Cloud Analytics starts getting me by the throat in a positive way. Week after week I am discovering the latest capabilities, and week after week I am surprised on how far cloud analytics already got. I already summarized some of the highlights in an earlier article, but there are so many I like to write this part II. And again it is about a number of best practices and tutorials I believe are important to understand.
In this "roadtrip" with SAP BusinessObjects Cloud, I cover the following best practices:
You probably already know that one of the strong points of BusinessObjects Cloud is that is supports the Closed Loop Portfolio of analytics. In one application we can combine business intelligence (monitoring) with business planning (budgeting) and predictive data. Even more, we can simulate how an adjustment to our planning would affect our monitoring and more. To do so, we need to populate our BusinessObjects Cloud model with not only "actual" metrics, but also with our budget data and/or initial forecast. If we have done that, we can create variance reporting (with Hichert - IBCS support) comparing actuals, budget, planning and forecast figures on the fly.
The "trick" here is in correctly loading your data into the SAP BusinessObjects Cloud model, which I explain in detail at this page.
Automated storyboard creation
Imagine you get access to a new data source and quickly want to know what kind of information it stores. Well than the automated story-generator within BusinessObjects Cloud is for you! In three (!) clicks a dashboard automatically generated for you that pitches an overview of your data. A few clicks more to customize that one to your need, delivers you a professional dashboard. Don't know how they do it, but this one rocks ! If you don't believe me, look here.
Everybody loves the cross-chart filtering facility we know from DesignStudio. Did you know it is also available in SAP BusinessObjects Cloud? The video here shows how to do it: the connection between various graphs is driven by the Linked Analysis option. One can choose which of the graphs in your story are affected or even the whole story (including subpages). One step further is the Data Point - option. If you apply this option, the applicable attribute-value(s) filters all of the dependent graphs immediately. This is very useful and for me one of the key visualization options that make me love BusinessObjects Cloud. The video on how to do this, is here.
Decision-Trees and Predictive forecasting
The decision-tree applies a predictive model on your data that shows the correlation of your data's attributes towards the measures. In other words; imagine you want to understand which of your attributes is the strongest influencer on you revenue? Is it the region where your products are sold? Is it the weather, or is it for example the product-category? In the video below I use repair cost as metric to finally discover to an unexpected equipment category is the main influencer. The outcome of the model is in various ways: correlation information, various graphs and charts that can be re-used in your dashboard.
The decison-tree can not only be applied to metrics, it can also be applied to dimensions. In the same video below we use it to create a base and comparison group to use our algorithm finding out a specific manufacturer of spare parts is our main influencer for the majority of our repair costs; we might want to replace this manufacturer and buy our spare-parts somewhere else.
Predictive forecasting is possible using another predictive algorithm that is embedded in SAP BusinessObjects Cloud. Planning based models are the source of the predictive forecasting that further needs of cause a time dimension (monthly as lowest grain) and some historic data to run its triple exponential predictions. The outcome can be applied in a dedicated version of your data and drive your rolling forecast. If that's nt innovation !
Everything is explained in a detailed video that you find here.