> For the complete documentation index, see [llms.txt](https://move-solutions.gitbook.io/untitled/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://move-solutions.gitbook.io/untitled/mymove-manual/analytics.md). # Analytics **Analytics** is a powerful data analysis tool designed to provide users with a dynamic and fully customizable environment tailored to their unique monitoring needs. By offering the ability to create custom charts and visualize complex datasets, Analytics simplifies the process of interpreting data from various sensors. This tool is essential for users who need to monitor multiple parameters simultaneously, as it allows for the overlay and comparison of different sensor data in real time. The flexibility of Analytics enables users to adapt their visualizations as their projects evolve, making it an indispensable resource for managing large datasets and extracting meaningful insights.

Analytics page

## Profiles #### Customizing your data visualizations In Analytics, charts are referred to as **Profiles**, which serve as the core elements for visualizing and analyzing data. A Profile represents a tailored chart that users create by selecting specific parameters from different sensors. These Profiles enable users to monitor and compare multiple data streams, such as vibration levels, temperature changes, or acceleration rates, all within a single visual representation. Each Profile can be customized to highlight relevant data by adding various **Data Series**—this feature allows users to choose specific parameters from sensors and adjust how they are displayed. You can customize elements like the line color, thickness, and legend names to ensure the chart is not only informative but also visually accessible. Users can preview Profiles and make adjustments to ensure clarity before saving them, making it easier to detect trends or patterns. Profiles can then be used to provide real-time insights, making complex data sets easier to manage. If you have already set an alarm on one of the parameters configured, you can import those alarm thresholds into the profile and display them on the graph. Users can also customize Y-axis scaling for each one of the Y-axis configured, deciding between an autoscale and a fixed scaling. The ability to create multiple Profiles allows for a highly detailed and segmented view of the data, perfect for users who need to examine specific areas of a project closely or monitor different parameters in parallel.

Profile configurator

Creating and configuring a profile is a simple and intuitive process. The user has access to all the parameters available in the project and can quickly select them as needed. A live preview of the resulting graph is available during configuration, providing immediate visual feedback. Each profile can contain up to 20 Data Series, enabling users to understand the correlation between data trends across the entire structure.

Data Series configuration page

## Folders #### Organizing Profiles for efficient management To keep your custom Profiles organized, Analytics introduces the concept of **Folders**. Folders act as containers, grouping multiple Profiles together for more structured and efficient management. Each Folder can store up to 20 Profiles, enabling users to create and categorize charts based on specific projects, timeframes, or monitoring goals. {% hint style="info" %} **Example**\ By organizing Profiles into Folders, users can keep a clear overview of their data analysis for each individual span or pillar of a bridge without being overwhelmed by multiple charts. For instance, a user monitoring the structural health of a bridge can create separate Folders for each span or pillar, with each Folder containing Profiles specifically focused on the vibration data, temperature, or displacement metrics of that particular section. This structure allows for easy comparison and more detailed analysis of the bridge’s overall integrity. {% endhint %} Folders provide a streamlined way to switch between different data visualizations and projects, ensuring that the data is always accessible and easy to find. This organizational structure not only saves time but also enhances collaboration, as it allows teams to easily share and access relevant data charts.

Analytics page

## Best Practices Here are **5 best practices** for using the **Analytics** tool effectively: 1. **Organize Profiles by Project or Structure**: Group your profiles into dedicated Folders based on specific projects, structures, or sections (e.g., spans or pillars of a bridge) to maintain clarity and focus in your analysis. 2. **Regularly Update Profiles**: Keep your charts and profiles updated with the most recent sensor data to ensure accurate analysis. Periodically review your charts to adapt to evolving data trends. 3. **Utilize Data Overlays**: Take advantage of the overlay feature to compare related parameters, such as temperature and vibration data, within the same chart. This allows for deeper insights and cross-analysis of different variables. 4. **Set Clear Naming Conventions**: Use clear, descriptive names for your Folders and Profiles to quickly identify the data sets or metrics being analyzed. This will make navigation and collaboration easier, especially in larger projects. 5. **Leverage Customization Features**: Customize chart appearances, such as line thickness and colors, to highlight important data trends or anomalies. Personalizing your data visualizations can make it easier to spot significant changes or areas of concern. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://move-solutions.gitbook.io/untitled/mymove-manual/analytics.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.