On September 10, 2013, Workday, Inc. announced Big Data Analytics (http://www NULL.workday NULL.com/company/news/press_archive/workday_delivers_big_data_analytics_for_hr_and_finance NULL.php), its entry into the market for Business Intelligence (BI) applications for enterprise business and comparably sized organizations in the public and not-for-profit sectors.
Much of the promotional information on the product echoes the same themes on which competitors for this market (Microsoft®, Oracle®, IBM®) frame their own communications:
- Big Data Analytics is designed to empower Lines of Business (LoBs) to design BI efforts genuinely capable of producing the results they’re after, without a lot of support from central IT organizations
- The User interface is managed by pointing a mouse and clicking on options, without any need for programming
- The application produces the dials and charts management has come to expect of BI dashboards
- Workday and non Workday data can be included to provide a panoramic scope for data analysis
A big difference can be found on the backend. This Workday application is built on Hadoop (http://hadoop NULL.apache NULL.org), in striking contrast to each of its BI competitors who may promote offers for Hadoop, but are much better known for their own proprietary backends.
Looking further into this point, I need to note a further distinction: Hadoop is built to manage unstructured data without a Relational Database Management System (RDBMS) architecture. Whether one considers Microsoft’s SQL Server, or IBM’s DB2, etc, one needs to note each of these competitive solutions is, in fact, an RDBMS. So the likely usefulness of Workday’s Big Data Analytics as a tool for analyzing online content, email messages, chat logs, etc. is going to be far superior to the competition.
Of course, Workday’s Big Data Analytics product also promises much better support for smart phones and tablets. The Workday workspace is a cloud Software as a Service (SaaS) offering, so any device equipped with a modern web browser can be used to work with the SaaS application. But I also need to note the application can be used with Microsoft Excel, so organizations with a commitment to Power Pivot should be fine simply bolting on Big Data Analytics to the same analytics platform.
Ira Michael Blonder (https://plus NULL.google NULL.com/108970003169613491972/posts?tab=XX?rel=author)
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