Business Intelligence Blog

We have been hearing of Big Data for several months now with definitions that vary depending on the context. In fact, during my analysis of the subject, I was able to determine that the problems of Big Data are the challenges created by the mass of information generated by the information ecosystem affecting the analytical performance required by the company.

There are several factors that favor SAP Xcelsius , the SAP BusinessObjects suite's visualization tool:

• it is easy to use
• the result is attractive
• there are a number of output formats.

However, when we do implementations in businesses, we find that there are certain elements that Xcelsius does a little less well. Fortunately, there are ways to overcome these shortcomings and to continue using this great tool.

This article explains how to solve a problem that often occurs during the making of a dashboard in Xcelcius. The problem lies in the selection / deselection of rows in a scorecard when a new selection is made ​​in another component of the dashboard.  

In last month’s article (Part I) we defined some key indicators that a fitness oriented individual might use on a dashboard. We established the key indicators as being the following:

Xcelsius, one of our favorite tools, is changing names; it is now becoming Dashboard Design. Although few visible changes have been made, some of them sound quite interesting.

Whether you are doing transactional data modeling, dimensional data modeling, Data Vault modeling or object-oriented modeling, all these techniques have one essential thing in common: they include complex entities (facts, dimensions, hubs, classes). One reason for this complexity: instances of these entities go through a life cycle that make then pass by different status (states) when conditions or events occur.

 Defining and segmenting KPIs by examining their relationships

Our goal this month is to start building a strategic map for a simple dashboard. In the process we will see a technique to discover the relationships of the metrics and based on this, how to best monitor their progress. After, we are going to place them along the strategic-tactical-operational axis to classify them in future dashboards.

This article is the fifth in a series of articles discussing the Data Vault modeling approach for data warehousing.

Now that the market has once more « crashed », most companies will want to pare their expenditures to stay afloat and ride out the storm. Others may want to seize the opportunity to gain more market share, but at what cost? The most cost effective way would be to make informed decision based on right-time and validated information coming from a Business Intelligence platform.