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Data Filtering Options for a Seamless User Experience

Data Filtering Options for a Seamless User Experience

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    Data Filtering Options For A Seamless User Experience

    A filter is used to provide different combinations of data. Instead of having a separate visual or dashboard for each category, you can add filters and let users change their criteria to explore the data. They allow you to view the same dashboard from a different business viewpoint. Bold BI allows you to configure different types of filters in dashboards, as well as preserve your filtered data to explore at any time. You can add filters at the data-source level, restricting the data that will be displayed to each user. You can also showcase top- or bottom-performing records by using data-source-level filters or widget-level filters in Bold BI. In this blog post, we will see different filters supported in Bold BI and their uses, and how to configure them to create multiple views of data using a single dashboard.

    Now, let’s examine each supported filter and its use case in Bold BI dashboards.

    Supported filters in Bold BI dashboards

    Data-source-level filter

    A data-source-level filter allows you to add a filter in the data source designer configuration that restricts the visibility of records based on defined criteria before you have designed the dashboard. It allows you to apply filtering to the data types, including Text, Numeric, DateTime, and Boolean type columns.

    In the Northwind Products and Suppliers Dashboard, you can monitor the sales performance for available products alone by applying a filter to the data source. The discontinued product record is restricted by selecting False for the Discontinued column in the Query Filters window as shown in the following image.

    Query Filters Configuration Window
    Query Filters Configuration Window

    Only current product records are showcased in the data preview grid as shown below.

    Data Source Designer Edit View
    Data Source Designer Edit View

    Next, in the same dashboard, I am going to add another filter condition in the data-source filter to showcase only the current product. The following dashboard screenshot shows the sales performance of all products. Note that the overall sales amount shown in the number card widget is $753,306.

    Northwind Products and Suppliers Dashboard in Bold BI
    Northwind Products and Suppliers Dashboard in Bold BI

    Here, you can restrict the dashboard visuals by showing only the current product order summaries by sales team. The following dashboard screenshot shows sales performance for the current product only.

    Northwind Products and Suppliers Dashboard with Data-Source-Level Filter in Bold BI
    Northwind Products and Suppliers Dashboard with Data-Source-Level Filter in Bold BI

    You can see the total sales is $623,829, which is the available product’s sales amount. To achieve this view, you can add another or multiple filters in the Query Filters configuration. For the text data type column, the parameter shows the specific conditions like Starts With, Ends With, etc. In this example, the specific condition is Inclusion, as shown in the following image. Similarly, for other data types, the relevant condition will be displayed to create query filters.

    Query Filter Configuration with Second Condition
    Query Filter Configuration with Second Condition

    For the integer type column, the parameter will be as shown in the following image.

    Query Filters Configuration with Third Condition
    Query Filters Configuration with Third Condition

    User-based filter

    User-based filtering is the process of imposing row-level security on the underlying data, thereby providing user-based data access. User-based filters help you avoid re-creating the same dashboard for each user; you can maintain one dashboard for all users by restricting other users from the information. This blog provides a brief discussion about user-based filtering.

    The Motor Vehicle Crashes Analysis Dashboard shows the  number of accidents in all states in a map widget. As an example, let’s say that management decides to provide access to the dashboard for each regional manager so they can visualize their region’s data and make changes to make driving safer.

    The following dashboard screenshot shows the administrator view, which shows the crash data for all regions.

    Motor Vehicle Accidents Analysis Dashboard in Bold BI
    Motor Vehicle Accidents Analysis Dashboard in Bold BI

    The following screenshot shows a regional manager’s view, which shows only their own state’s data.

    Motor Vehicle Accidents Analysis Dashboard with User-Based Filter in Bold BI
    Motor Vehicle Accidents Analysis Dashboard with User-Based Filter in Bold BI

    You can see that Indiana is the highlighted state in the map widget for this user, and all the other widgets only display the data for Indiana. Refer to the user-based filtering documentation for more details about this type of filtering in Bold BI.

    Widget-level filter

    A widget-level filter is applied to data as measures and dimensions. Measure fields comprise numeric types whereas dimension fields comprise strings, dates, and other types.

    In the Online Marketing Dashboard, we showcase website activities and other key metrics. By selecting a dimension filter in the Channel Name column, we can apply item-based, condition-based, and rank-based filtering. These allow us to track things like the top five revenue traffic sources, specific revenue ranges, and a specific list of traffic sources.

    Selecting a Filter in Dimension Field
    Selecting a Filter in Dimension Field

    You can track revenue from a specific list of traffic sources by using include or exclude conditions.

    Item-Based Filtering Configuration
    Item-Based Filtering Configuration

    Also, you can apply filters based on conditions to track specific revenue ranges.

    Condition-Based Filtering Configuration
    Condition-Based Filtering Configuration

    You can filter the top five values by applying the Rank filter to the Revenue column in the Filters window as shown below.

    Widget Filter Configuration with Top 5 Rank-Based Filtering
    Widget Filter Configuration with Top 5 Rank-Based Filtering
    Online Marketing Dashboard with Dimension Filters Applied
    Online Marketing Dashboard with Dimension Filters Applied

    You can see the top five revenue traffic sources in the pie chart, which is showing the top five traffic sources based on revenue.

    Let’s look at an example of measure filters. The Insurance Analysis Dashboard showcases the performance of an insurance company. By selecting a filter from the measure field for the Profit column, you can prevent negative values from being showcased in the widget. Set the filter Greater Than 0 to show positive values only, as shown in the following image.

    Measure Filter Configuration
    Measure Filter Configuration

    The following dashboard screenshot shows the performance of the whole insurance company. Note that the Profit vs. APE bar chart has negative values.

    Insurance Analysis Dashboard in Bold BI
    Insurance Analysis Dashboard in Bold BI

    After setting the filter to ignore negative values, the following screenshot shows the Profit vs. APE chart without negative values.

    Insurance Analysis Dashboard with Measure Filter Applied in Bold BI
    Insurance Analysis Dashboard with Measure Filter Applied in Bold BI

    Next, let’s see how you can track the performance of a company over any relative dates. For example, if you want to filter the last 30 days, last week, or any specific date ranges, you can do so by applying relative filters to the Date column.

    Relative Dates Filter Configuration
    Relative Dates Filter Configuration

    The following Retail Store Performance Dashboard screenshot shows the performance of apparel stores.

    Retail Store Performance Dashboard in Bold BI
    Retail Store Performance Dashboard in Bold BI

    Note the sales date in the date picker is 9/20/2020 to 9/25/2020

    The following screenshot shows the retail stores’ performance for the last 30 days, which is a relative date range.

    Retail Store Performance Dashboard with Relative Date Filter in Bold BI
    Retail Store Performance Dashboard with Relative Date Filter in Bold BI

    You can see the sales date is 8/26/2020 to 9/24/2020, which is the last 30 days. You can check out more widget filter configurations in our documentation.

    Now let’s explore the dynamic filter options available in widget-level filtering. They are:

    Allow filter

    Allow filtering enables filtering within a widget. Tabular-format widgets allow you to filter data in each column of the widget. You can perform a dynamic filtering operation on data within a widget by enabling the Allow filter option in the properties for the grid and pivot grid widgets.

    Allow Filtering Configuration
    Allow Filtering Configuration

    For the grid, a filter box will be enabled in each column as shown below.

    Grid with Allow Filtering Enabled
    Grid with Allow Filtering Enabled

    For the pivot grid, a filter icon will be enabled as shown.

    Pivot Grid with Allow Filtering Enabled
    Pivot Grid with Allow Filtering Enabled

    The Pharmaceutical Production Analysis Dashboard showcases KPIs relevant to the drug manufacturing process. It tracks overall production quality and the number of drugs produced compared to the production target, among other things. When tracking drugs that have many unique categories in a column, you can focus on specific categories through the allow filtering option.

    The following dashboard image shows overall production and the production targets.

    Pharmaceutical Production Analysis Dashboard
    Pharmaceutical Production Analysis Dashboard

    Note that the drugs shown in pivot grid is an overview of all the drugs. In the image below, the pivot grid data is filtered to show only the drug production and its target value for Syrup 1.

    Pharmaceutical Production Analysis Dashboard with Allow Filtering
    Pharmaceutical Production Analysis Dashboard with Allow Filtering

    Read this documentation to allow filtering in the pivot grid widget, and this documentation to allow filtering in the grid widget.

    Hierarchical filter

    A hierarchical filter helps when applying a top N filter with multiple dimension columns. The filtering is performed based on the hierarchy of the dimension columns. You can perform filtering based on hierarchy level in the grid and pivot grid widgets only.

    Enable Hierarchical Filtering in Properties Window
    Enable Hierarchical Filtering in Properties Window

    The following Student Details Dashboard visualizes various aspects of a student’s performance that is helpful for teachers and administrators.

    Student Details Dashboard
    Student Details Dashboard

    In the following screenshot, I have applied a top N filter to the student column to get the names of the top two students.

    Rank-Based Filtering Window
    Rank-Based Filtering Window

    By enabling a hierarchical filter, the top two students are filtered from each branch as shown below.

    Grid with Hierarchical Filtering
    Grid with Hierarchical Filtering

    Without hierarchical filtering, the top two students are filtered and those students’ details across all branches are shown, as in the following image. The students Bart Gusman and Emerson Butler are filtered.

    Grid without Hierarchical Filtering
    Grid without Hierarchical Filtering

    Refer to this documentation to configure hierarchical filtering in the pivot grid widget, and this documentation to configure hierarchical filtering in the grid widget.

    Drill down

    Drill-down filtering is multilevel filtering that you can use to view detailed breakdowns of your data with just a click. In the Personal Expense Analysis dashboard, a drill-down filter is applied to the doughnut chart shown in the following screenshot. The Home category is highlighted because we can click on it to drill down into its data.

    Personal Expense Analysis Dashboard with Drill-Down Filtering
    Personal Expense Analysis Dashboard with Drill-Down Filtering

    After navigating into the multilevel breakdown of the Home category, you can see a more detailed view of home expenses as in the screenshot below.

    Personal Expense Analysis Dashboard with Drill-Down Filter Applied to Home Category
    Personal Expense Analysis Dashboard with Drill-Down Filter Applied to Home Category

    You can refer to the documentation to learn how to enable drilling down in widgets.

    Dashboard filter

    Dashboard filters help apply master and listener relationships between widgets. They help control the interdependency of widgets in a dashboard with respect to dynamic user interactions.

    Enable the act as master property in a widget you want to act as a master. Select the listener widgets that you want to participate in filtering in the Filter Configuration window as shown below.

    Filter Configuration
    Filter Configuration

    The following Sprint Management dashboard showcases key metrics for tracking sprint performance.

    Sprint Management Dashboard
    Sprint Management Dashboard

    Note the project selection combo box, which is currently set to all projects.

    The following screenshot shows sprint performance for Project A alone.

    Sprint Management Dashboard with Dashboard Filter
    Sprint Management Dashboard with Dashboard Filter

    Managers can track sprint performance for individual projects by applying a master filter.

    Bold BI allows you to use widgets in filtering from one or more data sources. You can achieve this by enabling the Custom option in the Filter Configuration windowYou can map a column from the current data source to the target data source as shown below.

    Filter Configuration Window
    Filter Configuration Window

    The following GitHub dashboard shows GitHub metrics that track activities, pulls, and commits. These activities are fetched from an individual data source. However, those activities can be tracked for all repositories through mapping the columns to a target data source.

    GitHub Dashboard in Bold BI with “All” Repositories
    GitHub Dashboard in Bold BI with “All” Repositories

    The following screenshot shows the activities of one repository.

    GitHub Dashboard in Bold BI with “Sample” Repository using Dashboard Filter
    GitHub Dashboard in Bold BI with “Sample” Repository using Dashboard Filter

    Refer to this dashboard filters documentation for more details about configuration in Bold BI.

    Finally, Bold BI allows you to save the filtered view after publishing the dashboard and preserve your filtered data to view it at any time. For example, if you are filtering your dashboard view using a combo box or any other filter widgets, the resultant view will be saved in the Filter Overview option available in the top right corner of the page.

    Sprint Management Dashboard in Bold BI with Filter Applied After Publishing
    Sprint Management Dashboard in Bold BI with Filter Applied After Publishing

    If you want to preserve a filter applied to a dashboard, you can save the view through the Save option under Filters Overview.

    Save Filter View Configuration
    Save Filter View Configuration
    Saved Filter View
    Saved Filter View

    To know more about how to add, share, and delete saved views, you can check out this documentation. You can even share a filtered view without saving it. This is explained in this documentation.

    Conclusion

    We hope this blog article provided valuable information about the various data filtering options in dashboards to help you deliver a seamless user experience. If you have any questions on this blog, please feel free to post them in the following comment section. Get started with Bold BI by signing up for a free 15-day trial and create more interactive business intelligence dashboards. You can also contact us by submitting your questions through the Bold BI website or, if you already have an account, you can log in to submit your support question.

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