Optimizing Content Delivery and Viewer Engagement: How Data Warehousing and Analytics are Shaping the Future of Media

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optimizing content delivery and viewer engagement how data warehousing and analytics are shaping the future of media

With the media evolving at breakneck speed, organizations are increasingly focused on delivering content efficiently while boosting viewer engagement. This transformation played a significant role in revolutionizing how content is delivered and consumed through his expertise in data warehousing, cloud computing, and advanced analytics. The transformation was refined by Abhijit Joshi.

During his tenure at ViacomCBS since 2017, Abhijit has spearheaded efforts to optimize the data infrastructure of the company toward scalable data-driven solutions that are better aligned with increasing demands of the digital audience, bringing about not only improvements in operational efficiency but also enhancing overall experience in content consumption.

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The design and running of a fully orchestrated end-to-end orchestration platform based on Airflow on Google Cloud Platform’s Compute Engine required major skills. It later evolved into Google Cloud Composer to make data pipeline management even easier. These developments allowed engineering teams to deploy new features much faster by saving on overhead costs, which were sharply reduced as they moved away from the traditional data warehousing systems.

He and his team aligned on development of an organizationally scoped Kerberos-authenticated Docker setup that efficiently curtailed the virtual machine costs in GCP, amounting to $10,000 a month. The developed infrastructure is scalable and efficient in terms of content delivery while balancing the need for robust security with cost-effectiveness.

Abhijit remarks, “In addition to driving cost reductions, my work has strengthened ViacomCBS’s ability to engage its audiences”. This project involved integrating advertising sales data from various local and network sources into centralized data warehouses. This enabled more precise analysis of campaign performance and audience engagement, helping identify key metrics that optimized advertising strategies.

He developed sophisticated models for advanced audience segmentation, giving the ad sales force the ability to launch targeted campaigns. Also, accuracy on audience insights improved, that in turn will inform more personalized content recommendations and leads to better viewer retention. This has been enjoyed by the company to have viewer retention increased by 30%, a testimonial to the power of data-driven personalization.

Several high-impact projects changed the way the company was dealing with content delivery and engagement. Of course, it was a redo of the CDN architecture. The re-engineered infrastructure dramatically reduced latency and improved worldwide streaming, thus improving by 25% the efficiency of streaming.

 “In the realm of targeted advertising, the use of big data technologies enabled the creation of more refined audience segmentation models. These models improved the effectiveness of ad campaigns by 40%, helping the company maximize its advertising efforts”, he adds.

The implementation of a multi-repo GitHub setup for the CBS-Corp and CBS-Interactive divisions was another key development. This standardization of code structure and reusability streamlined the creation of data pipelines across the organization, contributing to more efficient workflows and better collaboration.

Additionally, he developed data pipelines using Python, Airflow, and SQL to analyze marketing impacts across various channels. These insights, presented through Tableau and Oracle, allowed marketing teams to adjust their strategies, leading to stronger engagement and improved ROI on campaigns.

Challenges Abhijit has faced abound, especially in scaling infrastructure to deal with an exponentially growing global audience. One big challenge he was able to overcome was content recommendation latency. It was overcome through the creation of machine learning models that reduced recommendation latency by a total of 40% at the end.

He says real-time data analysis and per-user experiences will be the future of content delivery. Media organizations best positioned to continue their trajectories of success will exploit data warehousing, advanced analytics, and AI. In addition, platforms will explode globally, and edge computing will represent an increasingly important latency-reducing technology.

As the media industry embraces these emerging technologies, professionals like him are paving the way with scalable, data-driven solutions. With a focus on automation, cloud-native infrastructure, and advanced analytics, these innovations will shape the future of media, setting new standards for how content is delivered and experienced by viewers worldwide. In an era where digital audiences demand more from their media experiences, leveraging data and technology is key to staying competitive. By continuously improving infrastructure, streamlining workflows, and harnessing the power of big data, media companies can not only meet but exceed audience expectations.

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