Vodafone Germany Customer Data Hub case study

Presented by

Michael Voeller, Product Manager, Vodafone & Gil Trotino, Director Product Marketing, K2View

About this talk

About this talk: Customer data is typically siloed in dozens of applications and data islands, in many different formats and technologies. Many enterprises have invested heavily in various internal and commercial solutions with the aim of delivering a real-time, single view of the customer in order to improve customer experience and support innovative business initiatives. Most of them have failed. Join this webinar to learn how Vodafone Germany has successfully implemented a Customer Data Hub (CDH), which unifies customer interactions, transactions, and master data, across dozens of data sources, to serve both operational and analytical workloads. Agenda: * The Customer 360 challenge * K2View data product platform * Key steps and lessons learnt in building a real-time Customer Data Hub

Related topics:

More from this channel

Upcoming talks (1)
On-demand talks (13)
Subscribers (3611)
At K2View, we believe that every company should be able to liberate and elevate its data to deliver the most personalized and profitable customer experience in its industry, while being innovative and radically agile. With K2View, companies manage data in a whole new way, using a business lens: they create data products that continually sync, transform, and serve data from siloed source systems – delivering a real-time, holistic view of any business entity to any data consumer. Our Data Product Platform fuels operational and analytical workloads, at enterprise scale. It deploys as a data fabric, data mesh, or data hub - in an on-premises, cloud, or a hybrid architecture - in a matter of weeks, and adapts to change on the fly. The most data-intensive companies in the world, including AT&T, Verizon, American Express, Vodafone, and Hertz trust K2View Data Product Platform for their operational use cases - spanning Customer 360, cloud migration, test data management, data tokenization, and legacy application modernization.