Power BI 的零售分析示例:教程Retail Analysis sample for Power BI: Take a tour

此行业示例仪表板和基础报表分析了跨多个商店和地区销售的商品的零售数据。This industry sample dashboard and underlying report analyze retail sales data of items sold across multiple stores and districts. 指标将本年度的绩效与去年在以下领域的绩效进行比较:销售、单位、毛利和方差,以及新店铺分析。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. 这些来自 obviEnce (www.obvience.com) 的真实数据都已进行匿名处理。This is real data from obviEnce (www.obvience.com) that has been anonymized.

先决条件Prerequisites

必须先将示例下载为内容包、.pbix 文件或 Excel 工作簿,然后才能使用它。Before you can use the sample, you must first download it as a content pack, .pbix file, or Excel workbook.

获取内容包形式的此示例Get the content pack for this sample

  1. 打开并登录 Power BI 服务 (app.powerbi.com)。Open the Power BI service (app.powerbi.com) and log in.
  2. 在左下角,选择“获取数据”。In the bottom left corner select Get data.

  3. 在显示的“获取数据”页上选择“示例”图标。On the Get Data page that appears, select the Samples icon.

  4. 依次选择“零售分析示例”和“连接”。Select the Retail Analysis Sample, then choose Connect.

    零售分析示例

  5. Power BI 导入内容包,并将新的仪表板、报表和数据集添加到当前工作区。Power BI imports the content pack and adds a new dashboard, report, and dataset to your current workspace. 新的内容会以黄色星号标记。The new content is marked with a yellow asterisk.

    零售分析示例

获取 .pbix 文件形式的此示例Get the .pbix file for this sample

也可以将此示例下载为 .pbix 文件,这是专为 Power BI Desktop 量身定制的文件格式。Alternatively, you can download the sample as a .pbix file, which is designed for use with Power BI Desktop.

获取 Excel 工作簿形式的此示例Get the Excel workbook for this sample

还可以针对此示例仅下载该数据集(Excel 工作簿)You can also download just the dataset (Excel workbook) for this sample. 该工作簿包含你可以查看和修改的 Power View 工作表。The workbook contains Power View sheets that you can view and modify. 若要查看原始数据,请选择“Power Pivot”>“管理”。To see the raw data select Power Pivot > Manage.

启动仪表板并打开报表Start on the dashboard and open the report

  1. 在仪表板上,选择“总商店数”磁贴:On the dashboard, select the "Total Stores" tile:

    此时,会转到报表中的“商店销售额概述”页面。This takes you to the "Store Sales Overview" page in the report. 你会看到我们总共有 104 家商店,其中 10 家为新店铺。You see we have 104 total stores, 10 of them new. 我们有两个供应链,Fashions Direct 和 Lindseys。We have two chains, Fashions Direct and Lindseys. Fashions Direct 商店平均面积要大一些。Fashions Direct stores are larger on average.

  2. 在饼图中,选择“Fashions Direc”。In the pie chart, select Fashions Direct.

    请注意气泡图中的结果:Notice the result in the bubble chart:

    FD-01 地区每平方英尺的平均销售额最高,FD-02 与去年相比销售额方差最低,FD-03 和 FD-04 总体绩效最差。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. 选择单个气泡或其他图表以查看交叉突出显示,从而透露你选择的影响。Select individual bubbles or other charts to see cross highlighting, revealing the impact of your selections.
  4. 若要返回到仪表板,请从顶部导航栏(痕迹导航)中选择其名称。To return to the dashboard, select its name from the top navbar (breadcrumbs).

  5. 在仪表板上,选择具有“本年度销售额”的磁贴。On the dashboard, select the tile that has "This Year’s Sales."

    这相当于在问题框中键入“本年度销售额”。This is equivalent to typing "This year sales" in the question box.

    你会看到如下屏幕:You see this screen:

查看使用 Power BI 问答创建的磁贴Review a tile created with Power BI Q&A

我们将更具体地进行说明。Let’s get more specific.

  1. 将“按地区划分本年度销售额”添加到问题中。Add “this year sales by district” onto the question. 观察结果:它会自动将答案放在条形图中,并建议其他短语:Observe the result: It automatically put the answer in a bar chart and suggests other phrases:

  2. 现在,将问题更改为“按邮编和供应链划分本年度销售额”。Now change the question to “this year sales by zip and chain”.

    注意你采用相应图表键入时问题答案有何不同。Notice how it answers the question as you type with the appropriate charts.

  3. 浏览更多问题并查看所获得的结果类别。Play around with more questions and see what kind of results you get.
  4. 准备好后,返回到仪表板。When you’re ready, return to the dashboard.

深入了解数据Dive deeper into the data

现在,让我们更详细地浏览下结果,了解下各地区的绩效。Now let's explore on a more detailed level, looking at the districts' performances.

  1. 在仪表板上,选择将本年度销售额与去年作比较的磁贴。On the dashboard, select the tile comparing this year's sales to last year’s.

    请注意与去年相比最大的方差变化,1 月、4 月和 7 月尤其差。Notice the large variability on Variance % to last year, with Jan, Apr, and Jul being particularly bad months.

    我们来看看是否可以缩小问题范围。Let’s see if we can narrow down where the issues might be.

  2. 选择气泡图,然后选择“020-男性”。Select the bubble chart, and choose 020-Mens.

    观察到男性类别在 4 月的影响不如整体业务严重,但是 1 月和 7 月仍是问题月。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. 现在,选择“010-女性气泡”。Now, select the 010-Womens’ bubble.

    注意,女性类别在所有月份的表现都比整体业务糟糕许多,并且与去年相比,几乎每个月都更糟。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. 再次选择气泡以清除筛选器。Select the bubble again to clear the filter.

尝试切片器Try out the slicer

让我们来看看具体地区的情况。Let’s look at how specific districts are doing.

  1. 在左上角的切片器中选择 Allan Guinot。Select Allan Guinot in the slicer on the top left.

    注意,Allan 地区在 3 月 和 6 月的表现都超过去年。Note that Allan’s district outperformed Last Year in March and June.

  2. 现在,虽然仍选择 Allan,请选中女性的气泡。Now, while Allan is still selected, select the Women’s bubble.

    注意,对于女性的类别,他所负责的地区始终未达到去年的量。Note that for the Women’s category, his district never met last year’s volume.

  3. 探索其他地区经理和类别,可以发现其他什么见解?Explore the other district managers and categories – what other insights can you find?
  4. 准备好后 – 返回到仪表板。When you are ready – return to the dashboard.

数据显示本年度的销售增长是怎样的?What is our data telling us about sales growth this year?

我们最不想了解的就是增长 – 今年新开了很多商店。The last area we want to explore is our growth – new stores opened this year.

  1. 选择“今年开业的商店”磁贴。Select the 'Stores Opened This Year’ tile.

    显而易见 – 今年开业的 Fashions Direct 商店比 Lindseys 商店多。As evident from the tile – more Fashions Direct stores than Lindseys stores opened this year.

  2. 观察“按名称划分每平方英尺的销售额”图表:Observe the 'Sales Per Sq Ft by Name' chart:

    新商店中每平方英尺的平均销售额有很大差异。There is quite a bit of difference in Average Sales per SQF across the new stores.

  3. 在右下角的图表中单击 Fashions Direct 图例项。Click on the Fashions Direct legend item in the top right chart. 注意,即使针对同一个供应链,最好的商店 (Winchester Fashions Direct) 表现明显比最差的商店 (Cincinnati 2 Fashions Direct) 要好,分别是 21.22 美元与 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. 在切片器中单击 Winchester Fashions Direct,观察折线图。Click Winchester Fashions Direct in the slicer and observe the line chart. 2 月份报告的第一批销售数字。The first sales numbers were reported in February.
  5. 在切片器中单击 Cincinnati 2 Fashions Direct,你将会在折线图中看到它于 6 月开业,似乎是表现最不好的店。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. 和前面一样,通过单击图表中的其他条、线和气泡来了解情况,看看你能发现什么见解。As before, explore by clicking on other bars, lines and bubbles throughout the charts and see what insights you can discover.

这是一个安全的试验环境。This is a safe environment to play in. 你可以始终选择不保存所做的更改。You can always choose not to save your changes. 但是,如果保存更改,则可以始终转到“获取数据”来获得本示例的新副本。But if you do save them, you can always go to Get Data for a new copy of this sample.

连接到数据Connect to your data

我们希望本教程已经演示 Power BI 仪表板、问题解答和报表如何能够帮助深入了解零售数据。We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into retail data. 现在轮到你了 — 连接到你自己的数据Now it’s your turn — connect to your own data. 借助 Power BI,你可以连接到各种数据源。With Power BI you can connect to a wide variety of data sources. 了解 Power BI 入门的详细信息。Learn more about getting started with Power BI.

后续步骤Next steps