Power BI 的零售分析範例教學Retail Analysis sample for Power BI: Take a tour

這個產業範例的儀表板、基礎資料集和報表,會分析在多個門市和區域售出之品項的零售資料。This industry sample dashboard and underlying report analyze retail sales data of items sold across multiple stores and districts. 計量會比較今年與去年在以下領域的表現:銷售、單位、毛利率和變異數,以及新門市分析。The metrics compare this year’s performance to last year’s in these areas: sales, units, gross margin, and variance, as well as new store analysis. 此為來自 obviEnce 的匿名真實資料 (www.obvience.com)。This is real data from obviEnce (www.obvience.com) that has been anonymized.

[!Note] 您也可以只下載此範例的資料集 (Excel 活頁簿).You can also download just the dataset (Excel workbook) for this sample. 活頁簿包含您可檢視和修改的 Power View 工作表。The workbook contains Power View sheets that you can view and modify. 若要查看未經處理的資料,請選取 [Power Pivot] > [管理]。To see the raw data select Power Pivot > Manage.

進入儀表板,然後開啟報表Start on the dashboard and open the report

  1. 在儀表板中選取 [所有門市] 磚:On the dashboard, select the "Total Stores" tile:

    這會帶您前往報表中的 [銷售門市概觀] 頁面。This takes you to the "Store Sales Overview" page in the report. 您會看到我們總共有 104 個門市,其中 10 個為新門市。You see we have 104 total stores, 10 of them new. 我們有兩種連鎖店:Fashions Direct 和 Lindseys。We have two chains, Fashions Direct and Lindseys. Fashions Direct 的門市通常比較大。Fashions Direct stores are larger on average.

  2. 在圓形圖中選取 [Fashions Direct]。In the pie chart, select Fashions Direct.

    請注意泡泡圖中的結果:Notice the result in the bubble chart:

    FD-01 區有每平方英呎最高的平均銷售額,FD-02 區與去年相比的變異數最低,FD-03 區和 FD-04 區的整體表現最差。FD-01 district has the highest Average Sales per Square Foot, FD-02 has the lowest Variance in Sales compared to last year, FD-03 and FD-04 are worst performers overall.

  3. 選取個別泡泡或其他圖表,即可查看交叉醒目提示,呈現您選取範圍的影響。Select individual bubbles or other charts to see cross highlighting, revealing the impact of your selections.
  4. 若要返回儀表板,請從上方導覽列 (階層連結) 選取其名稱。To return to the dashboard, select its name from the top navbar (breadcrumbs).

  5. 在儀表板中選取標題為「本年度銷售量」的磚。On the dashboard, select the tile that has "This Year’s Sales."

    這等同於在問題方塊中輸入「本年度銷售量」。This is equivalent to typing "This year sales" in the question box.

    您會看到這個畫面:You see this screen:

檢閱為 Power BI 問與答所建立的磚Review a tile created with Power BI Q&A

讓我們詳加說明。Let’s get more specific.

  1. 在問題中加入「 依區域的本年度銷售量」。Add “this year sales by district” onto the question. 觀察結果,您會發現答案自動呈現在橫條圖中,並建議其他片語:Observe the result: It automatically put the answer in a bar chart and suggests other phrases:

  2. 現在將問題改為「 依郵遞區號和連鎖店的本年度銷售量」。Now change the question to “this year sales by zip and chain”.

    請注意當您輸入適當的圖表時,它會如何回答。Notice how it answers the question as you type with the appropriate charts.

  3. 試問更多問題,看看會得到何種結果。Play around with more questions and see what kind of results you get.
  4. 當您準備好時,請返回儀表板。When you’re ready, return to the dashboard.

深入探索資料Dive deeper into the data

現在探討更詳細的層面,我們來查看區域的表現。Now let's explore on a more detailed level, looking at the districts' performances.

  1. 在儀表板上,選取比較本年度和去年度銷售量的圖格。On the dashboard, select the tile comparing this year's sales to last year’s.

    請注意去年在差異 % 上有很大的變動,1 月、4 月和 7 月都是狀況特別不好的月份。Notice the large variability on Variance % to last year, with Jan, Apr, and Jul being particularly bad months.

    現在來看看是否可以縮小範圍,找出問題所在。Let’s see if we can narrow down where the issues might be.

  2. 選取泡泡圖,然後選擇 [020-Mens] 。Select the bubble chart, and choose 020-Mens.

    您會觀察到,男性類別在 4 月並沒有像整體生意那樣受到嚴重影響,但 1 月和 7 月仍是有問題的月份。Observe the men's category wasn't as severely affected in April as the business overall, but January and July were still problem months.

  3. 現在選取 [010-Womens] 泡泡。Now, select the 010-Womens’ bubble.

    請注意,女性類別在所有月份的表現都比整體生意更差,而且每個月的表現幾乎也都不如去年。Notice the women's category performed much worse than business overall across all months, and much worse in almost every month compared to the previous year.

  4. 再次選取泡泡即可清除篩選條件。Select the bubble again to clear the filter.

試用交叉分析篩選器Try out the slicer

我們來看一看特定區域的表現。Let’s look at how specific districts are doing.

  1. 在左上方的交叉分析篩選器中選取 [Allan Guinot]。Select Allan Guinot in the slicer on the top left.

    請注意 Allan 的區域在 3 月和 6 月的表現優於去年。Note that Allan’s district outperformed Last Year in March and June.

  2. 現在在已選取 Allan 的狀態下,按一下女性的泡泡。Now, while Allan is still selected, select the Women’s bubble.

    請注意對於女性類別,他的區域從未達到去年營業額。Note that for the Women’s category, his district never met last year’s volume.

  3. 探索其他區域的經理和商品類別狀況 – 您可找出其他的深入資訊嗎?Explore the other district managers and categories – what other insights can you find?
  4. 當您準備好時,請返回儀表板。When you are ready – return to the dashboard.

從資料中,我們了解到本年度銷售成長隱藏了哪些含意?What is our data telling us about sales growth this year?

我們要探討的最後一個領域是我們的成長 – 本年度新開的門市。The last area we want to explore is our growth – new stores opened this year.

  1. 選取 [本年度新開門市] 圖格。Select the 'Stores Opened This Year’ tile.

    如圖格顯示,本年度開張的 Fashions Direct 門市比 Lindseys 門市更多。As evident from the tile – more Fashions Direct stores than Lindseys stores opened this year.

  2. 觀察「依名稱的每平方英尺銷售量」圖表:Observe the 'Sales Per Sq Ft by Name' chart:

    各家新門市在「平均每平方英尺銷售量」上的差異相當大。There is quite a bit of difference in Average Sales per SQF across the new stores.

  3. 按一下右上方圖表中的 Fashions Direct 圖例項目。Click on the Fashions Direct legend item in the top right chart. 請注意即使是同一系列的連鎖店,最佳門市 (Fashions Direct 溫徹斯特店) 的表現顯著優於最差門市 (Fashions Direct 辛辛那提 2 號店),分別是 $21.22 美元及 $12.86 美元。Notice, even for the same chain, the best store (Winchester Fashions Direct) significantly outperforms the worst store (Cincinnati 2 Fashions Direct) $21.22 vs $12.86 respectively.

  4. 按一下交叉分析篩選器中的 Fashions Direct 溫徹斯特店,然後觀察折線圖。Click Winchester Fashions Direct in the slicer and observe the line chart. 第一個銷售數字在二月報告。The first sales numbers were reported in February.
  5. 按一下交叉分析篩選器中的 Fashions Direct 辛辛那提 2 號店,折線圖中顯示該門市於 6 月開幕,似乎是表現最差的門市。Click on Cincinnati 2 Fashions Direct in the slicer and you will see in the line chart that it was opened in June and it seems to be the worst performing store.
  6. 請和之前一樣,在其他長條、折線和泡泡上按一下,看看您可以找到哪些深入資訊。As before, explore by clicking on other bars, lines and bubbles throughout the charts and see what insights you can discover.

這是安全的作業環境。This is a safe environment to play in. 您一律可以選擇不儲存變更。You can always choose not to save your changes. 但如果儲存了變更,您也可以隨時移至 [取得資料],重新複製此範例。But if you do save them, you can always go to Get Data for a new copy of this sample.

連線到您的資料Connect to your data

希望本教學已讓您了解 Power BI 儀表板、問與答和報表能夠如何提供零售資料的深入資訊。We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into retail data. 現在輪到您了 — 連接到您自己的資料。Now it’s your turn — connect to your own data. 您可以透過 Power BI 連接到各式各樣的資料來源。With Power BI you can connect to a wide variety of data sources. 深入了解開始使用 Power BI.Learn more about getting started with Power BI.

後續步驟Next steps