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    Custom Dashboards 201
    • 24 Mar 2024
    • 18 Minutes to read
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    Contents

    Custom Dashboards 201

    • Updated on 24 Mar 2024
    • 18 Minutes to read
    • Contributors
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    Article Summary

    The following are links to more detailed information about how to create custom dashboards. For more basic information, refer to Custom Dashboards 101.

    Note

    The user session timeout when using the Custom Dashboard Builder is 180 minutes. If you are logged in to the Dashboard Builder and are inactive for 180 minutes, your session ends and you are automatically logged out. You will lose any unsaved work.

    Create, Copy and Modify Datasets

    Datasets can only be created from delivered Stewardship Tier and read-only Postgres data sources. When you modify an existing dataset, create a copy of the existing dataset and modify the copy. Any changes made to existing datasets have the potential to break any visuals that rely on those datasets. Refer to Working with Datasets for more information. You can also filter datasets.

    Note

    Create unique, descriptive names for each dataset and analysis, including an indication of the data source’s instance. For example, web*DashReportObjectSelDEV

    Create datasets

    To create a dataset from an S3 data source:

    1. Click the Datasets tab.

    2. Click New dataset.

    3. Under FROM EXISTING DATA SOURCES, click the data source you want to use for your new dataset.

    4. Click Edit/Preview data to select specific columns, create calculated columns or create filters
      OR
      Click Visualize to create an analysis from the unfiltered dataset.

      Note

      Rename the dataset or analysis to include the instance from which the data is being pulled. This is the only way to indicate the data source to dashboard viewers.

    To create a dataset from a Stewardship Tier SQL data source:

    1. Click the Datasets tab.

    2. Click New dataset.

    3. Click the data source you want to use for your new dataset.

    4. Click Create dataset.

    5. Select a database object from the list and:

      1. Click Select.

      2. Select Directly query your data.

      3. Click Visualize to create an analysis from the unfiltered dataset.
        OR
        Click Edit/Preview data to select specific columns, create calculated columns or create filters.

    Select specific columns

    To select specific columns in the data source after clicking Edit/Preview data:

    1. Click All to check all of the checkboxes and select all columns for the dataset
      OR
      Click None to uncheck the checkboxes and deselect all columns for the dataset.

    2. Check the checkbox for each column that you want to include in the dataset.

      Note

      While datasets can be manipulated on this page, we recommend that rather than selecting certain columns on this page to tailor data sources, you should use filters or create a tailored view and upload it to the Stewardship Tier to use as a data source.

    Next, create calculated columns and filters.

    Copy datasets

    To copy a dataset in QuickSight:

    1. Click the Datasets tab.

    2. Click a dataset.

    3. Click Duplicate dataset.

    4. Enter a unique, descriptive name in the Duplicate dataset name field.

    5. Click Duplicate.

    Modify datasets

    Making changes to datasets that are already being used for analyses has the potential to break the visuals and insights in those analyses. To avoid these complications, we recommend that you modify a copy of the dataset rather than the existing dataset.

    To modify a dataset in Quicksight:

    1. Copy the existing dataset you want to modify.

    2. Click the newly created dataset copy.

    3. Click Edit dataset.

    4. Select specific columns, create calculated columns and/or create filters.

    5. Click Save to save the dataset and return to the Datasets page.
      OR
      Click Save and visualize to create an analysis from the dataset.

    Configure dataset with multiple data sources

    Sometimes, it may be necessary to configure a dataset using multiple datasources, like when configuring certain indicators. Datasets configured from multiple data sources may sometimes have data that is temporarily out of sync. Read-only Postgres data sources typically experience a 30-minute delay displaying updates to data, while data sources from the Stewardship Tier will show live updates to the data, so keep this in mind when considering the accuracy of the data displayed in a dashboard using multiple data sources.

    New dataset

    To add an additional data source to a new dataset:

    1. Create a new dataset.

    2. Click Edit/Preview data.

    3. Click the Add data link at the top of the Data Prep page.

    4. Under Table, select an object from the current data source underlying the dataset,
      OR
      Click Switch data sourceto add objects from an additional data source, and:

      1. Select an additional data source.

      2. Click Select.

      3. Select the database object you want to add to the dataset.

        Note

        Rather than using local files as additional data sources, upload the files to the Stewardship Tier and select the records from the underlying Stewardship Tier data source objects.

    5. Click Select.

    6. Repeat steps 4-6 for each additional data source.

    Existing dataset

    To add an additional data source to an existing dataset:

    1. Copy the existing dataset you want to modify.

    2. Click the newly created dataset copy.

    3. Click Edit dataset.

    4. Click the Add data link at the top of the Data Prep page.

    5. Under Table, select an object from the current data source underlying the dataset,
      OR
      Click Switch data sourceto add objects from an additional data source.

      1. Select an additional data source.

      2. Click Select.

      3. Select the database object you want to add to the dataset.

        Note

        Rather than using local files as additional data sources, upload the files to the Stewardship Tier and select the records from the underlying Stewardship Tier data source objects.

    6. Click Select.

    7. Repeat steps 4-6 for each additional data source.

    Create joins among multiple data sources

    To create joins among multiple data sources on the Data Prep page:

    1. Configure a dataset with multiple data sources.

    2. Click the pink circle next to the data source for which you want to create a join.

    3. Click the dropdown menu for each data source and select the field you want to join from each data source.

    4. Click the +Add a new join clause link to add additional joins.

    5. Click the appropriate join for all of the listed clauses under Join type.

    6. Click Apply.

    Create Analyses

    Before publishing an interactive, read-only dashboard for general use, dashboard authors must first create an analysis. An analysis is a container for interacting with visuals. You can use multiple datasets in an analysis, although any given visual can use only one of those datasets.

    Note

    Create unique, descriptive names for each analysis, including an indication of the underlying dataset’s instance. Analysis names can be long, so don’t shy away from providing as much context as you can in the name field. For example, web*DashReportObjectSelDEV for US filtered by Wave.

    An analysis is composed of:

    • Visuals—visual representations of data in graphical or tabular form that appears on an analysis.

    • Insights—paired with visuals to provide textual context based on the data in an analysis.

    To create an analysis in QuickSight:

    1. Click the Analyses tab.

    2. Click New analysis.

    3. Select a dataset.

      Note

       If you’re going to modify an existing dataset for the analysis, refer to Create, Copy and Modify Datasets.

    1. Click Create analysis.

    Next, Add Visuals and Insights to an Analysis.

    Add Visuals and Insights to an Analysis

    Analyses are a thoughtful combination of both:

    • Visuals—visual representations of data in graphical or tabular form that appears on an analysis.

    • Insights—paired with visuals to provide textual context based on the data in an analysis.

    Visuals and insights work together to create a cohesive, contextual experience when viewing dashboards.

    Visuals

    To add a visual to an analysis:

    1. Click Add on the page toolbar.

    2. Select Add visual from the dropdown menu; a blank visual box appears below any existing visuals.

    3. Select a Visual type for the visual depending on the fields you want to include.

    4. Select fields from the Fields list to display that data in the selected visual.

    5. Experiment until you create a visual that clearly and concisely displays vital information.

    Note

    By default, your analysis will automatically save as you work. If you turn off the Autosave option, you may lose your work. When an analysis is published as a dashboard, the Autosave option is disabled and you have the option to use ‘Save as’ to save the dashboard as an unpublished analysis.

    Insights

    To add an insight to an analysis:

    1. Click Add on the page toolbar.

    2. Select Add insight from the dropdown menu; the Computation modal displays.

    3. Select a Computation typefrom the dropdown menu. Options are:

      • Bottom ranked

      • Bottom movers

      • Forecast

      • Growth rate

      • Maximum

      • Metric comparison

      • Minimum

      • Anomaly detection

      • Period over period

      • Period to date

      • Top ranked

      • Top movers

      • Total aggregation

      • Unique values

    1. Select the insight and drag relevant fields to the insight.

    2. Click Customize insight to insert code and custom text; the Edit narrative page displays.

    3. Add the following components, if applicable:

      • Computations—Click the Computations tab and click the Add one… link
        OR
        Click the +Add computation button.

      • Parameters—Choose a pre-configured parameter. Refer to Use Filters for more information.

      • Functions—Click the Functions tab to add functions from the to create custom computations.

    1. Click Save.

    Next, to provide a cohesive visual experience for your dashboard, Create Themes and Use Filters.

    Create Calculated Columns

    Calculated columns can be used for aggregate functions within datasets. To avoid inconsistencies and delays for any other data calculations, we recommend that you include calculating functions in the database view used to create the dataset. Refer to Create, Copy and Modify Datasets for more information.

    Calculated columns for new datasets

    To create a calculated column for a new dataset:

    1. After creating a new dataset, click Edit/Preview data to open the Data Prep page.

    2. Click Add calculated field.

    3. Click the Fields tab.

    4. Double-click fields to which you want to add function(s).

    5. Click the Functions tab.

    6. With your cursor next to the field to which you want to add functions, double-click the function(s) you want to add to each field.

    7. Click Save.

    Calculated columns for existing datasets

    To create a calculated column for an existing dataset:

    1. Copy the existing dataset you want to modify.

    2. Click the newly created dataset copy.

    3. Click Edit dataset.

    4. Click Add calculated field.

    5. Click the Fields tab.

    6. Double-click fields to which you want to add function(s).

    7. Click the Functions tab.

    8. With your cursor next to the field to which you want to add functions, double-click the function(s) you want to add to each field.

    9. Click Save.

    Use Filters

    Filters are an excellent way to tailor information in datasets, visuals and dashboards to fit the needs of specific people, groups or tasks. Filters can help create customized views for dashboards, and they can allow dashboard viewers to drill into more granular information in a visual. Refer to Adding a Filter and Using Filters with Parameters in Amazon QuickSight for more information about filtering datasets. Refer to Filtering Visual Data in Amazon QuickSight and Parameterizing a Filter for more information about filtering visuals and dashboards.

    Filters and parameters can be applied to:

    • Datasets

    • Visuals

    • Dashboards (at the page level)

    Datasets

    You can create filters for datasets to tailor information based on a field’s values. However, we recommend that you filter your datasets through filters applied to visuals/dashboards. For example, rather than creating different filtered datasets for each country’s data, it’s more efficient to create a dataset for all countries and then to filter by country for each dashboard. Refer to Create, Copy and Modify Datasets and Adding a filter and Using Filters with Parameters in Amazon QuickSight for more information.

    Restrict access to dashboard data based on the user

    When creating dashboards, there is often a requirement to be able to restrict dashboard data based on the user. This may be to focus users on specific data relevant to them or to ensure compliance with data privacy rules. To address this issue, Custom Dashboard Authors now have access to a User List button to the Syniti Dashboard Builder page that allows users with Custom Dashboard Author permissions to download a CSV file list of the Custom Dashboard users in their tenant. This data can be downloaded into a CSV file, imported into a MS SQL Server table, and then used in datasets that support analyses and dashboards. Refer to Applying row-level and column-level security on Amazon QuickSight dashboards in the QuickSight help for more information.

    You can use user names and additional columns to specify that only information filtered by Row-level Security(RLS) can display for certain users.

    This topic contains the following sections:

    • Download a list of Custom Dashboard users from the Syniti Dashboard Builder

    • Configure Row-level security for users

      • Use RLS values as Custom filters

    Download a list of Custom Dashboard users from the Syniti Dashboard Builder

    Users with Custom Dashboard Author permissions can download a list of the Custom Dashboard users in their tenant. This list helps users gather the information they need to share dashboards with other users and to restrict dashboard data based on the user.

    The User List includes the following:

    • Name

    • Email (Knowledge Platform username)

    • Dashboard Username—the user name that needs to be used in the dataset used to provide row-level security.

    To download a CSV file with a list of the dashboard users in your tenant:

    1. Navigate to the Syniti Dashboard Builder page.

    2. Click the User List button.

    3. Click the Download button.

    Configure Row-level security for users

    To configure RLS for users, the dataset you want to use as a filter must have values in the UserName field that are populated with user names from the Syniti Dashboard Builder User List. You may add any additional columns by which you want to filter user views, but the name of the additional columns in this Dataset must match the name of the columns to which you wish to bind this view. For example, if you want to filter by UserName and Company, the Dataset you wish to filter by Company must also have a corresponding column named “Company.” When you apply your user-restricted dataset to the dataset underlying the analyses and dashboards to which you wish to apply RLS, the dataset underlying the analyses must have a UserName column set up, and any additional columns used for filtering must have the same name as the corresponding columns in this dataset.

    To create row-level security by user:

    1. Select a Dataset that contains a column called UserName that has the users for whom you want to execute row-level security.

      Note

      The values in the UserName field must be populated with user names from the User List.

    1. Click Edit Dataset.

    2. Add any additional values by which you want to filter datasets.

    3. Click Save.

    4. Select the dataset you want to filter.

    5. Click the Row-level security button.

    6. Click Edit Dataset.

    7. Add any additional values by which you want to filter datasets.

    8. Click Save.

    9. Select the dataset you want to filter.

    10. Click the Row-level security button.

    11. Select the view by which you want to filter the dataset.

      Note

      This dataset must have a UserName column set up, and any additional columns used for filtering must have the same name as the corresponding columns in this dataset.

    1. Click the Apply dataset button.

    Now users who access analyses and dashboards that use these datasets will see filtered data to which they have been granted specific access.

    Use RLS values as Custom filters

    Once you have applied row-level security to a dataset, any analyses using that dataset will have the ability to be filtered by the values applied.

    To change how your row-level security filters apply to an analysis:

    1. Click the Filters tab.

    2. Click the Filter type list box.

    3. Select Custom filter.

    4. In the list box that appears below, select Equals.

    5. Now the fields you set up in the row-level security dataset display in a filter list box under Controls for the analysis.

    Row-level security can only be used to grant access to view certain data. Refer to Using Column-Level Security (CLS) to Restrict Access to a Dataset in the QuickSight help for more information about excluding access to certain data using column-level security.

    Visuals

    Create parameters

    To create a new parameter for a visual:

    1. Click the Parameters tab.

    2. Click the + icon to add a parameter.

    3. Enter a descriptive name for the parameter in the Name field.

      Note

      No special characters are allowed in this field, so we recommend using CamelCase to name parameters.

    4. Select either:

      1. Single value—Single parameter value type supports single dropdown, text field, and slider control styles.

      2. Multiple values—Only multi-select dropdown control style is supported for multiple default values.

    1. If needed, configure default values. To configure default values, either:

      1. Enter a value in the Static default value field.
        OR
        Click Set a dynamic default.

      2. Click the Dataset with default values and user information dropdown menu to select a dataset.

      3. Click the User name column dropdown menu to select a user name, which allows dashboards and visuals to display certain information based on the viewer’s user name.

      4. Click the Group name column dropdown menu to select a group name, which allows for dashboards and visuals to display certain information based on the viewer’s group name.

      5. Click the Column for default value dropdown menu to select a column, which allows for dashboards and visuals to display information based on a default value.

      6. Click Create.

    1. Click Update; the Parameter added modal displays.

    2. Click Close.

    Next, create a filter and connect a parameter to a filter.

    Create filters

    Create filters to tailor data in a dashboard for certain users, groups, or values. Refer to Filtering Visual Data in Amazon QuickSight for more information.

    To create a filter for visuals:

    1. Click the Filter tab.

    2. Click the + icon.

    3. Select a field to filter.

    4. Click the gray text under the filter name to configure the filter type.

    5. Click the Filter type dropdown menu and select Custom filter.

    6. Click the dropdown menu that appears and select one of the following:

      • Equals

      • Does not equal

      • Starts with

      • Ends with

      • Contains

      • Does not contain

    1. Click Apply.

    Next, you can connect a parameter to your filter.

    Connect parameters to filters

    Filters are applied to one or some visuals in a dataset. You can connect parameters to filters to filter all visuals from a dataset.

    To connect a parameter to a filter:

    1. Click the Filter tab.

    2. Click the gray text under the filter name to add a parameter.

    3. Click the Use parameters checkbox to check it; a warning message displays.

    4. Click Yes if you want to use a parameter to filter all visuals from the dataset.

    5. Click the dropdown menu under the Use parameters checkbox to select a parameter. Refer to Create parameters for more information.

    6. Click Apply.

    Next, set control for filters.

    Add control to parameter

    To add a control to a parameter so that it can be applied to a sheet:

    1. Click the Parameters tab.

    2. Click the arrow next to the parameter to which you want to add a control.

    3. Enter a descriptive name for the control.

    4. Click the Style list box and select Single select list box.

    5. Under Values, select Link to a date set field.

    6. Click the Select a dataset list box to select a dataset.

    7. Click the Select a column list box to select the field value you want to apply to the control.

    8. Click the Hide [ALL] option from the control values if the parameter has a default configured check box.

    9. Click Add.

    Next, configure controls for pages.

    Configure control for pages

    Once a parameter is connected to a filter, and a control is added to that parameter, that control can be configured to apply your pre-configured parameters for a page (sheet) in your dashboard.

    To configure controls for a page in an analysis:

    1. Select the sheet for which you want to configure controls.

    2. Click the word Controls; filter dropdown menus with control options display.

    3. Click each filter dropdown to select a value by which to filter all the data on the page.

    4. Click the … icon next to a parameter to edit the controls that parameter has over the page.

    5. Click Apply.

    Create Themes

    Create a theme to quickly and consistently a custom color template to your analyses. Refer to Using Themes in Amazon Quicksight for more information.

    Syniti Knowledge Tier color theme

    Main colors

    • Primary Background: #FFFFFF

    • Primary Foreground: #3B617A

    • Secondary Background: #F6F6F6

    • Secondary Foreground: #444444

    • Accent: #3B617A

    • Accent Foreground: #FFFFFF

    Data colors

    The following list is in order of data colors to use for charts/graphs:

    1. #00558B

    2. #503D63

    3. #1A9584

    4. #ECC21F

    5. #C25052

    6. #E65722

    7. #444444

    8. #C9C9C9

    Create the Syniti Knowledge Tier theme

    To create the Syniti Knowledge Tier theme:

    1. Click the Main tab.

    2. Click the arrows next to My themes to expand the menu.

    3. Click the Create one… link.

    4. Enter a descriptive name in the Theme name field.

    5. Click the color box under Primary background and select Custom color.

    6. Enter #FFFFFF in the HEX field.

    7. Click Apply.

    8. Click the color box under Primary foreground and select Custom color.

    9. Enter #3B617A in the HEX field.

    10. Click Apply.

    11. Click the color box under Secondary Background and select Custom color.

    12. Enter #F6F6F6 in the HEX field.

    13. Click Apply.

    14. Click the color box under Secondary foreground and select Custom color.

    15. Enter #444444 in the HEX field.

    16. Click Apply.

    17. Click the color box under Accent and select Custom color.

    18. Enter #3B617A in the HEX field.

    19. Click Apply.

    20. Click the color box under Accent foreground and select Custom color.

    21. Enter #FFFFFF in the HEX field.

    22. Click Apply.

    23. Click the Data tab.

    24. Using the same color selection method as above, click each color box and enter the following values in order:

      1. #00558B

      2. #503D63

      3. #1A9584

      4. #ECC21F

      5. #C25052

      6. #E65722

      7. #444444

      8. #C9C9C9

    25. Once all desired changes have been made, click Save in the top right corner of the page.

    26. To apply the theme, click the newly created theme on the Themes pane.

    Publish and Share Dashboards

    You can publish any analysis as a dashboard to either everyone or to a limited set of users. When you are still drafting dashboards, identify the initial stakeholders that need preview access to the dashboard and share the analysis with those users directly. To avoid confusion when publishing different drafts of dashboards, we recommend that you use a naming convention for dashboards such as the prefix “For Review.” For example, “(For Review) Data Quality for Supply Chain.”

    Publish your new analysis as a dashboard

    To publish an analysis as a dashboard:

    1. Create an analysis.

    2. Click Share in the page toolbar.

    3. Select Publish dashboard from the dropdown menu.

    4. Select Publish new dashboard as and enter a descriptive name for the dashboard.

    5. Click Publish dashboard.

    Note

    You can share the published dashboard either with everyone in the account or with specific people. Refer to Share your dashboards for more information.

    Replace published dashboards with updated dashboards

    Once a dashboard has been reviewed and is ready for general publication, you can replace the existing dashboard to which you made edits with the new, improved and reviewed version.

    To replace an existing dashboard:

    1. Click the Analyses tab in the navigation pane.

    2. Click on the reviewed analysis with which you want to replace an existing dashboard.

    3. Click Share in the page toolbar.

    4. Select Replace an existing dashboard.

    5. Click the dropdown arrow to select an existing dashboard to replace.

    6. Once you have chosen the existing dashboard to replace, you can click rename to enter a new name for the dashboard that is to be replaced.

    7. Click the Publish Dashboard button.

    Note

    You can share the updated dashboard either with everyone in the account or with specific people. Refer to Share your dashboards for more information.

    Share your dashboards

    To share your published dashboard:

    1. Navigate to the dashboard.

    2. Click Share in the page toolbar.

    3. Select Share dashboard from the dropdown menu.

    4. To share the dashboard with everyone, enable the Everyone in this account toggle.

    Note

    If sharing the dashboard with everyone in the account, also enable the Discoverable in QuickSights toggle, which makes the dashboard searchable and appear in everyone’s dashboard list. If this setting is disabled, you can only access the dashboard if you have a link to it.

    1. Alternatively, search for specific users to share the dashboard with.

    Download a list of Custom Dashboard users from the Syniti Dashboard Builder

    Users with Custom Dashboard Author permissions can download a list of the Custom Dashboard users in their tenant. This list helps users gather the information they need to share dashboards with other users and to restrict dashboard data based on the user.

    The User List includes the following:

    • Name

    • Email (Knowledge Platform username)

    • Dashboard Username—the user name that needs to be used in the dataset used to provide row-level security.

    To download a CSV file with a list of the dashboard users in your tenant:

    1. Navigate to the Syniti Dashboard Builder page.

    2. Click the User List button.

    3. Click the Download button.

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