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Post-Merger Data Lake Solution | RevGen Partners
Success Stories

Post-Merger Data Lake Solution

Untapped TV viewership data creates new business opportunities

television remote control in human hands

Project Overview

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.

Client Challenge

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:

  • Disparate data. Each legacy company had different source data collection methods and technologies, different business and data objectives, and different rules to correlate and enrich their data for business use. Additionally, each data environment was developed for a single purpose and not broad organizational use.
  • Lack of data quality controls. No one truly understood the extent of data completeness and accuracy issues, nor were there insights into root causes for mitigation to improve data quality.
  • Lack of holistic viewership data across viewing platforms. Each viewing platform’s (e.g., Linear, IPTV, DVR, Video On Demand) data was collected, correlated, and enriched in separate environments, using different logic, and different tools. There was no single place to analyze all viewership data.

Approach

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.

Solution

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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