Welcome to Apache™ Hadoop™! Error in SSAS Cube pivot table when creating custom groups - SSAS 2008, Excel 2007. Hi, We have found an extrange behaviour when grouping some dimension members , in an Excel 2007 pivot table connected to a SSAS 2008 perspective. Details: 1. Structure:One cube divided in 8 perspectives. 2. 3. The problem: after it finishes retrieving the data (takes quite a long time), the fields' list is changed! - Some atributes have dissapeared --> cannot continue analysis... - We can see dimensions and measures from other perspectives!!!! I haven't found anything related (this forum, google,...). It's really driving me crazy... Thanks in advance!!!! Grouping members together « Chris Webb's BI Blog.
One of the weaknesses of Analysis Services, in my opinion, is support for creating custom groupings of members. I reckon that 90% of all calculated members on non-measures dimensions must be doing just this, ie just doing an AGGREGATE or SUM over a set of members, and yes calculated members will return the right values but my complaint is something else. It’s that you then have no idea what members were aggregated together inside this calculated member, and that functions like VISUALTOTALS, NONEMPTYCROSSJOIN etc that you would like to be ‘group aware’ of course aren’t. Some examples needed, I think… Consider the following query on Foodmart 2000: WITH MEMBER [Customers]. Wouldn’t it be nice, then if VISUALTOTALS ‘knew’ what was in the set and this query WITH MEMBER [Customers]. returned the same results as this query?
WITH MEMBER [Customers]. Of course this isn’t possible at the moment, because a calculated member could contain any sort of calculation, so AS simply can’t make any assumptions. PowerPivot Workshop - The first PowerPivot course, produced by SQLBI - Tweet #ppws. Web Analytics Blog | Occam's Razor by Avinash Kaushik. Kimball University: Handling Arbitrary Restatements of History > > Intelligent Enterprise: Better Insight for Business Decisions. How do you cope with an executive's request to "bring back a time series of activity for all subscribers who were in platinum status as of X date," or "show me a time series of orders by sales region according to the sales organization as of Y"? Here's how data warehouse pros can cope with the common requirement to look back in time. Most business users of the data warehouse/business intelligence system are content with looking at their information in one of two ways: by the current state of affairs, or by tracking history.
For example, a sales manager developing a sales forecast wants to see sales for his or her region as that region is defined today. But that same sales manager confirming the compensation plan must correctly associate all sales with each salesperson, even if they used to report into a different region. Today's best-practice BI systems are designed for these alternative approaches. But sometimes it's more complicated than that. Manage Changes to Dimension Attributes. Announcing Google Refine 2.0, a power tool for data wranglers.