Data Transformation to Enable Advanced Analytics and AI
Our client needed a modern, transformative data architecture to reach the next level of analytics, including AI.
Untapped TV viewership data creates new business opportunities
Post-merger, this newly combined Communications Service Provider (CSP) struggled to effectively leverage their TV viewership data to its fullest potential. Each of the merged companies had disparate data platforms, with differing data structures and business rules, being used for single purpose business objectives. RevGen helped the CSP take what was a chaotic environment of disparate data systems and turn it into a valuable business resource.
Working with RevGen, the CSP built a centralized data lake to integrate viewership data from all legacy companies and viewing platforms to enable high value business use cases, such as data monetization, increasing media revenue, reducing programming expense, personalizing and improving the customer experience, reducing churn, optimizing pricing, and identifying upsell and cross-sell opportunities.
Corporate mergers are never easy. A lot of work goes into integrating people, processes and technology. For this CSP, that was particularly true for their data systems. They faced many challenges common to mergers, including:
Data comes from varying video server technologies and TV set top boxes that differ in make, model, and software. This creates quite an integration challenge. RevGen worked closely with the organization’s IT and business teams to understand the current-state data environments for all legacy companies, including data sources, transformation rules, data formats, timing, accessibility, and gaps.
Additionally, in partnership with the client’s IT team, RevGen helped to gain consensus on universal business requirements for broad usage of the data across the organization, formulated an execution roadmap, and designed and implemented a big data solution to meet the viewership data objectives of the organization.
The CSP is now better equipped to realize the potential value of this relatively untapped data asset to truly move the needle for the organization.
The solution included:
Viewership Data Roadmap: RevGen helped gain an understanding of current state environments, process, and data integrity issues across all legacy companies as well as the future state viewership data needs of the organization. This knowledge was then used to formulate a multi-phased implementation roadmap to guide the integration and implementation of a centralized viewership data lake environment to serve the combined organization.
Viewership Data Lake Solution: A centralized and combined company big data platform built on opensource Hadoop technologies to accommodate both real-time and batch data ingestion, processing, and presentation of viewership data. The solution ingests and stores data in its native form, correlates raw events into viewing impressions, enriches these viewing impressions with other organizational data, and provides this data for business usage in an easy to consume format. Data sizes are in the petabytes supported by a cluster of nodes in the 100’s.
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