Deploying Data Virtualization at an Enterprise Scale – A Journey towards an Agile, Data-Driven Infrastructure

The Company, being one of the largest multinational companies, with offices, data centers, and fabrication facilities all over the world, developed a heterogeneous ecosystem of tools and technologies over time, giving rise to a complex, distributed data ecosystem. As SaaS applications became mainstream, SaaS adoption within The Company skyrocketed; data oriented nomenclature grew inconsistent across business units, and the office of the CIO was under tremendous pressure to deliver business-friendly, consistent information with the lowest total cost of ownership (TCO), as well as products and services with enterprise grade security and privacy, and the fastest time-to-market (TTM). The physical EDW fell short of its promise. The Company also wanted fast, post-M&A data integration, distribute new selfservice entitlements to downstream acquisition applications, and distribute directory identities to the acquisition directory. The Company also wanted to architect its enterprise data access layer for a single point of entry for HR and supplier data consumption, seamless support for data source migration, and scalable interaction among on-premises and cloud data sources. As its IT culture was not historically suited for reusable information, The Company experienced and egregious misuse of resource time and effort. As challenges became overwhelming, The Company searched for an agile data access solution.

One of the largest semiconductor companies in the world, “The Company” boasts more than 100,000 employees worldwide, including more than 6,000 IT professionals, and The Company operates 61 large data centers around the world. The Company manufactures a wide variety of semiconductors for personal computers, handheld devices, and wearables, and with the proliferation of mobile devices, The Company is redefining the next generation of semiconductor products.