Big Data and Operational Efficiencies

How Media Companies Are Balancing Big Data and Operational Efficiencies?

The business environment in publishing and media industry is being disrupted by the digital collision. The explosion of big data along with availability of technology, analytics and social media, are the new facets of customer engagement for the industry. This explosion is not only impacting operations of silos but also other components of the business, as they are involved in generating more data than ever before in structured as well as unstructured forms. Media companies are increasingly using the internet as a means to deliver content, resulting in increased data velocity and aggregated data volumes. This current digital turbulence presents massive opportunities – and big data has now become a foundation of future success.

While going digital, big data and analytics significantly impacts decision-making, as there will always be a need to switch to real time data resulting in increased scope and scale of work. For instance, the company Springer, a leading publisher of scientific journals and books; decided to go digital and provide online offerings, thus; making all content easily searchable and accessible on all devices. They used data tools to provide search results based on geographical locations and also real-time data along with trending topics. Not only they made their journals easily accessible but also gained 95% of their revenue from online business. This wouldn’t have been possible without using big data.

Media companies are now profiling customers using both enriched internal CRM data and public data from online content delivery platforms and social networks. Customer has now taken a center stage in real-time with data-driven reporting. Real-time data mining and analytics are revealing customer needs and this helps the companies to tailor content dynamically, resulting in better decision making and content provisioning.

When companies are handling so much of data, media asset management becomes important and meta-tagging of media assets becomes necessary. For, instance, British Broadcasting Company(BBC) generated more than two petabytes of data during the 2012 Olympics and the big challenge was to deal with the enormous data that was to be created; which included more than 10,000 individual pages covering over 10.000 athletes, 200 teams and 500 disciplines. It became necessary to incorporate big data in their strategy. As a solution, the BBC opted for generating these pages automatically and enriched it with metadata. This metadata was also used to automatically generate more new pages. This approach worked to handle huge amounts of data with an average of 25.000 transactions per second.

The challenge the media companies face is to access, analyze, and manage vast volumes of data and improve operational efficiency as well as performance. Using big data in an appropriate way can help transforming these challenges into opportunities.

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