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• Excel Data Set

Hi! To start visualizing your data, let’s navigate to the Add-ins in the Home tab. By now, you should already have the Zebra BI add-ins within the My Add-ins section. If Zebra BI Charts and not in My Add-ins yet, check out the previous sessions or search for it in More Add-ins. Locate Zebra BI Charts and click on it. This will open a window where Zebra BI Charts are displayed. Here, you can choose from various chart types, as Zebra BI offers many options for visualizing your data. Let’s start with charts that visualize data over time. We have single series charts like simple column charts, line charts, area charts, and horizontal bar charts. For multiple series charts, where you have multiple categories in your data, we offer options including the small multiples column chart, also known as the trellis chart. This chart type is valuable for comparing values and trends of different categories in one visual – where all charts are perfectly scaled between each other. We also support single and multiple series structural charts, such as vertical bar charts and comparison bar charts. In these charts, the category axis is vertical rather than horizontal. As this is the IBCS recommended way of visualizing structural data. As opposed to structural comparisons with vertical axis visualize data series over time with horizontal one to ensure standardization. One of key features of Zebra BI Charts is the ability to automatically calculate variances based on your dataset. Within Variance charts you can choose to highlight these variances using column or pin charts. Additionally, you can also choose between the responsive variance column chart, which adapts to visualize as much data as possible when resized, and other options like the integrated variance column chart, area chart, and bar chart. Next, we have contribution charts like the bridge chart, which is useful for visualizing how different parts contribute to the subtotal and total values. For multiple series, we offer horizontal for structural comparisons and vertical waterfall charts for time series. The last section is for part-whole visualizations, including stacked bar charts, stacked column charts, and stacked area charts, to address specific business cases. To begin visualizing, navigate to the variance chart section and select the integrated variance chart. This will provide an immediate visualization of the data, combining actual and previous values over time. The chart is drawn horizontally, variances are automatically calculated and formatted according to best practices, and you can add comments to explain the why in the visual. When you select a visual from the chart selector, sample data is added. You can modify it to see how the visual reacts. You can also add or delete comments to appear in the visual. That’s it! By choosing the type of chart you want to draw and adjusting the dataset to your needs, Zebra BI will respond and visualize your data according to best practices and IBCS standards.

Hello! You’ve learned how to insert Zebra BI charts; now it’s time to learn about Zebra BI tables. Tables are also located within the Add-ins of the Home tab. To get started, locate Zebra BI Table within My Add-ins, click on it, and the table selector will open. On the left side, you will find all the types of tables that Zebra BI offers. Let’s go through them: Structural Tables: These are simple tables that can be used to integrate various charts to visualize your data effectively. Comparison Tables: These tables allow you to add and automatically calculate variances for context. Single Series Cross Tables: These are two-way tables consisting of columns and rows, also known as multidimensional tables. They are suitable for structuring, summarizing, and displaying larger datasets. Calculation Tables: These are particularly useful for building P&L statements. They visualize data in a way that inflows and outflows contribute to the total, similar to a waterfall chart. Hierarchical Tables: These tables display structural multi-hierarchy variance data, including comments and can be used to explore data down to every detail or present key finding on a top level. For our first Zebra BI Table example, let’s go to the comparison tables and select a table with one comparison. Zebra BI will immediately create a sample dataset, which you can then adjust to reflect your numbers or comments. As you can see from the dataset, you have columns for actual (AC) and previous year (PY) values. Additionally, the Zebra BI table includes variance calculations, showing the difference between the actual and previous year in both absolute and relative terms. This Zebra BI table is not just a regular table with figures where you need to mentally calculate variances. Instead, the visual does it for you, automatically calculating and formatting the variances with integrated charts according to IBCS standards. This makes it easier to identify where variances come from and understand the data immediately.

Data ranges: To start using Zebra BI, it’s important to understand the possible data sources you can use with Zebra BI visuals. The first and most straightforward option is Excel ranges. Simply select all the cells containing your data, go to Add-ins, and add Zebra BI Charts. The only requirement is that the data structure includes a category column and a value column, such as actuals and previous years. Excel ranges are powerful and easy to use. For example, you can create a Zebra BI chart, like a horizontal waterfall chart, with this data. One unique feature of Zebra BI visuals is that all interactions and settings are on the visual itself, not in the ribbon at the top of the screen. For instance, to change the title name, hover over the title, open the drop-down section, and adjust the title name, font, and size. Zebra BI offers different types of charts, and you can easily switch between them without starting from scratch. Locate the chart slider on the right-hand side of the visual, click on it, and the visual will display various recommended chart types that best visualize your data. Let’s stop at integrated variance chart. To modify data labelling, such as increasing or decreasing the number of decimals, hover over the data label, open the drop-down menu, and make your adjustments. If you want to highlight a particular month, hover over the category, open the menu, and select the option to highlight. It’s that simple. Additional settings are located in global toolbar, in the top right corner next to Zebra BI logo. We will touch upon those in detail in the following sessions. Our recommended data source are however Excel tables. Like Excel ranges, Excel tables support data updates, meaning if you change a number, it will be reflected in the visual. However, inserting columns or rows is not supported with Excel ranges, so in such cases, you should use Zebra BI tables. Excel Tables: As mentioned, using Excel tables is recommended for Zebra BI add-ins in Excel because they are simple to use and offer useful features. Excel tables allow you to add new data by inserting columns or rows within the table. Here’s how to convert a data range to an Excel table: Select a cell within the data range. Press Ctrl + T as a shortcut to create an Excel table. Check the box indicating that your table has headers and click OK. Once you have a table, select a cell within it, go to Zebra BI Add-ins, and insert a Zebra BI Table. This is a common use case where you start with an existing dataset and want to enhance it with Zebra BI visuals. Immediately, you will see that variances are calculated and formatted according to best practices. The table now includes integrated charts that highlight which categories are more relevant to total performance and identify those performing well or poorly. Like charts, where you have a chart slider to switch between different chart types, you can switch to the table view with a simple click on the arrow. This changes the display to a plain table, but you can still highlight variances. Returning to the visual representation brings more insights immediately. All interactions with the table are done on the visual itself, just like with charts. For example, if you want to change the column order, such as showing relative variances before absolute variances or switching the order of previous year and actuals, you can easily drag and drop the columns. Our recommendation is to keep the columns in the order from left to right according to the point of time which is described by the data point. Meaning, previous years before actuals. More importantly keep it consistent. For sorting, simply click on a column header to change the order from descending to ascending or to use a custom sort based on the dataset. You can also adjust specific column settings. Hover over the column header and open the dropdown menu. Here you can choose different chart types, format the column, or hide a column if needed. Hiding a column means it won’t be displayed in the visual, but the data is still stored there. To bring back a hidden column, click the plus sign in the top left corner of the table and add the column back. In the global toolbar of Zebra BI Tables, located in the top right corner, you can find additional settings, such as data label settings, category settings and design settings. We will cover these settings in detail later, but for now, you just need to know where to find them.

Pivot Tables: Moving on to the next data source, let’s discuss PivotTables. PivotTables are one of the most powerful tools in Excel, summarizing and filtering your tabular data efficiently. When combined with Zebra BI add-ins for Excel, you can create amazing hierarchical tables or small multiple charts used in combination with slicers and filters. Or even better avoid numerous filters and slicer and create a fully interactive dashboards where selecting a particular data point in Zebra BI Chart or Table filters the rest of the visuals in the dashboard – it’s called cross-filtering. We will show all these cases later. To further benefit from modern Excel, you can even combine PivotTables with existing data models. For example, connect directly to a Power BI dataset or other external data sources. This allows to have a one source of truth and a better data governance in Excel. To create a PivotTable from a Power BI or any other available data source, simply go to insert PivotTable and choose the desired data source. For instance, I selected a Power BI dataset to create the PivotTable. Zebra BI visuals require separate columns for each value, such as actuals, plans, previous years, and forecasts. If visualizing yearly results, you need to have a separate column for each year in your data source for PivotTable (e.g., 2022, 2023, 2024). This preparation allows you to use all functionalities with Zebra BI. Once created, drag and drop the values and categories within the PivotTable fields to construct it. The rest is handled by Zebra BI visuals. Now, let’s imagine we have defined our data source and have already created a PivotTable. Select a cell within the PivotTable, go to Add-ins, and add the Zebra BI table. If your PivotTable includes more than one category column, the Zebra BI visual will recognize it as a hierarchical table. When using PivotTable as a data source you need to format it using the tabular layout. To do this, go to the Design tab, select Report Layout, and click Show in Tabular Form. With dataset constructed to have hierarchies of regions and countries, Zebra BI Visuals recognizes this and allows you to expand and collapse to present details at various levels. Clicking on the arrow next to the regions lets you collapse or extend the fields. All interaction with the visual is on the visual itself. This includes expanding, collapsing, reordering columns, sorting, switching to the table view, changing the title, and formatting the visual. An important feature we haven’t touched upon is field mapping, indicated by this icon within global toolbar. It defines data fields for data sources, such as ranges, Excel tables, and PivotTables. If you created a visual from a PivotTable, you could still switch to other data sources within the workbook. Once your data sources are defined, check how the visual recognizes and maps your fields. By default, Zebra BI may assign data sources incorrectly upon visual insertion. For example, plans might be assigned to the previous year placeholder, or forecasts might be assigned to plans. Incorrectly assigned columns cause visual errors and inconsistencies in reporting.