> For the complete documentation index, see [llms.txt](https://docs.inforiver.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.inforiver.com/analytics+/working-with-analytics+/5.-tables/5.1.-tables-getting-started.md). # 5.1. Tables - getting started We've already talked about Inforiver's powerful data table. In this section, we'll get down to business and build a responsive, intuitive data table in under a few minutes. Let's begin by switching to table mode and adding dimensions and measures. 1. Analytics+ automatically adds measures to the comparison data wells based on the order of the measures: the first measure parameter is assigned to Actuals(AC), the second is assigned to Prior period (PY), the third is assigned to Plan (PL), the fourth is assigned to Forecast (FC) and subsequent measures are assigned to the AC bucket. You can drag and reorder the measures as required in the pivot data window.

2. Analytics+ applies TopN ranking and displays only the top 4 categories- let's display all the product categories in our report.

3. Inforiver enables you to change the look and feel of your reports using a range of built-in themes. We'll switch to the xViz theme.

4\. Now comes the part that we have been waiting for - the small multiples table. All you need to do is add a dimension to the Small Multiples parameter and voila - you have a trellis!

5\. You can visualize your tabular data by embedding charts. We can insert an inline lollipop chart just by selecting the measure and choosing the chart.

6. Not just charts - you can add KPI metrics for data tables as well. Just click on the KPI icon to display the KPIs for each panel.

In the next sections, we'll take a detailed look at all the configuration and analytics options provided by Inforiver. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.inforiver.com/analytics+/working-with-analytics+/5.-tables/5.1.-tables-getting-started.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.