Plugin - Enable Multicolor Legend Items for Conditional and Range
Overview Legend items come with colored boxes that represent the data points in the chart. The color of each box matches the bar/column/bubble in the chart, as long as the measure is set to a single color, and not conditional or range. When conditional or range is used, the legend item's box becomes grey (or the palette's default color for Scatter Charts), because the box cannot natively accommodate multiple colors. This plugin solves this limitation by: splitting the box into smaller strips to accommodate multiple colors, for conditional, or creating a gradient of two colors in the box, for range. Limitations This plugin is only relevant to Bar Charts, Column Charts, and Scatter Charts. Other chart types either do not support conditional/range or have their own version of legends (e.g., Area Map). If there are too many legend items, wider boxes might affect spacing and cause certain items to be cut off. See the Configuration section below for more details. Installation Instructions Download and unzip the plugin zip file. Extract the files directly (do not extract into a new folder); the plugin files are already organized within a folder in the zip file. Upload the multiColorLegendItems folder to the plugins directory on your Sisense server (/opt/sisense/storage/plugins). Check the Add-ons page in the Admin tab (under Server & Hardware) and make sure the new plugin is listed and enabled. Modify the config file as needed (this can be done before of after the upload). Configurations This plugin comes with a configuration file that can be updated as needed. The four configuration settings in the file are: numberOfColorsForWiderBoxes . If there are too many conditions, the box may be too small to accommodate all colors, so the width may need to be increased. In this case, specify the threshold for the number of colors. For example, a threshold of 5 means the box width will be increased if there are five or more colors assigned to it. Otherwise, the original width will be kept. Note: Wider boxes might affect spacing and cause certain legend items to be cut off if there are too many of them. To work around this, the verticalLayout setting can be set to true. The default value is 5. widthMultiplierForConditional . For wider boxes, specify the multiplier. For example, a multiplier of 1.5 means the new width will be 1.5 times the original width for boxes that have more colors than the numberOfColorsForWiderBoxes threshold. The default value is 1.5. widthMultiplierForGradient . If wider boxes are needed for range as well, specify the multiplier. Otherwise, leave the default value of 1. The original width is generally sufficient for range. verticalLayout . Specify whether legend items should be laid out vertically. This is useful when wider boxes are needed and there are too many legend items to fit correctly horizontally. The default value is false. Examples 1. Conditional with 4 colors (less than the numberOfColorsForWiderBoxes threshold) [ALT Text: A comparison of two column charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in grey despite conditional formatting being applied, while the "After" chart correctly displays the four conditional colors.] 2. Conditional with 11 colors (greater than the numberOfColorsForWiderBoxes threshold, the legend item box width is increased) [ALT Text: A comparison of two scatter charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in blue (the palette's default color) despite conditional formatting being applied, while the "After" chart correctly displays all eleven conditional colors, with a wider box to fit them.] 3. Range Auto (both the min and max colors are auto-selected) [ALT Text: A comparison of bar scatter charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in grey despite automatic range (gradient) being applied, while the "After" chart correctly displays a gradient between the automatically selected minimum and maximum colors.] 4. Range Manual with Min Max range type (both the min and max colors are manually selected) [ALT Text: A comparison of bar scatter charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in grey despite manual range (gradient) with Min/Max mode being applied, while the "After" chart correctly displays a gradient between the user-selected minimum and maximum colors.] 5. Range Manual with Min range type (only the min color is manually selected) [ALT Text: A comparison of bar scatter charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in grey despite manual range (gradient) with Min mode being applied, while the "After" chart correctly displays a gradient between the user-selected minimum color and the automatically selected maximum color.] 6. Range Manual with Max range type (only the max color is manually selected) [ALT Text: A comparison of bar scatter charts labeled "Before" and "After," displaying sales and costs data by sales associates. The "Before" chart shows the "Sales" legend item box in grey despite manual range (gradient) with Max mode being applied, while the "After" chart correctly displays a gradient between the automatically selected minimum color and the user-selected maximum color.]Customizing the Sisense User Interface with Interactive Buttons and Icons
Sisense plugins and scripts enable extensive customization of the Sisense user interface, allowing developers to add interactive elements such as buttons and icons to enhance functionality and user experience. A common use case of plugins involves adding clickable icons or buttons that trigger specific plugin features or open custom UI elements. This article outlines the process for adding these interactive elements using a practical example.Loading Amchart5 and Other External Libraries via Script Tags in Plugins
This article explains how to load external libraries, such as Amchart5, into Sisense plugins by dynamically adding script tags to the page header to load the library. This method can avoid potential issues associated with other loading techniques but also offers flexibility such as using an external CDN to reduce plugin size and file count. Previous articles have discussed how to load external libraries and modules for Sisense plugins via adding the file to the plugin folder, and adding the file to the "source" parameter array in the plugin.json.
Custom Map Widget
Download: Custom Map Widget Note: (Sept 18, 2017) Added support for filtering on shapes. Introduction This article explains how to embed custom map visualizations in Sisense. Purpose/Benefits Sisense has some native mapping functionality but does not allow for importing custom maps. This plugin allows you to view data in whatever map you like. See the references for more information on GeoJSON, Leaflet, and Mapbox. Custom shapes (Counties) overlayed on a base map: Custom shapes (Chinese Provinces) with no base map: Steps The following steps will walk through the process of adding the new chart type and creating a sample map. STEP 1 - ADD THE PLUGIN Download the customMapWidget.zip attachment and unzip the contents into your C:\Program Files\Sisense\PrismWeb\plugins\ folder. If you are using version 7.2 and higher unzip the contents into your C:\Program Files\Sisense\app\plugins\ folder. If the plugins folder doesn't exist, just create it. After those files have been unzipped there, you may also have to restart the web server. Now, when you create a new widget the Custom Map widget should show up in the list of options STEP 2 - PREPARE GEOJSON FOR YOUR CUSTOM MAP This plugin uses GeoJSON files to overlay data as shapes on a map. More information on GeoJSON can be found here, but the general concept is that each file defines a JavaScript object that has a type of FeatureCollection and a list of features. There are different types of features, but the most common type is a polygon. Each feature represents a shape to display on the map and contains properties and geometry. Properties describe the attributes of the entire shape, while geometry is a list of points. Each point is a latitude/longitude combination, and the mapping function displays all points of the shape on the map and then draws a line to connect them. Below is an example of the format for a GeoJSON file. { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": { "ID": "1", "Name": "MyShape1" }, "geometry": { "type": "Polygon", "coordinates": [ [ [-86.411172, 32.409937], [-86.496774, 32.344437] ] ] } } ] } This plugin comes with 3 GeoJSON files included, but you can add in more if you want to show a different set of shapes. Some government agencies provide geo data for free use, and there are several 3rd party sites that provide free geo data as well. If you want to add in your own geo data, copy the file to customMapWidget/geojson/ folder. STEP 3 - CONFIGURE THE PLUGIN Open the config.js file and update the setting object's properties. urlTemplate - When using mapbox as the tiling server, you will need to provide a tile url mapboxKey - When using mapbox as the tiling server, you will need to provide an api key mapboxId - When using mapbox as the tiling server, you will need to provide a map type to use shapeSeparatorColor - color used for the outlines of the shapes shapeHighlightColor - color used to differentiate the highlighted shape Next update the list of Map options. This is a list of all the map types that are allowed by the widget, so if you are adding a custom GeoJSON file make sure to add it to the list and set the properties accordingly label - Name that appears in the widget editor, for selecting a map type url - Path to the GeoJSON file showBaseMap - should be true or false, based on whether you want to overlay your data on a map keyAttributes - a list of attribute names to use as the key, these get concatenated together using the separator below keySeparator - character to use as a separator for the attribute key prism.customMap = { settings: { mapboxKey: 'myMapboxApiKey', urlTemplate: window.location.protocol + '//api.tiles.mapbox.com/v3/sangil.i6ch70f8/{z}/{x}/{y}.png', mapboxId: 'mapbox.light', shapeSeparatorColor: 'white', shapeHighlightColor: 'black' }, maps: [ { label: 'Canada', url: '/plugins/customMapWidget/geojson/canada-GeoJSON.js', showBaseMap: true, keyAttributes:['NAME'], keySeparator:',', }, { label: 'US Counties', url: '/plugins/customMapWidget/geojson/USCounties-GeoJSON.js', showBaseMap: true, keyAttributes:['STATE','COUNTY'], keySeparator:'', }, { label: 'China Provinces', url: '/plugins/customMapWidget/geojson/china-provinces.js', showBaseMap: false, keyAttributes:['name'], keySeparator:'', }, ], widgets: {} }; STEP 4 - CREATE THE CHART On your dashboard, click the Create Widget button and select Advanced Configuration. Next, select the Custom Map Chart from the chart types menu. Pick a map type from the menu on the right. This selection determines which shape file to load, so you can use this plugin to make several map types available. Next, pick a dimension to use for the Geography dimension. The values from this field need to match the attribute key defined in the map's keyAttributes field. For example, this plugin comes with a GeoJSON file that provides the shape information for all counties in the US. If you open this file, each shape is has properties for STATE and COUNTY that uniquely identify each shape. The included Elasticube combines the STATE and COUNTY codes into a single field named GeoKey. In order to match up data from the Elasticube to the GeoJSON file, the config file specifies that the key is comprised of STATE and COUNTY. The Label dimension (optional) identifies which field to use when displaying the tooltip. The US Counties example uses FIPS codes to identify each county, but you may want to show tooltips with the county names instead. The Value measure is the number to embed into each shape. You can use the standard options to format the number, and the color selections get passed along to each shape. References/Notes Mapbox API - More information about the Mapbox API. This plugin uses mapbox in order to render the maps, so it does require a Mapbox API Key in order to render shape overlays on top of maps. More information on Mapbox API pricing can be found here. LeafletJS - The Mapbox project is an extension of the Open Source LeafletJS JavaScript library. If you're looking to modify the plugin, this can be a useful reference. Natural Earth - This site provides free geo data for download, so if you don't have the geo data already you can likely get it from this site. MyGeoData - This plugin requires a lat/long coordinate system (WGS 84) in order to display overlays on top of maps. If you're custom geo data comes in a different format, this site can likely help convert it to WGS 84 format. Upload your geo files, and convert/export it to a geojson file using the WGS 84 coordinate system. Also, you may need to change the file extension from geojson to js in order for your web server to know how to handle this file type. SampleElasticube.zipExploring the Potential of Sisense Jump to Dashboard Filter Configurations
Sisense Jump to Dashboard offers a powerful way to enhance the user experience and streamline data exploration with the help of different filter configurations. By default, all the filters from the parent dashboard, measured values, and widget filters are passed and replaced in the drill dashboard. This guide explains and provides examples of how you can customize the way filters impact the drill dashboard. We'll delve into multiple filter configuration options and provide a step-by-step guide on how to implement them effectively.Passing Filters to Accordion in Sisense Dashboards
Passing Filters to Accordion in Sisense Dashboards Introduction This article provides guidance on how to pass widget filters to an accordion in Sisense dashboards. This functionality allows users to maintain a single version of a dashboard while applying different filters, enhancing efficiency and consistency across multiple dashboard views. If there is an issue with Accordion not passing/ carrying over the dashboard or widget filters, this guide might also help you to configure the add-on according to your needs. Step-by-Step Guide To pass widget or dashboard filters to an accordion in Sisense, follow these steps: For Sisense versions prior to L2024.3: Navigate to the widget script section in your Sisense dashboard by clicking 3 dots menu > Edit Script. Use the “dashboardFiltersSelection” array to specify which dashboard filters should be passed to the target dashboard. Example: dashboardFiltersSelection: [], // Add your desired filters here Set “dashboardFiltersInheritance” to true if you want to apply all filters from the parent dashboard to the target dashboard. Example: dashboardFiltersInheritance: true, Set “widgetFiltersInheritance” to true to inherit widget filters to the dashboard. Example: widgetFiltersInheritance: true, Save the changes to apply the filter settings. The example script is provided below: widget.on('ready', function(){ Accordion({ //default: true, // uncomment this to make accordion to open on start element: element, widget: widget, dashboard: dashboard, dashboardName: '_accrd_myDashboardName', dashboardFiltersSelection: [], // dashboard filters which should be passed to the target dashboard. For configuration please see section 'Configuration' point two. dashboardFiltersInheritance: false, //gives the possibility to apply all of the filters from the parent dashboard to the target dashboard widgetFiltersInheritance: false // set to true if you want to inherit the widget filters to the dashboard }); }) Starting from L2024.3 it’s possible to configure the same behavior via the new UI. Please refer to this guide for reference: https://docs.sisense.com/main/SisenseLinux/accordion.htm Conclusion By configuring the widget script as outlined, you can effectively pass widget filters to an accordion in Sisense dashboards. References/ Related Content For more detailed information, please refer to the Sisense Accordion Documentation: https://docs.sisense.com/main/SisenseLinux/accordion.htm. This resource provides additional technical details and configuration options.Plugin - RemoveImageDownload - Removing Items From Sisense Menus
This article discusses a plugin (and an equivalent dashboard script) that removes the “Download as Image” option from Sisense menus. This same approach can be applied to remove any other menu option in Sisense by adjusting the relevant code. Organizations may want to hide or remove specific menu items for several reasons: Security: Prevent certain menu options from being used. Enforcing Best Practices: Remove menu items not used in the standard recommended workflow Streamlined UI: Hide unused menu items to simplify the user experience. Plugin Overview RemoveImageDownload plugin removes the “Download Image” option from all standard Sisense menus which include the:Managing Sisense Add-ons: Upgrades, and Version Control
This article describes how certified add-ons are upgraded in Sisense. Additionally, this guide will help you address questions related to add-on versions, such as when different versions of add-ons are installed on different instances or how to keep add-ons updated on on-premise instances.Comparative analysis using the filtered measure plugin
Comparative analysis using the filtered measure plugin By default, filter selections in Sisense are applied at the dashboard or widget level. The Filtered Measure add-on enables the creation of additional selection states, allowing you to display two or more different sets of selections within a single widget. For more details, please refer to the link below. Here are some common use cases for Filtered Measures: Comparative Analysis Example: Compare the same metric (e.g., Revenue) across two different date ranges (e.g., this month vs. last month) to analyze trends or identify growth patterns. Filter Applied Directly on a Measure Instead of applying a filter to the entire widget or dashboard, apply the filter directly to a specific measure (e.g., applying a filter to "Sales" based on a particular product category, without affecting other parts of the dashboard). This allows for more granular control over the displayed data while preserving other elements of the analysis. This article highlights a comparative analysis of a single measure, Revenue, across multiple dimensions—Date and Category. It incorporates two filters for each dimension: Primary and Compare. Background When it comes to comparative analysis, dashboards are often designed to display measures broken down by the dimensions being compared. This approach can make it challenging to extract specific values and may require adding additional dimensions for grouping. Example Dashboard Alt text: A dashboard displaying total revenue information. At the top, there is a summary showing total revenue of $263,661, with a breakdown indicating that 61% comes from Europe and 39% from the USA. Below, bar graphs illustrate total revenue by category, listing categories such as Bikes, Body Armor, Cables & Hubs, and more, with respective revenue figures. At the bottom, a line graph represents total revenue over several months, showing fluctuations with values ranging from $1.6K to $29.3K. This dashboard currently does not address the following questions: How can we filter by Category and compare Bikes to Wheels & Wheelsets across different Regions? How can we evaluate the performance of the Category Bikes against Wheels & Wheelsets over time? How can we compare a specific group of members within a Category to the overall total of the Category? How can we compare specific date ranges, such as Yesterday versus the same day last week? How can we provide flexible date selection options tailored to the user’s preferences? Filtered Measure - Implementation Steps Enable the Measured Filter Plugin Ensure the Measured Filter Plugin is activated in your environment. Modify the Data Model - Navigate to the Data Model. - Locate the Dimension table that requires a comparison - Duplicate the column you want to compare (e.g., the Date column) and assign it a meaningful name, such as Date_compare - Build or Publish the data model after applying the changes Prepare the Dashboard - Create a new dashboard or update an existing one. - Add both filters - Primary and Compare - as Dashboard Filters - Maintain a clear naming convention for the filters (e.g., Date for the primary filter and Date_compare for the comparison filter). Update Widgets with Measure Filters - Create a new widget or update an existing one - Add the relevant measure filters (Primary and Compare) to the metric. For example: ALT text: "Screenshot of a formula editor displaying a formula that sums order revenue based on category name and years in date." Rename Filter Measures - Rename the filter measures by adding an @ symbol before the name. - Update the formula syntax to include the renamed filters. Example ALT Text: A screenshot of a formula editor displaying a calculation formula in a spreadsheet application. The formula is a SUM function that includes parameters for "Order Revenue," "Category Name," and "Date." The text is shown in a code-like format, with certain elements in blue. - Ensure that the filter name in the dashboard matches the Measure Filter name used in the formula. - Repeat the Same for the Compared measure ALT text: A screen displaying a formula editor in a data visualization tool. The formula shows a calculation using the SUM function on "OrderRevenue," referencing "CategoryName_Compare" and "Date_Compare." The interface includes sections labeled "Values" and "Break by." Key Points of the Filtered Measure Plugin The @ symbol is required in the formula to apply the dashboard filter as a parameter. However, it should not be added to the name of the dashboard filter itself. Grouping by the Compared Dimensions is unnecessary and adds no value. Filtered measures support multiple measures and dimensions In the same formula, it is possible to include measures for both the Primary measure and the Compare measure. For example: ALT Text: A screenshot displaying a data analysis tool. The left side shows a panel for selecting categories labeled "Region" and "Values," while the lower section features a formula editor with a mathematical expression for calculating revenue compare by region. For Indicator, Blox widgets, and any widget using a single measure applied to either Primary or Compare, disable the corresponding filter. Similarly, turn off the other filter when switching between them. ALT Text: A screenshot of a data visualization interface showing "Revenue Primary" as the main heading. Below it, there are options labeled "Date Compare" and "Category Level Compare" with a highlighted checkbox next to each option. The current displayed revenue amount is $95,751, prominently positioned in the center of the screen. The interface includes buttons labeled "Apply" and "Cancel" at the top. If both measures, Primary and Compare, are used, ensure that both filters are enabled. Here are some common examples of comparative analysis: Use Case 1 - Compare Category Dimension ALT Text: A dashboard displaying revenue statistics. At the top, two sections show “Revenue Primary” and “Revenue Compare,” both with a figure of $76,274. Below, a third section displays “Revenue Compare Over Time” with a line graph illustrating revenue trends, peaking around $62,597. The bottom section features a table listing revenue by employee, with names and corresponding revenue figures, including entries for Andrew Williams and Emily Johnson. The visualizations include bar charts, line graphs, and a detailed employee revenue table. This example compares between Category Bikes and Wheels & Wheelsets over 3 groups by dimensions: Displaying the Revenue asan Indicator for each one of the Categories. Compare the Revenue over time ALT Text: A line graph titled "Revenue Compare Over Time" showing two data series. The blue line represents "Revenue," while the orange line indicates "Revenue Compare." The vertical axis measures revenue in dollars, ranging from $0 to $30,000. The horizontal axis displays dates from May 2011 to March 2012. The graph illustrates fluctuations in both revenue metrics over the specified time period with markers indicating values at various points. Compare the Revenue by Region Summary Table of Revenue Comparison by Employee Use Case 2 - Compare multiple Dimensions: Date and Category ALT Text: A data visualization dashboard displaying revenue metrics. The top section shows total revenues for "Revenue Primary" ($33,832) and "Revenue Compare" ($34,743). Below, a bar chart compares revenue by region, with separate bars for Europe and USA. Another chart shows revenue comparison by employee, with individual bars for names including Aria Williams, John Doe, Emily Johnson, and others. The dashboard features filters on the right side for data customization. This example compares Dates and Categories. The implementation of the measured filter is the same as shared above: (sum([Order Revenue]),[@CategoryName],[@Date]) Enable dynamic comparison between different time ranges from the viewer's side, rather than being predefined by the dashboard designer. Compare Category and Date over time Use Case 3 - Compare Different Date Ranges with Different granularities Compare Year to Single Quarter Example ALT Text: A data visualization showing revenue comparisons across different territories and employees. The top section displays a horizontal bar chart comparing revenue by TerritoryID, with revenue values in blue bars and revenue compare values in orange. The lower section features a bar chart comparing revenue by employee, with blue bars representing individual revenues and orange bars indicating revenue comparisons. Key figures are labeled, with total revenue values ranging from $380 to $16K. Date selection options are visible in the upper right corner, indicating the year 2012 and the fourth quarter of 2011. Compare Different Custom Date Ranges Example ALT Text: A data visualization dashboard displaying revenue comparisons. The upper section shows a horizontal bar chart labeled "Revenue Compare By TerritoryID" with blue bars indicating revenue amounts and orange bars representing revenue comparisons for various Territory IDs. The lower section features a vertical bar chart titled "Revenue Compare By Employee," highlighting revenue data for individual employees. Each bar is labeled with revenue amounts, with blue bars indicating revenue and a few orange bars for comparison. The sidebar includes date-selectors for filtering the data. Use Case 4 - Compare the selected Category with the total, excluding the selected category. This allows users to view the performance of a specific category in contrast to the remaining categories ALT Text: A dashboard displaying financial data, including three summary boxes at the top showing total revenue figures of $76,274 for Primary and $187,388 for Revenue Compare. Below, a graph illustrates revenue comparison over time with two lines plotting values for each month. To the left, there is a bar chart comparing revenue by region, highlighting Europe at $130K and USA at $74K. On the right, a table lists employee revenue with columns for employee names, revenue amounts, quantities, and total sales orders. There are filter options on the right side of the image. Best Regards Assaf
