Effective analytics – with or without the cloud

Developing a meaningful business analytics strategy is a challenge for many organisations – especially those that are concerned about security. Bob Bedard from deFacto Global says that there is now a range of solutions that can help, either on-premise or in the cloud

By Guest on 18 August 2016
Effective analytics – with or without the cloud

This article first appeared in the Summer 2016 issue of The Record.

Business analytics and the cloud are undeniably two naturally compatible offerings. But not all users of business analytics are enamoured with the cloud. This is because security remains a major concern for many larger companies, especially those that are highly regulated or publicly traded. While these companies may be willing to entrust their marketing or business operations data to the cloud, they cautiously choose to restrict their core financial data to on-premise solutions. 

What’s more, although marketing or operations managers use business analytics for predictive analytics, they still depend on CRM, ERP, and budgeting and planning systems to address the ‘last mile’ problem – the ability to request, process, and deliver forecasts to business users in the timeframe and business context they need to make timely decisions. 

With the introduction of R-scripting support in SQL 2016 and Azure Machine Learning, Microsoft customers now have two excellent alternative ways for business users to tap into business analytics capabilities, either on-premise or in the cloud. More risk-averse companies can get started with SQL 2016 to perform predictive forecasting. They can stop there or seamlessly migrate to the more capable Azure Machine Learning platform based on their need for higher performance or added capabilities to support more sophisticated applications, if and when they feel comfortable.

The ‘last mile’ problem is best left in the hands of vendors that are able to seamlessly integrate predictive analytics capabilities into their core offering. Microsoft CRM and Dynamics AX have begun to integrate machine learning (ML) capabilities into their platforms. Microsoft ISV partners, like deFacto Global, can take the same approach and enable their offerings with more intelligent analytics. 

deFacto Global has introduced the first Predictive Financial Forecasting solution based on Microsoft ML that can enable customers to take advantage of the capabilities offered by Azure ML and SQL 2016. Both approaches enable users to deploy predictive financial forecasting to achieve similar results quickly and easily. It gives CFOs, finance analysts, and business unit managers the ability to perform budgeting, analysis, and forecasting using predictive analytics just as easily as they have been doing with their traditional methods, enabling all of these business planners to realise increased accuracy and significant operational advances.  

Bob Bedard is president and CEO at deFacto Global



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