itsnotaboutthecell 2024-08-11 19:39:20 -05:00
Родитель 17b20fa7c9 f961e1f79f
Коммит a4bb7b3eed
4 изменённых файлов: 106 добавлений и 4 удалений

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@ -122,7 +122,7 @@ It is also recommend to strive to deliver the **right number of tables** with th
| ☑ | FactOnlineSales (StoreKey) | DimStore (StoreKey) | Many to one (*:1) | ☑ | Single |
| ☑ | FactOnlineSales (DateKey) | DimDate (DateKey) | Many to one (*:1) | ☑ | Single |
| | FactOnlineSales (DeliveryDate) | DimDate (DateKey) | Many to one (*:1) | ☑ | Single |
| ☑ | DimStore (StoreKey) | DimEmployee (StoreKey) | Many to one (*:1) | ☑ | Both |
| ☑ | DimEmployee (StoreKey) | DimStore (StoreKey) | Many to one (*:1) | ☑ | Both |
The following image shows a finished view of the semantic model with all the created relationships included.
@ -189,7 +189,7 @@ Learn more about [time intelligence functions](https://learn.microsoft.com/dax/t
1. To add a **[Total Sales SPLY]** measure, leveraging our **DimDate** table and our DateKey column, select the **FactOnlineSales** table in the Tables list. On the Home tab, select **New measure** and in the formula editor, copy and paste or type the following measure to calculate the total sales amount. Select the **check mark** to commit.
```dax
CALCULATE([Total Sales Amount], SAMEPERIODLASTYEAR(Calendar[DateKey]))
Total Sales SPLY = CALCULATE([Total Sales Amount], SAMEPERIODLASTYEAR(DimDate[DateKey]))
```
> [!NOTE]
@ -246,7 +246,7 @@ An important aspect of data modeling is usability and extending our semantic mod
The Row label property is a field that identifies the column that represents a single row in a table. As an example, the Row label property can be used to ensure that two users with the same name are not aggregated into a single record. By setting the Row label property to a field in your data that uniquely identifies each user, such as an ID number, you can keep their records separate.
1. From the **Data** pane select the **DimEmployee** table and within the **Properties** pane set the **Row label** to the **FullName** field.
1. From the **Data** pane select the **DimEmployee** table and within the **Properties** pane set the **Row label** to the **EmployeeKey** field.
![Row label](./Media/row-label.png)
@ -285,7 +285,7 @@ Data categorization is a feature in Power BI that allows you to specify the data
| Field | Data category |
| :--- | :--- |
| RegionCountryName | Country/Region |
| StateProvinceName | State of Province |
| StateProvinceName | State or Province |
![Region category](./Media/data-category.png)

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@ -736,3 +736,6 @@ This part of the lab has demonstrated how dataflows can help you prepare data in
# Completed files
To download the completed files from the lab instructions:
```text
https://github.com/microsoft/pbiworkshops/raw/main/Day%20After%20Dashboard%20in%20a%20Day/Source_Files/DayAfterDataflow.pqt
```

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Day After Dashboard in a Day/Source_Files/DayAfterDataflow.pqt Normal file

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1
Chevrolet
Silverado 2500 HD Extended Cab
2001
2
Suzuki
Grand Vitara
2000
3
Chevrolet
Silverado 1500 Regular Cab
2011
4
Ford
Explorer
2010
5
Acura
RL
2008
6
Chevrolet
Astro Cargo
1992
7
MAZDA
MX-5 Miata
1992
8
Toyota
FJ Cruiser
2008
9
Audi
RS 7
2015
10
Nissan
Rogue
2015
11
Lexus
GX
2012
12
MAZDA
B-Series Regular Cab
1996
13
Kia
Rio
2016
14
Volvo
S90
1997
15
Nissan
240SX
1996
16
Audi
A6
2011
17
Audi
A7
2019
18
Chevrolet
Colorado Extended Cab
2019
19
Chrysler
Fifth Ave
1993
20
Oldsmobile
Achieva
1997
1 1
2 Chevrolet
3 Silverado 2500 HD Extended Cab
4 2001
5 2
6 Suzuki
7 Grand Vitara
8 2000
9 3
10 Chevrolet
11 Silverado 1500 Regular Cab
12 2011
13 4
14 Ford
15 Explorer
16 2010
17 5
18 Acura
19 RL
20 2008
21 6
22 Chevrolet
23 Astro Cargo
24 1992
25 7
26 MAZDA
27 MX-5 Miata
28 1992
29 8
30 Toyota
31 FJ Cruiser
32 2008
33 9
34 Audi
35 RS 7
36 2015
37 10
38 Nissan
39 Rogue
40 2015
41 11
42 Lexus
43 GX
44 2012
45 12
46 MAZDA
47 B-Series Regular Cab
48 1996
49 13
50 Kia
51 Rio
52 2016
53 14
54 Volvo
55 S90
56 1997
57 15
58 Nissan
59 240SX
60 1996
61 16
62 Audi
63 A6
64 2011
65 17
66 Audi
67 A7
68 2019
69 18
70 Chevrolet
71 Colorado Extended Cab
72 2019
73 19
74 Chrysler
75 Fifth Ave
76 1993
77 20
78 Oldsmobile
79 Achieva
80 1997