如何在时间维度上对非事实事实表进行切片？ (SSAS)
从惯例开始——“请原谅，因为这是我的第一篇文章，我是一个相对初学者”的免责声明，我有以下问题......
我为一个非营利性的竞选组织工作，我已经建立了一个 SSAS衡量一组活动家（客户）采取的活动行动（例如向总理发送电子邮件）的解决方案主要事实表以行动计数作为其衡量标准，并且可以按时间和地理位置进行切片......
但我还希望有另一个无事实的事实表，可以显示有多少活动家在哪个邮件段...所以我认为我需要做的基本上是转储我的活动家维度的副本（对于搬家的人来说，这正在慢慢改变）地理等）进入其自己的事实事实表...列是FK_campaigner，segment_id，start_date，end_date，但是我如何将其链接到时间维度，因为它没有FK_time（仅是开始和结束时间）..我想我想要做的是将非事实表与“当 PK_time > 时”的时间表相关联。开始日期和 < end_date”然后为我切片...但是如何？这可能吗？或者我是否必须沿着某人在某段中的每一天加载一个事实的路线？
非常感谢任何可以指出我正确方向的人方向要么是结构性的（广泛的方法是错误的吗？），要么是在 SSAS 中实际执行的实用性更好..
AJ
Starting with the customary - "please excuse me as this is my first post and i'm a relative beginner" disclaimer, i have the following question...
I work for a not for profit campaigning organisation, I've set up an SSAS solution to measure campaigning actions (e.g emailing the priminister) taken by a set on campaigners (customers) the main fact table has a count of actions as its measure, and is sliceable by say time and geography....
... but I also want to have another factless fact table that can show a count of how many campaigners are in what mailing segment... so i think what i need to do is basically dump a copy of my campaigner dimesion (which is slowly changing for people moving geography etc) into its own factless fact table... columns being FK_campaigner, segment_id, start_date, end_date but then how do i link that into the time dimension as it doesn't have an FK_time (merely a start and end time)... i guess what i want to do is relate the factless table to the time table on a "when PK_time > start_date and < end_date" then slice for me... but HOW? and is this possible or do i have to go down the route of loading one fact for each day that someone was in a segment?
many thanks to anybody who can point me in the right direction either structurally (is the broad approach wrong?) or even better in the practicalities of actually doing it in SSAS..
AJ
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如果您只想分析单个时间点的数据，例如显示我的数字在 x 点的样子。然后你可以将时间维度作为“生效日期”。
这将是半相加的，您将无法跨时间聚合数据。
但是，如果您感兴趣的是分析时间段之间的过渡，那么有一个“多对多”解决方案可以实现：
多对多革命白皮书
该白皮书提供了几种模型与您的场景相关的是“跨时间”或“转换矩阵”
祝你好运
If you just want to analyse this data for a single point in time e.g. show me what what my numbers looked like at point x. Then you could have the time dimension be the "effective date" .
This would be semi additive and you would not be able to aggregate the data across time.
However, if what you interested in is analyzing the transition between time periods, than there is a "Many to Many" solution that would allow this:
Many to Many revolution white paper
The whitepaper provides several models the one that would be relevant in your scenario would be either the "Cross Time" or "Transition Matrix"
Good luck