hosted on physical hardware and subsequently synchronised to a SharePoint application server hosting corporate reporting.

As configured, the infrastructure was not suitable for delivering data to business users by the established 6am deadline. Instead of investing more money in expensive on-premise hardware solutions and infrastructure to manage it, Hearst wanted to explore the viability of a cloud implementation of their existing BI solution in Microsoft Azure.

Decentrix was commissioned to migrate the existing BI solution onto the Azure cloud platform. Decentrix took a hybrid approach to shift the heavy workloads into Azure without disrupting existing business processes relying on the on-premise SharePoint solution. Using BIAnalytix in the Azure cloud, Hearst is getting data insights much faster than previously. Furthermore, the company now has the architectural flexibility to scale operations as data sources and volumes continue to grow.

By refactoring a few pieces of the extract, transform and load (ETL) process to align better with the Azure architecture, the end-to-end processing time for nightly work was reduced by 40%. This means more flexibility in the processing schedule to add additional data for business users. At the same time, resources in Azure were used to their maximum capability whenever possible because the entire BI solution was on dedicated equipment.

By implementing a rolling shutdown and start-up routing, Decentrix was able to minimise the uptime of the servers in Azure, thus reducing overall costs. By using this carefully managed operational technique, the overall cost of hardware, software and support has been reduced by 35%.

“The results have exceeded my expectations,” said Al Lustgarten, vice president of IT and administration at Hearst. “The reduced processing times have been impressive, and the stage is set for future projects in the cloud. I can’t say enough good things about the team at Decentrix that made all this happen, and I am very impressed at how quickly this was completed.”

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