When we think about the strategies for increasing analytics adoption, it’s not surprising that we often focus on the front-end analytics technology in terms of ease of use and suitability for business users. A key aspect of this ease of use is the benefit of having analytics embedded in core business applications which was the focus of a blog earlier in the series.
Perhaps the thing we don’t think about so often is the importance of a modern data architecture underpinning the analytics and the role that has to play in driving adoption.
At Infor, we believe that it is crucial that line of business-driven, packaged analytic applications should be built on a flexible and modern data architecture. This is important because the highly differentiated value of a modern analytic application investment isn’t just the out-of-box functionality; it’s also the data and analytics strategy that comes from using the application as a springboard to becoming a data-driven organization.
A flexible and modern data architecture can act as an innovation platform that allows the seamless layering of data and analytics services to differentiate an organization’s business further. In addition, it enables organizations to build on and extend the packaged analytics provided by the vendor.
LOB-driven analytic applications should be delivered on a flexible platform that easily allows customizing pre-built analytics such as changing visualizations, adding new filters, defining new calculations, blending new data sets, and more—all without needing to involve the IT team. And when it comes to extending the pre-built analytics to new data sources, business domains, and analytic techniques such as machine learning and artificial intelligence, it should be effortless for IT to quickly integrate and deliver without the need to procure additional resources or integrate other software.
To learn more about how to increase analytics adoption across your organization, read our best practice guide today.
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