dax

I am trying to get percentage difference with month and year using DAX function Month Year records Jan 2015 100 Feb 2015 120 Mar 2015 140 Apr 2015 160 and I am trying to calculate percentage diff in a new column Month Year records %change Jan 2015 100 0% Feb 2015 120 20% Mar 2015 140 17.02% Apr 2015 180 22%.03 In your current setup, something like this could work. Using a datetable would be better and easier though. %change = VAR StartLastMonth = ( DATE ( 'table'[Year], 'table'[Month] - 1, 1 ) ) VAR RecordsLastMonth = CALCULATE ( MAX ( 'table'[Records] ), FILTER ( 'table', 'table'[Year] = YEAR

We are building a PowerBI reporting solution and I (well Stack) solved one problem and the business came up with a new reporting idea. Not sure of the best way to approach it as I know very little about PowerBI and the business seems to want quite complex reports. We have two sequences of events from separate data sources. They both contain independent events occurring to vehicles. One describes what location a vehicle is within - the other describes incident events which have a reason code for the incident. The business wants to report on time spent in each location for each reason. Vehicles

时间是数据分析中经常使用的条件，通常情况下在DAX中对时间列有以下几种常见处理情况。 将数字列转换成时间列 有些原始数据对时间的存储采用了纯数字形式，例如用20170122表示2017年1月22日。但是采用这种存储方式的数据列在导入到Power BI中会被认为是整数类型，将无法自动转换成日期格式，就不能做时间相关运算。 要解决该问题，有两种思路，一种是在数字形式的日期上添加反斜杠“/”，将年月日分开。例如将20170122变成2017/02/22，之后就能被Power BI自动识别转换成日期格式了。 转换方式可以用一下DAX完成： DateFormat = LEFT (Store[ Date ], 4 )& "/" & MID (Store[ Date ], 5 , 2 )& "/" & RIGHT (Store[ Date ], 2 ) 另外一种方式是调用DATE函数，直接将数字类型转换成日期时间类型。 DateTime = DATE ( INT ( LEFT (Store[ Date ], 4 )), INT ( MID (Store[ Date ], 5 , 2 )), INT ( RIGHT (Store[ Date ], 2 ))) 基于表单日期列创建日历 在用DAX做很多时间相关的数据分析时都需要一个单独的日历表单来作为分析基准。这个日历表需要满足以下条件：

表连接是指两张表根据关联字段，组合成一个数据集。表连接不仅可以利用数据模型中已有的关系，而且可以利用DAX表达式基于表的任意列定义连接条件。因此，在DAX中，实现表与表之间的连接，有两种方式： 第一种方式：利用数据模型中的现有关系，以便查询包含在不同表中的数据。 第二种方式：编写 DAX 表达式创建连接，以生成与关系等效的效果。 一，利用数据模型中的关系（左外连接） 利用数据模型中的关系来连接表，是DAX中最常用的行为， 关系隐式实现外连接(LEFT JOIN) 例如，FactSales和DimProduct、FactSales和DimDate之间存在多对一的关系，可以利用关系来建立左外连接（LEFT OUTER JOIN），注意，左外联接的左表（保留表）是FactSales，右表是DimDate和DimProduct，这意味着，如果FactSales表中存在的数据不包含在DimProduct或DimDate表中，那么这些数据行都被分到Color为空值（BLANK）或CalendarYear为空值的分组中。 SUMMARIZE(FactSales,DimProduct[Color],DimDate[CalendarYear],"SalesAmount",SUM(FactSales[SalesAmount])) 该DAX表达式等价于以下TSQL脚本， select p.Color

I have been working on Power BI for a while now and I often get confused when I browse through help topics of it. They often refer to the functions and formulas being used as DAX functions or Power Query, but I am unable to tell the difference between these two. Please guide me. M and DAX are two completely different languages. M is used in Power Query (a.k.a. Get & Transform in Excel 2016) and the query tool for Power BI Desktop. Its functions and syntax are very different from Excel worksheet functions. M is a mashup query language used to query a multitude of data sources. It contains

I need a DAX measure which shows me a flag (1 or 0) if a customer (DimCustomer) bought the product "A" someday (for the first time) and later (doesn't matter when) have bought or product "B" or "C". Measure1: Flag (1 or 0) in their customer names if bought Measure2: When was the first time that they bought product B or C Basicly I have a FactSales, DimCustomer, DimDate and Dimproduct Can someone help me? 来源： https://stackoverflow.com/questions/51948638/dax-measure-if-client-has-bought-product-a-or-b-later

Using DAX to identify first instance of a record I'm faced with trying to identify the first instance in a database where someone (identified by the ID column) has purchased a product for the first time. It's possible for said person to purchase the product multiple times on different days, or purchase different products on the same day. I drummed up an excel formula that gets me there, but am having trouble translating into DAX. =COUNTIFS(ID,ID,PurchaseDate,"<="&PurchaseDate,Product,Product) Which results in the correct values in the "First Instance?" Column. Ideally I won't have to hardcode