As a provider of software-as-a-service (SaaS) applications for both human resources and finance departments, Workday is in a unique position that enables it to compare lots of data. At a Workday Rising 2017 conference today, Workday announced the limited availability of a Workday Prism Analytics service that enables organizations to analyze data residing in Workday […]
As a provider of software-as-a-service (SaaS) applications for both human resources and finance departments, Workday is in a unique position that enables it to compare lots of data. At a Workday Rising 2017 conference today, Workday announced the limited availability of a Workday Prism Analytics service that enables organizations to analyze data residing in Workday SaaS applications as well as third-party data. Workday Prism Analytics spans data preparation, data integration, data discovery and analytics running on top of a core engine that Workday manages as a service.
Dan Beck, senior vice president of technology platform for Workday, says Workday Prism Analytics leverages the open REST application programming interfaces (APIs) that Workday infused into a Workday Cloud platform-as-a-service (PaaS) environment to make it possible to analyze the data stored in external data sources alongside Workday SaaS applications. Both Workday Prism and Workday Cloud Platform are expected to be generally available in 2018.
Workday today also announced its first Workday Data-as-a-Service, a cloud-based offering through which it will provide complementary capabilities such as key performance indicators (KPIs) and other benchmarks with which organizations can compare how they are performing versus other organizations using Workday SaaS applications.
“We’re see our open APIs as a building block,” says Beck.
Like most providers of SaaS applications, Workday is exploring ways to deliver more value from the data it collects. Those efforts include everything from analyzing customer data to providing anonymized comparisons. Eventually, that data will also be used to fuel a variety of machine and deep learning algorithms to automate many routine business processes.
In the meantime, IT organizations will need to soon come to terms with what capabilities they can provide by deploying applications on-premises versus what SaaS application providers are soon going to be able to provide, thanks to a level of scale an internal IT organization can’t match.
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Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.
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