Cloud-Based Customer 360º Data Lake for Data Monetization

May 30, 2017

As one of the largest publishers in North America and a leading provider of end-to-end business process outsourcing, CDS Global wanted to augment its business model by monetizing its 45 years of subscriber data to enable a Customer 360 approach and simplify its delivery of big data marketing insights to CDS customers.

Zaloni Customer Success - CDS Global, Patrick Lea

Challenge: CDS had decades of valuable subscriber data from its magazines, online subscriptions and marketing materials, untapped and sitting in siloed systems across the organization. CDS was limited by existing hardware and software and was unable to combine these large volumes of internal data with third-party data to provide its customers with access to subscriber data – missing an opportunity to create additional downstream revenue sources. CDS began to go down the path of custom open source development, but found this effort was consuming too much time and too many resources to be sustainable. CDS knew they wanted to leverage the cloud for its cost efficiency and scalability but needed a way to manage and govern their data in the cloud.

Solution: The Zaloni Data Platform on AWS created a managed and governed cloud-based data lake that provided a scalable, centralized repository for internal and third party data. In support of the company’s Customer 360 strategy, the data lake enabled CDS to gather data from all of its systems and manage, track lineage and govern it consistently across the enterprise with a unified data platform. ZDP enabled a stable, reliable foundation on which CDS could implement and customize an operational framework according to their data needs. ZDP also provided an intuitive, user-friendly system that required minimal customization but was fully extensible to meet customer requirements.

Results: Throughout implementation, CDS achieved four times the functionality in 1/2 the time of building in-house. CDS expects to realize significant savings due to faster ramp up to using big data technologies, reduced time to market and the ability to seamlessly scale data management and analytics at the speed of the business.

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