This article looks at different techniques to analyse joiners and leavers using Web Intelligence. Analysing joiners and leavers is where you need to understand the change in membership of a set, for example, products moving in and out of your top 10 sales. If you are able to identify which key products that are dropping in sales you can then adjust your marketing strategy to reverse the trend.
Other scenarios include
Customer analytics – customers can be categorise in terms of gold, silver bronze to indicate whether the customer generates high, medium or low revenue. We can then use joining and leaving analysis to identify which customers are moving between these groups
HR analytics – analysis of employee turnover or once identifying joiners then analysing this group for diversity metrics, for example, is a campaign to recruit more female members of staff working?
Healthcare – analysis of people by age group taking or dropping private healthcare
Two sample Microsoft Access databases come with SAP BusinessObjects Enterprise: eFashion and Club. This article describes the steps involved in migrating the eFashion database to Microsoft SQL Server. The Club database can be migrated in a similar manner. Continue reading →
This article is the first in a series that lists date functions and date manipulation calculations for leading database systems and this article looks at the first of those – Microsoft SQL Server.
Please refer to the other articles in this series on DB2 and Oracle.
Rather than providing a list of all possible calculations I’ve focused on just listing the calculations that I’ve found occur often in a BI reporting or data analysis solution. I haven’t gone into details behind the calculations as this article should be treated as more of a reference than a tutorial and there are plenty of other articles available on the internet that explain in detail how to perform date calculations.