An analytical application is a form of application software that is being used presently for business reasons. An analytical application main purpose is to progress the performance of the business operations. It falls in the category of business intelligence. Simply put it makes use of the compilation of old data regarding business operations which will facilitate them to provide the firm/businessmen with data and tools which eventually helps them in improving the business functions. They are currently the buzzword in the field of business intelligence.
Predictive analysis forms a part of analytical applications. However; it depends upon the data that is being analyzed and the complexity of the analysis that is be required.
Ideally speaking analytical applications are defined as the split of performance management. And why, the reason being primarily that they associate to the complete analysis of business process which facilitates in decision making. Some of the examples that can be commonly picked up are analysis based on sales pipeline, profitability after adjusting risk analysis and accounts payable analysis.
One of the features of analytical application is automation. Without the feature of automation it can’t be called as an analytical application.
It should be able to read data from a selected system which could be an ERP, CRM or a SCM. It should be read into data warehouse which can be maximized for performance. One should be able to develop all information in the form of reports, scorecards or a dashboard. One should be able to look at the what-if analysis.
In most of the cases the above-mentioned three levels are cautious functions and as far as automation is concerned there is very little automation present here.
The impact of implementing the analytical application
The problem or the only hindrance is the implementation of analytical application. You may need to consider what could be the possible problems that would come after you end up customizing the source systems. The amount of double work can be associated with, when the source systems will be upgraded. Also, in many cases the customization of the same will need more than 20% of primary or the vanilla application you have to be worked over again. This is just few cases, there would be lot many cases where the percentage of reworking can be little higher.
The other possible hindrance would be in the form of data quality. There are bound to be data quality issues. The issues are masked in such a way that it would be very difficult to identify it. It could be in the way the logic is built in the system. Many a time working on the logics and other things will cause a lot of issues and thereby eventually disturbing the timeline of the project.
And also the other thing that you need to know about analytical applications is that they can be a very lengthy process, it might take more time than actually required.
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