Embedded Analytics Designer

This program lets you configure your data connections and sources for SYSPRO Embedded Analytics, as well as design and view browser-based business intelligence dashboards.

Exploring

Functionality

The SYSPRO Embedded Analytics module form part of SYSPRO's Enterprise Reporting capabilities and empowers you to create, manage and deploy both operational and analytical dashboards into SYSPRO. This is achieved using the SYSPRO Web View technologies and is based on SYSPRO's Business Activity Queries (for input data).

Sources

The Source panel enables you to manage all active source definitions currently available within the selected account, as well as leverage a connected data store to build a new source configuration.

Once you connect to a database, you can generate a source configuration (i.e. pull data and prepare it to be used in conjunction with a visual or dashboard) by using one of the following:

Business Activity Queries
Table and database schema
Materialized view
Custom SQL statement (i.e. for more detailed definition)

The selected data is then prepped for end user consumption by applying friendly names, filter defaults, distinct count, etc.

The source configuration is then saved for future visual creation.

Visualizations

The Visual Gallery panel is where you can build a single, reusable visual that’s driven by one of your defined sources.

The visualization types available include:

Arc gauge
Bar charts:
- Bars
- Histogram
- Multiple metrics
Box plot
Bullet Guage
Combo chart
Donut
Floating bubbles
Heat map
KPI
List filter
Packed bubbles
Pie chart
Pivot table
Table
Scatter Plot
Tree map
Word cloud

The design capabilities within the visualization manager enable you to tweak and customize your visual, which you can then place into a dashboard later on.

Library

The Library panel houses of all your existing dashboards (either created by you or shared with you from another author) and provides access to the Dashboard Designer, from where you can create new dashboards.

The dashboards within your library, as well as your visualizations, can be embedded within SYSPRO in various ways:

SYSPRO Web UI (Avanti):
- Role-based SYSPRO Workspaces
- Program web views
SYSPRO Desktop:
- Main Menu
- Program web views
- Application Builder
- Application Designer

Terminology

Starting

Prerequisites

Configuring

To use this program, the following setup option(s) must be configured appropriately:

Setup Options

Setup Options > System Setup > Connectivity

Application Gateway service settings

This lets you connect to the SYSPRO Application Gateway service.
Embedded Analytics:
- Embedded Analytics enabled
  
  This lets you activate or deactivate the usage of the SYSPRO Embedded Analytics feature.
- Analytics Endpoint
  
  This lets you connect to SYSPRO Embedded Analytics.
- Configure
  
  This configures your SYSPRO Embedded Analytics environment.

Known Issues

The following considerations are being addressed and should be resolved with a later release of the software:

A warning message is displayed when you add a new connection that uses Microsoft SQL Server 2022, however this does not prevent you from proceeding.
KPI or Metric visualizations don't have a drill-down capability.
When using the Embedded Analytics Designer program in the SYSPRO Web UI (Avanti) version:
- After creating a new dashboard, you must log out and back in for the new dashboard to reflect within the list of Embedded Analytics cards.
- When you change your settings to use the Dark theme, you must refresh the page for the change to reflect.
The SYSPRO Embedded Analytics module doesn’t currently support the following within your SQL server name configuration:
- TCP protocol or Named Instances
  
  View the Why doesn't the Embedded Analytics Designer program render when launched? FAQ within the Solving section of this topic for solution details.
- User defined SQL port numbers (i.e. SQL port numbers outside of the defaults provided)
  
  Please contact your local support office for assistance with any issues around connection strings until a hotfix is made available to resolve this.

Solving

FAQs

Installation and Services

What occurs during the installation of SYSPRO Embedded Analytics?

Once you have installed PostgreSQL 12 and the SYSPRO Application Gateway service, the following indicates the processes which occur when you select to install SYSPRO Embedded Analytics using the SYSPRO Installer Application:

The app collects all the required information for the install, ports, passwords, etc.
The connection to PostgreSQL is validated.
The required files are deployed.
The applicable services are created.
Property entries are updated.
The app calls the SYSPRO Application Gateway and creates the applicable entry within the C:\ProgramData\SYSPRO\Application.Gateway\appsettings.reverseProxy.json file.
The database and database user are created:

The SYSPRO Embedded Analytics.msi retrieves the properties passed to it to enable access to PostgreSQL and create the required databases, as well as a user called zoomdata.
The services are started in the following order:
1. PostgreSQL (unless already running)
2. SYSPRO Application Gateway (unless already running)
3. Zoomdata Services:
  1. Zoomdata_consul
  2. Zoomdata_edc_* (i.e. data sources or connectors)
  3. Zoomdata_query_engine
  4. Zoomdata_data_writer_postgresql
  5. Zoomdata_screenshot_service
  6. Zoomdata_service
Registry entries are written.
The SYSPRO Deployment Database is updated.

What ports are used by SYSPRO Embedded Analytics?

The following ports are used:

Port number	Service name	Comments
5432	Zoomdata-postgres	Composer metadata repository
5580	Zoomdata-query-engine	Composer query engine microservice
8090	Zoomdata	Composer server
8081	Zoomdata-data-writer	Composer Data Writer microservice
8083	Zoomdata-screenshot-service	Composer Screenshot microservice
8100	Zoomdata-edc-mssql	Microsoft SQL Server connector
8105	Zoomdata-edc-postgresql	PostgreSQL connector, Flat File uploads, and Upload API processing
8300	Zoomdata-consul	Internal port used by the Consul for inter-node communication in a distributed environment
8301	Zoomdata-consul	Internal port used by the Consul for inter-node communication in a distributed environment
8302	Zoomdata-consul	Internal port used by the Consul for inter-node communication in a distributed environment
8443	Zoomdata	Composer HTTPS requests
8500	Zoomdata-consul	Consul

How do I update SYSPRO Embedded Analytics when a new version becomes available?

As the SYSPRO Embedded Analytics module doesn't form part of the standard SYSPRO release cycle, the update process for this module is slightly different to other SYSPRO products.

Therefore, when an update is made available, proceed as follows:

Launch the SYSPRO Installer Application.
Once a connection is made to the SYSPRO Deployment Service, login using your InfoZone credentials.

If you are a partner or super-user, enter the applicable Customer ID for the customer being installed.
From the SYSPRO Installer home screen, select the SYSPRO Additional Software option.
From the Additional Software Packages screen, select the SYSPRO Embedded Analytics option.
If an update is available when the SYSPRO Embedded Analytics page loads, the existing local product files (including the related install files) are deleted and the latest files are retrieved from Azure. This ensures that the latest files are always used.

The SYSPRO Embedded Analytics version then has an Upgrade button. Select the button to proceed with the update.
From the SYSPRO License Agreement screen, read and accept the license terms and conditions before continuing with the update.
A summary of all products to be updated is displayed for you to review.

Once you are satisfied with the list, continue by selecting the Begin Upgrade button.
The Upgrade Complete screen is displayed with a summary of all products installed.

What is the order in which the zoomdata services should be started?

If you need to restart the zoomdata services for any reason, ensure to start them in the following order:

Zoomdata_consul
Zoomdata_edc_* (i.e. data sources or connectors)
Zoomdata_query_engine
Zoomdata_data_writer_postgresql
Zoomdata_screenshot_service
Zoomdata_service

Dashboard Migration

How do I export an Embedded Analytics dashboard?

To create an Embedded Analytics dashboard pack and export it (along with all its related files), proceed as follows:

Open the Embedded Analytics Export program (Program List > Embedded Analytics).
From the Dashboard listview, select the applicable dashboard that you want to export.
Once selected, navigate to the Action column and select the Details function against the dashboard.

This opens the Embedded Analytics Pack Details program, from where you can view the meta data associated with the selected dashboard.

In addition, the BAQ details pane indicates all Business Activity Queries that are used by or associated with the selected dashboard pack.
Within the Pack details form, update the entries as required:
1. Name and Description:
  
  Leave as is, or edit as required.
  
  The more descriptive you are in your naming convention and description, the easier it is for other users to identify and understand the purpose of the dashboard pack.
2. Owner:
  
  Indicate the user responsible for the dashboard pack creation.
3. Documentation:
  
  Upload a PDF document to provide all the related details for the dashboard pack.
  
  This allows the creator of the dashboard pack to provide:
  - Documentation about the pack and what it hopes to achieve
  - What visuals are included within the dashboard
  - What users should expect to see in within the dashboard.
  Use the Preview function to view the document using the Document Viewer program.
4. URL:
  
  Optionally indicate a website for more information about the dashboard author or their company.
Select the Save function to record your changes.

You are returned to the Embedded Analytics Export program.
Select the Export Selected Dashboards toolbar function.

This exports each pack in its entirety to a zip file (which includes all of its related files) with a seax extension.

This zip file is exported to the \Work\Analytics folder on the application server.

Considerations:
- If the pack name already exists, a subscript is added to the end of the file name (e.g. Financial_Manager(1).seax).
- The following characters are replaced in the file name:
  - All spaces are replaced by an underscore (_)
  - All semicolons are replaced by a dash (-)
Exit the program.

How do I import an Embedded Analytics dashboard?

To import an Embedded Analytics dashboard pack (along with all its related files), proceed as follows:

Open the Embedded Analytics Import program (Program List > Embedded Analytics).

You are presented with a list of all Embedded Analytics dashboard packs found within the following folders on the application server:
- \Base\Samples
- \Work\Analytics
From the listview, select the applicable dashboard that you want to import.
Once selected, navigate to the Details column and select the Details function against the dashboard.

This opens the Embedded Analytics Pack Details program, from where you can view the meta data associated with the selected dashboard.

In addition, the BAQ details pane indicates all Business Activity Queries that are used by or associated with the selected dashboard pack.
Within the Pack details form, you can optionally preview the PDF document saved against the Documentation field.

This allows the creator of the dashboard pack to provide:
- Documentation about the pack and what it hopes to achieve
- What visuals are included within the dashboard
- What users should expect to see in within the dashboard.
Exit the Embedded Analytics Pack Details program to return to the Embedded Analytics Import screen.
Select the Import toolbar function.

The import process creates the required connections, sources and visuals it needs to populate the dashboard.
Exit the program.

Imported dashboards are displayed in the Library of the Embedded Analytics Designer program, with the operator that imported the pack listed as the Author for that dashboard. From there you can modify and tailor the dashboard according to your requirements.

Troubleshooting

What should I do if one of the services fail to start?

After a new install or upgrade, you might not be able to access SYSPRO Embedded Analytics until the zoomdata service has completed its checks and database updates (which can take up to 15 minutes).

To verify if this is the cause for your services not starting, open the Task Manager and look for a high running java process that belongs to zoomdata. If present, wait for the process to calm down, after which you should be able to continue.

If however, this does not resolve the problem, check to see if the port is already in use by another application.

See the What ports does SYSPRO Embedded Analytics use FAQ for information regarding port numbers.

If the above doesn't resolve the issue either, proceed as follows:

Check the log files for any error recorded.
Stop all of the zoomdata services.
Delete the log files.
Restart the zoomdata services in correct sequence:
1. Zoomdata_consul
2. Zoomdata_edc_* (i.e. data sources or connectors)
3. Zoomdata_query_engine
4. Zoomdata_data_writer_postgresql
5. Zoomdata_screenshot_service
6. Zoomdata_service

What should I do if I can't connect to SYSPRO Embedded Analytics?

There are a few possible reasons for your not being able to connect to SYSPRO Embedded Analytics. Therefore, check each of the following:

SYSPRO Application Gateway service:
1. Check the configuration file of the SYSPRO Application Gateway for an Embedded Analytics entry.
PostgreSQL:
1. Check if anything has been changed in your PostgreSQL configuration.
2. Confirm that you have the correct version of PostgreSQL: PostgreSQL 12.
SYSPRO Configuration:
1. Validate your connection to the SYSPRO Embedded Analytics endpoint by using the Test Connection function against the Embedded Analytics setup option (Setup Options > System Setup > Connectivity).

Using

Understanding Data Types

SYSPRO Embedded Analytics uses a classification system to interpret and bucket your data into three primary types:

Attributes
Metrics
Time

Primary Data Type: Attributes

Attributes represent a set of discrete labels (i.e. categories) that are often grouped together in charts.

Considerations:

Data that is categorical in nature.
Used in visuals as the “group by” object.

For example:

Airport, Airlines, User ID, State, City, product name

Related Data Type: Text

This is a related data type for attributes which has a relationship that’s defined based on being an object that can be categorized. Text is primarily used in conjunction with smart connectors that have a text search capability.

Considerations:

Data that is categorical in nature, just like attributes.
Primarily used with search-based connectors.

For example:

Apache Solr, Cloudera search and Elasticsearch use cases

Primary Data Type: Metrics

This is a numerical unit used for calculations and aggregations. Common metrics may be the order count, revenue generated, etc.

These are broken down into two sub classifications:

Numbers (i.e. floating values)
Integers (i.e. whole numbers)

Considerations:

Used in calculations and aggregation
Often used as a baseline count

Primary Data Type: Time

This is a special typing in SYSPRO Embedded Analytics as time is treated as the primary driver for smart data insights and provides the ability to view historical datasets over configured points in time.

Considerations:

You can explore historical data with the Timebar.
Some data sources allow for data playback and live streaming.

Referencing

Connections

The Connections panel lists all active connections and lets you create new connections if required.

This function lets you create a new connection type.

From the Connection Type window, select your required type of connection.
- MS SQL
- PostgreSQL
From the Input Credentials screen, enter your applicable credentials for the selected connector.
For example:

When selecting the MS SQL connector, enter the following information:
- Connection Name
- Jdbc Url
- User Name
- Password
Select the Validate function to save your newly created connection.

Your newly created connection is then added to the list of available connections.

Listview

The listview provides the following details for each existing connection:

Column	Description
Type	This indicates the associated icon for the connection type: = Microsoft SQL Server = PostgreSQL
Name	This indicates the unique name defined against the current connection.
Author	This indicates the name of the author (i.e. operator) who created the connection.
Modified Date	This indicates the date on which the connection was last changed.
Sources	This indicates the number of sources configured using this connection.
Actions	The Delete icon () within this column lets you delete the selected connection. You can't delete connections that are currently connected to a source (i.e. the Sources column must indicate 0 for the Delete function to be available).

Sources

The Source panel lists all active source definitions currently available and lets you leverage a connected data store to build new source configurations.

The listview provides the following details for each existing source:

Column	Description
Type	This indicates the associated icon for the connection type that was used to build the selected source: = Microsoft SQL Server = PostgreSQL
Name	This indicates the unique name defined against the current source configuration.
Connection	This indicates the connection that was used to build the selected source.
Author	This indicates the name of the source configuration's data creator (i.e. operator).
Modified Date	This indicates the date on which the data source was last modified.
Actions	Clear Cache This function lets you clear the cache by removing all of the aggregated results from the source. From the Cache Cleanup window, you can select your requirements for this function: Data Cache This clears the cache of all query results. Statistics Cache This clears the cache of the field's statistic metadata (i.e. min, max and distinct value numbers). Delete This function lets you delete the selected source. More Available Visual Types This loads the Available Visual Types window from where you can view all visualizations that are available for the selected source. Materialized Views This loads the Materialized Views window from where you can view existing externally created materialized views, or create a new one. Materialized views allow you to use pre-aggregated query results to speed up query processing in certain scenarios, especially when processing a query with heavily aggregated data. This boosts your visual rendering time. Materialized views only work if the metrics and groups in the materialized view definitions match those used by your visuals. For example: No benefit from using materialized views will occur if you define a materialized view for a Planned Sales metric in a data source, but none of the visuals in your environment use the Planned Sales metric. Consequently, it is a good idea to understand what data in your data source is used (or will be used) in visuals before you define a materialized view. A Count metric is required in all materialized view definitions.

This window is displayed when you select the Materialized Views option from the More menu against a specific source configuration.

This lets you view any existing materialized views which have been created externally against the source configuration.

The Add View button opens the New Materialized View (external) window from where you can create a new materialized view.

This dialog is used to identify where the aggregated result from a query is stored so it can be quickly recalled in visuals.

Field	Description
View Details	This lets you indicate the following information for the new materialized view: View name Target Connection This is a mandatory field. The connections listed for this field match the list of connections defined for the SYSPRO instance. The target connection is not required to be the same as the connection of the data source; it can be any other connection configured in Composer. Schema and Entity Use these fields to identify the target entity that will store the aggregated data. The target entity is required, while the schema is not. However, selecting a schema filters the list of entities so you can more quickly find the entity you want. As soon as an entity is specified, the Add Count, Add Metric, Add Group, and Add Filters functions become available. Description
Metrics	From here you can add count mapping to create your materialized view. Add Count This opens the Select Count work area from where you can add the count that you require from the target column. Select a source field in the Source Metric list and a Target Column to list which source field should be used, then select Apply to save your changes. Add Metric This opens the Select Metric work area from where you can add metric(s) to your materialized view definition. The Count metric must be added as it is mandatory. Other metrics are optional, but must match the metrics used in your visuals. Materialized views only work if you specify the metrics and groups used by your visuals in the materialized view definition. For example: If you use Sales (SUM) as your metric and State as your group in a visual, be sure to add these metrics and groups to your materialized view definition. If they don't match, SYSPRO will not use the materialized view to boost your visual rendering time. Select a source field in the Source Metric list and a target column in the Target Column list to which the source field should be mapped. Aggregated data for the source field will be taken from the target column to provide the results of the query. When you select a source field (other than Volume) you can also select a metric function to be used to aggregate the field data: Use the drop-down list to select the metric function. Use the search boxes at the top of the Source Metric and Target Column to quickly locate a source metric or target column in their lists. Select Apply to apply the mapping to the materialized view definition. Repeat this step for as many metrics as needed for the definition. If you have two visuals that differ only in their metrics, and you have an externally stored table containing pre-aggregated data for both visuals, you can specify all of the metrics for both visuals in a single materialized view. When the visuals are rendered, both visuals will be matched by the same materialized view.
Groups	This section lets you define the grouping you require within the materialized view. Select Add Groups to add groups to your materialized view definition. The groups must match the groups used in your visuals. Be sure that the target entity contains correct data for this materialized view. If there are more pre-aggregated group columns in the target entity than configured groups in the materialized view, the data for the query will be taken as-is from the target entity. This might result in incorrect data shown on the visual (e.g. non-unique group values and incorrect metrics). Select a source field in the Source Column list and a target column in the Target Column list to which the source field should be mapped. Aggregated data for the source field will be taken from the target column to provide the results of the query. Use the search boxes at the top of the Source Column and Target Column to quickly locate a source field or target column in their lists. Select Apply to apply the mapping to the materialized view definition. Repeat this step for as many groups as needed for the definition.
Filters	This section lets you customize the view further with customizable filters. Select Add Filters to add filters for the data that is stored in the target entity. Only requests that match the specified filters in the materialized view definition will be processed using the data from this materialized view. Select a source field for the filter. Use the search box at the top of the list to quickly locate a source field in the list. The Select Values dialog appears. Select an operator for the filter in the Operator drop-down menu. Optionally enter a custom value in the Customize field. The field name you supply is added and selected in the value list on the dialog. Select one or more values in the value list. Select Apply to apply the filter to the materialized view definition. Repeat this step for as many filters as needed for the definition.
Cancel	This ignores any entries made and returns you to the previous screen.
Save	This saves and creates the new external materialized view definition.

Source Configuration Wizard - Source Creation

The Source Creation window is presented when you select an existing source or the Add Source toolbar function.

Source Definition

Field	Description
Name	This indicates the source configuration's unique name.
Description	This provides a descriptive explanation of the source configuration's objective. This is useful so that other users can easily understand the source's use case.

Data Entity Definition

Data Entity Details - From Connection

These fields only apply if you selected From Connection as your data entity.

Field	Description
Data Entity Details
Data Entity Name	This indicates the unique name assigned to the data entity.
Select Connection	This indicates which connection is used for the source configuration.
Existing Entity	This lets you create the source configuration based on an existing row or materialized view (i.e. entity).
Custom SQL	This lets you create the source configuration based on a custom SQL to retrieve the data you want from your source, instead of selecting an existing row or materialized view from the connections list. When you select this option, a Custom SQL editing pane opens that you can use to write and run your SQL query. After you have run a successful query, the results populates the Available Fields and Preview table, and you can Apply your changes. Custom SQL queries are a powerful tool for performing complex data queries. However, be careful when creating custom SQL queries because it is easy to define a heavy query or a query that may overwhelm your database. Considerations: You can't save invalid SQL. Don’t use a semi-colon at the end of your statement. Variables (specified as custom user attributes) can be inserted in custom SQL. You can use a vertical bar (\|) in the SQL to separate the custom attribute name from a default value used for user definitions that do not have the custom user attribute defined. For example: The following custom SQL uses the value of the state customer user attribute to filter data source data for records from whatever state the user's state custom user attribute is set to. If a state custom user attribute is not defined for a user, a default of Alabama is used. Copy `SELECT * FROM Orders WHERE state = '${User.state\|Alabama}'`
Select Entity	This indicates which tables from the selected data connection are used for the source configuration. The drop down provides a catalog of tables and views found in the database schema. This only applies if you selected the Existing Entity option.
Select Schema	This indicates the schema used for the source configuration and is used to filter a list of entities for this connection.
Available Fields	This pane displays a list of columns found in the selected table, from which you can select or deselect to show to your users based on your requirements (i.e. for use within the visualization). All fields available from this data source are included by default. Disable (uncheck) specific fields to exclude them from the data source configuration. The fields, when disabled, are not included in any work areas of the data source configuration. If you attempt to remove a field in use by a visual or other object, SYSPRO will prevent you from saving your changes to the source configuration. Each row is assigned a data typing or classification – as displayed beneath the field's name.
Preview	This pane provides a preview of the data from the source for all fields (even if deselected in Available Fields) so that you can visualize how its currently being modeled.

Data Entity Details - From File

These fields only apply if you selected From File as your data entity.

Field	Description
Data Entity Name	This indicates the unique name assigned to the data entity.
Select File	This lets you select an available uploaded file for this data entity. A list of all native fields from this entity populates the Available Fields and Preview table.
Upload New File	This opens the File Upload window, from where you can add files to this source.
Available Fields	This pane displays a list of columns found in the selected table, from which you can select or deselect to show to your users based on your requirements (i.e. for use within the visualization). All fields available from this data source are included by default. Disable (uncheck) specific fields to exclude them from the data source configuration. The fields, when disabled, are not included in any work areas of the data source configuration. If you attempt to remove a field in use by a visual or other object, SYSPRO will prevent you from saving your changes to the source configuration. Each row is assigned a data typing or classification – as displayed beneath the field's name.
Preview	This pane provides a preview of the data from the source for all fields (even if deselected in Available Fields) so that you can visualize how its currently being modeled.
API Endpoints	Select for more information about appending data, replacing data, or deleting data from your file upload.
Edit File	This lets you edit the File Details of your uploaded file.

File Upload

This windows is displayed when you select the Upload New File function:

Field	Description
File Details	This lets you indicate the Display Name and Description for the source file.
Data Details	This lets you select the file you want to use for the source, as well as the number of records to display. You can also use the Single Quote Char. and Field Delimiter fields to refine your file upload even further.
Preview	This pane provides a preview of the data from the source for all fields (even if deselected in Available Fields) so that you can visualize how its currently being modeled. A detailed error message is displayed if the system detects any errors within the selected file.
Upload Settings	This lets you include the settings during the file upload. Select the Use Only File Structure option if you don't want to include settings in the upload.
Cancel	This ignores any entries made and returns you to the previous screen.
Save	This saves and uploads the selected file.

Join Definition

Create joins between pairs of data entities to create a Fusion data source:

You must have at least two data entities in your data source to create a join.

Therefore, this pane only applies once the source configuration has at least two data entities saved.
If you have more than one data entity in your source, all entities must be used in a join.

Joins

This pane lists the joins currently defined for the source configuration.

Use the Add function to configure additional join information.

Join Settings

Field	Description
Cancel	This ignores any entries made and clears the pane.
Apply	This saves the join information against the source configuration.
Entity Left	Select an available entity (from the data entities you defined) for the left side of the join.
Join Type	This indicates the join type: Full Outer Inner Left
Entity Right	Select an available entity (from the data entities you defined) for the right side of the join.
Enable Dimension Entity	Select the gear icon to enable dimension for one or both entities. This improves the performance of queries execution by removing unused data entities from the join.
Field Left	Select at least one field from this entity. You can add multiple fields by selecting the add field button (). Each row is assigned a data typing or classification – as displayed beneath the field's name.
Field Right	Select at least one field from this entity. You can add multiple fields by selecting the add field button (). Each row is assigned a data typing or classification – as displayed beneath the field's name.

Source Configuration Wizard - Fields

This panel only becomes available for new sources once the source configuration is saved within the Source Creation window.

The Fields panel lets you pre-format your tables as follows:

Show friendly names
Update table types
Strategically define numerical and time formatting

The following listview is displayed when you select to view the Fields or Custom Metrics panes:

Column	Description
Visible	This lets you toggle the visibility of fields/metrics within the source. This is useful if you don't want all fields/metrics to be visible to your users.
Label	This indicates the friendly name defined to represent the field ID.
Type	This indicates the field/metric type (i.e. classification).
Data Type	This indicates the data type (e.g. number, attribute, etc.) of the field (i.e. column).

When you select any line, its properties are populated within the Settings pane, from where you can maintain the details according to your requirements.

Once you have set up all of your fields, you may want to combine the available fields to build something a bit more custom to tell a specific part of your data story.

The Derived Fields and Custom Metrics sections let you select your available fields and metrics, and build new values using row level and aggregate functions.

Fields

This pane is populated with the details applicable to the selected field (in the Fields pane) and the options presented depend on the field's data type.

Setting	Description
Name	This indicates the field ID (i.e. the default name pulled from the data store) and can’t be changed.
Label	This lets you assign a friendly name to represent the Field ID. This makes it easier for end users to work with and understand the data points within the prebuilt visuals.
Data Entity Label	This indicates the name of the selected source configuration and can’t be changed.
Data Type	This indicates the data type (e.g. number, attribute, etc.) of the field (i.e. column). The Convert function lets you change the automatic classification (i.e. typing) of the field, if required.
Default Aggregation	The aggregation defaults to Count, but you can change this to Distinct Count if required. The Distinct Count functionality returns unique value results when analyzing data. For example: If you want to get a count of unique customers in a sales database. This functionality also determines the number of unique values in a column or expression within a selected table, by comparing all of the records pulled from the datastore by the data source configuration. This setting only applies to Attribute and Number data types.
Filter Display	This lets you control the behavior of filtered dialogs by data source. For example: You can define that only custom values are allowed. This setting only applies to Attribute data types.
Format	This lets you edit the current formatting defined against the field. This setting only applies to Number data types.
Granularity	This lets you define the granularity of the data's refresh rate. The Live Mode option is based on a Time field, and the refresh rate is based on the granularity applied to that field within the data source configuration. This setting only applies to Time data types.
Time Zone	This lets you define the time zone applicable to the field. This setting only applies to Time data types.
Custom Range	This lets you define a custom range against the field: Using an Integer or Number field: You can specify the initial default minimum and maximum values available for selection. Using a Time field: You can specify the initial minimum and maximum dates available for selection. This setting only applies to Number and Time data types.
Partition	This lets you define a partition for the field by entering the Partition Field and Partition Function. Certain connectors support partitions which allow you to link a partitioned field to another field to help improve the performance of filtering operations for a data source.

The Derived Field Editor is displayed when you select the Add Derived Field option of the Fields panel and helps you create and test derived fields for a data source.

Create a derived field by defining a formula composed of metrics and attributes that include row level functions. You can also include existing derived fields in your new derived field formula.

Field	Description
Editing space	Build your expression in this space. Syntax highlighting improves the readability of your expression and provides visual clues about the items being used and their validity. Auto-complete functionality is supported within the editor and therefore, a list of possible auto-completions appears after you type two letters. Function completions provide the type of function, the name of the function, the description of the function, and an example of how the function is used, including parameters. Field completions are available by typing either the field ID or the field label. The field ID appears in square brackets next to the field label when the two are different. Field completions provide the type of the field, the field label and ID, expressions for derived fields, and information about whether the field is hidden (as applicable). Metric completions provide the metric label and the expression that will be inserted into the editor when the metric is selected.
Expression Builder	This tool includes Row Level Functions and Fields to help you build your derived field.
Calculation Help	This provides more detailed information about the types of expressions supported.
Preview	This shows a preview of the results of your expression. Syntax and validation errors are displayed within the Preview area.
Save	This saves your newly created derived field. This function is disabled until the derived field has both a unique name and a successfully run expression.

Custom Metrics

A Volume metric is defined by default, which groups your data by volume (i.e. count) in Visuals. You can hide or rename this field as per your requirements.

This panel is populated with the details applicable to the selected field (in the Custom Metrics pane).

Setting	Description
Name	This indicates the metric ID (i.e. the default name pulled from the data store) and can’t be changed.
Label	This lets you assign a friendly name to represent the metric ID. This makes it easier for end users to work with and understand the data points within the prebuilt visuals.
Expression	This indicates the expressions used within the custom metric. The Edit function against this field opens the Custom Metrics Editor, from where you can view and maintain the metric's statement.
Format	This indicates the current formatting used within the metric. The Edit function against this field lets you maintain the numerical and/or time value formats.

The Custom Metrics Editor is displayed when you select the Add Custom Metric option of the Custom Metrics panel and helps you create and test custom metrics for a data source.

Create a custom metric by defining a formula composed of metrics and attributes that include row level functions and aggregation functions. You can include existing custom metrics in your new custom metric formula, and control the visibility of each metric.

Field	Description
Editing space	Build your expression in this space. Syntax highlighting improves the readability of your expression and provides visual clues about the items being used and their validity. Auto-complete functionality is supported within the editor and therefore, a list of possible auto-completions appears after you type two letters. Function completions provide the type of function, the name of the function, the description of the function, and an example of how the function is used, including parameters. Field completions are available by typing either the field ID or the field label. The field ID appears in square brackets next to the field label when the two are different. Field completions provide the type of the field, the field label and ID, expressions for derived fields, and information about whether the field is hidden (as applicable). Metric completions provide the metric label and the expression that will be inserted into the editor when the metric is selected.
Expression Builder	This tool includes a Function Library, Row Level Functions, and Fields to help you build your custom metric.
Calculation Help	This provides more detailed information about the types of metrics supported.
Preview	This shows a preview of the results of your expression. Syntax and validation errors are displayed within the Preview area.
Save	This saves your newly created custom metric. This function is disabled until the custom metric has both a unique name and a successfully run expression.

Source Configuration Wizard - Cache

The Cache panel enables you to maintain your preferences regarding the caching of source data.

Fields Statistics Configuration)

This pane only applies if the Statistics Cache option is enabled against the source configuration.

Column	Description
Field Label	This indicates the friendly name assigned to field ID.
Data Type	This indicates the data type (e.g. number, attribute, etc.) of the field (i.e. column).
Enable Cache	This lets you toggle your caching requirements and is enabled by default. Caching ensures that the aggregated results from the query are stored in memory. When a visual is then created later on, the request for the needed data is sent to the cache. Once those results are found, they are applied to the visual, thereby saving time. If the results are not found in the cache, the system then pushes down to the data store to retrieve the data and then store it within the cache for later use.
Schedule Refresh	The toggle within this column lets you define refresh settings at field level. This lets you select the exact fields that you want refreshed during your scheduled window.
Manual Refresh	The icon within this column lets you manually refresh the data source meta data at field level. For example: If you have changes to the fields that are coming from the database, this function refreshes the meta data associated with each field.

Source Configuration Wizard - Global Settings

The Global Settings Configuration panel lets you maintain various settings for the source configuration.

Time Bar Settings

If time fields are available in this data source, the following settings correspond with the timebar and time fields within that data.

The setting of defaults is not mandatory and can be changed manually during your dashboard creation. However, its good practice to ensure everything is aligned prior to building any visualizations.

Setting	Description
Settings Affecting New Visuals Only
Time Bar	This lets you enable or disable the time bar on new visualizations by default. The options associated with this setting determine the default time field to be used for new visuals, which allows users to view trend reports from any visual. Enable to allow setting of time bar related global settings here, and to enable the time bar on visuals by default. Users can then disable the time bar for individual visuals as needed. Disable to prevent setting of time bar related global settings and to disable the time bar on visuals by default. Users can then enable the time bar for individual visuals as needed.
Default Time Attribute	This lets you indicate an available time field to use, by default. The options vary based on the time field in your data source.
Playback	This lets you play back your data (like a data DVR). Playback is then automatically enabled for optimal time fields, including: Time fields with indexes Partitions Other query optimizations enabled within the data source
Time Range	This lets you define the time range for the time bar: Static Time: Define the exact dates of when to start and end the timebar. Dynamic Time: Select conditions for your time range. By default, the time range runs from the end of the data set minus one hour to the end of the data set as dynamic time. If you don't want to use the default, you can select a preset value from Presets, or design your own Conditions for the From and To fields.
Presets	This lets you select a time range from a list of presets.
Settings Affecting existing and New Visuals
Live Mode	This lets you automatically refresh the data from your data source, based on the refresh rate and delay. This excludes file-based sources. Ensure that your data includes a partition or index field, as without one of these fields available, playback and live mode remains disabled.
Prefer Sharpening	This allows Data Sharpening for data sources that support it.
Max Queries	When Prefer Sharpening is enabled, use this slider to adjust the maximum number of queries for data.

Other Settings

Setting

Description

Settings Affecting New Visuals Only

Tile Provider

This lets you define a default tile provider.

Supported providers include:

OpenStreetMap
MapQuest
CloudMade
MapBox

API Key

Indicate the API key for your tile provider, if needed.

Global Filters

These options allow you to define your filter settings for new visuals.

Defining initial filters increases the performance of new visuals the first time you load them.

Setting	Description
Settings Affecting New Visuals Only
Add Filter	This lets you add a filter to new visuals created using this source.
Nest Filters	This lets you nest your filters for new visuals created using this source.

Visual Gallery

The Visual Gallery lists all existing visualizations that are driven by your defined sources. This includes all visuals created within both the Visual Gallery and Library.

This is also the panel where you can build, customize and save your individual visuals. These visuals can be placed into any number of dashboards that you're planning to build, so they should be purposefully designed to create the required user case.

If required, you can tweak and customize an existing visual or even build a new visual from scratch, during your dashboard creation within the Library panel.

Listview

The listview provides the following details for each existing visualization:

Column	Description
Type	This indicates an icon which represents the type of chart being used by the visual.
Name	This indicates the name defined against the visual.
Author	This indicates the name of the visual's content creator (i.e. operator).
Usage	The usage metric indicates the number of times the particular visual is being used across the application.
Modified Date	This indicates the date on which the visual was last changed.
Actions	The Delete icon () within this column lets you remove the visual and delete it's design. You can't delete visuals that are currently in use (i.e. the Usage metric must indicate 0 for the Delete function to be available).

Visual Designer

The Visual Designer panel is opened once you select to create a new visual.

Sidebar Customization Options

When you select an existing visual (or when you create a new one) the following customization options are presented on the right-hand side of the preview window:

Selecting the Apply function after making any changes refreshes your view of the visual so that you can see your changes straight away before saving the visual.

Option	Description
Visual Style	This lets you change the current type defined for the visual. This is useful when strategising ways to present your data so that it provides the most information possible.
Sort and Limit	This lets you define how the data must be sorted, aggregated, ordered and/or limited within the visual. Sorting allows you to sort your data by a metric or attribute, to better organize the underlying data. Whereas limiting sets a cap for the amount of data points available on the visual, which is used to display metrics (e.g. top 10) or to simplify more data heavy visuals.
Filters	This lets you use row-level, group or saved filters to narrow the scope of the data in a visual by either an attribute or metric. You can then use filters to quickly find and display data on the dashboard visuals. Considerations: When all the visuals in a dashboard use data from the same data source, you can apply row-level and saved filters for the data in all the visuals on the dashboard. When more than one filter is applied to a visual (either via the visual itself or via a dashboard filter), the filter conditions are ANDed. In other words, both filter conditions must be met for the data to appear in the visual. If the style of your visual is an arc gauge, KPI chart, table (raw data), histogram, or map markers chart, the Group tab is available, however you can't create a group filter because all filters for these visual styles are row-level filters.
Time Bar	This lets you set or change the time series attribute for the visual.
Settings	This lets you make visual and functional changes (e.g. orientation, labels, style, etc.).
Rulers	This lets you add a threshold to the chart (i.e. customize how the X and Y grid lines appear). This only applies to charts that have an X and Y axis.
Color	This lets you change the color palette of the visual, as well as toggle the visibility of your chart's legend.
Interactivity	This allows you to toggle off and on the interactive objects and menus on the visual itself (i.e. define the level of user interaction allowed within the visualization). This is useful if you want to limit the level of access that your end users have to the visual. Options available include: Data Interactivity This refers to the level of interaction allowed for sorting, filtering, grouping and metrics. Radial Menu This refers to the ability to perform analysis on the data within the visual (e.g. zoom, filter, trend, etc.). Visualization This lets you enable or disable the Sidebar Customization Options for your end users (e.g. settings, rulers, copy, etc.).
Info	This provides a summary of the visualization's properties (e.g. Name, Data source, etc.). From here you can change the visual's title and/or name.

The available configurable objects vary based on the visual's classification.

Other Customization Options

The following customization options are available around your visualization canvas:

Option	Description
Group \| Metric (displayed beneath or on the right-hand side of the chart)	The following options let you to change any of the available attributes: Group This object allows you to select an attribute to act as your group by clause, thereby changing the visual design. Metric This allows you to select from your list of available metrics to use in tandem with your group object. For example: You can set your group to be customer account by city, and your metric as the number of orders. In addition to these options, there may be secondary customization options available depending on your visual type (e.g. color, trend, etc.). These options vary based on the type of visual you're working with. For example: The Color attribute lets you change the color used within certain charts to align with one of the used metrics.
(displayed above the chart in the left-hand corner)	This opens the filter options pane, from where you can add row-level, group or saved data filters within the visual.
Show More (displayed above the chart in the right-hand corner)	This opens a mini menu with the following options: Create Keyset Selecting this opens the Save Keyset menu from where you can define the keyset properties and preview it before saving it. Export This lets you save (i.e. export) the visual in one of the following formats: Image (PNG) Document (PDF) Visual Data (CSV) Raw Data (CSV)

Option

Description

Group | Metric

(displayed beneath or on the right-hand side of the chart)

The following options let you to change any of the available attributes:

Group

This object allows you to select an attribute to act as your group by clause, thereby changing the visual design.
Metric

This allows you to select from your list of available metrics to use in tandem with your group object.

For example:

You can set your group to be customer account by city, and your metric as the number of orders.

In addition to these options, there may be secondary customization options available depending on your visual type (e.g. color, trend, etc.). These options vary based on the type of visual you're working with.

For example:

The Color attribute lets you change the color used within certain charts to align with one of the used metrics.

(displayed above the chart in the left-hand corner)

This opens the filter options pane, from where you can add row-level, group or saved data filters within the visual.

(displayed above the chart in the right-hand corner)

This opens a mini menu with the following options:

Create Keyset

Selecting this opens the Save Keyset menu from where you can define the keyset properties and preview it before saving it.
Export

This lets you save (i.e. export) the visual in one of the following formats:
- Image (PNG)
- Document (PDF)
- Visual Data (CSV)
- Raw Data (CSV)

Library

The Library acts as a repository for housing all of your existing dashboards (either created by you or shared with you from another author) and provides the following capabilities:

Build new dashboards (i.e. a collection of visuals)
Customize existing dashboards
Create new visuals from scratch for placement on the dashboard canvas
Customize existing visuals
String multiple visuals together to globally filter
Use built-in components to analyze and drill into your data

Listview

The listview provides the following details for each existing dashboard:

Column	Description
Fav	This identifies favorite dashboards using a star icon. You can click on the star in this dashboard to make the selected dashboard a favorite or remove it from favorites. This is useful if you have a large amount of dashboards and want to have easy access to a select few by using the Favorites filter.
Name	This indicates the name assigned to the dashboard.
Data Source	This indicates the data source used to drive the dashboard.
Author	This indicates the name of the dashboard's creator (i.e. operator).
Modified Date	This indicates the date on which the dashboard was last changed.
Actions	The Delete icon () within this column lets you remove the dashboard and delete it's design. Considerations: If you delete a dashboard that has been shared with another user, it is deleted for all users. You can't delete a linked dashboard. If any other visual is linked to the dashboard, you must first remove the link from the visual or delete the visual's source dashboard.

Dashboard Designer

The Dashboard Designer panel is launched when you select the Add Dashboard function from the Library.

Toolbar Menu

Field	Description
Dashboard Interactivity	This allows you to toggle the interactive objects and menus on the dashboard itself (i.e. define the level of user interaction allowed). This is useful if you want to limit the level of access that your end users have. Options available include: Editing This refers to the level of interaction allowed for editing various components of the dashboard (e.g. Filter, Delete, Adding to favorites, etc.). Data This refers to the ability to refresh the dashboard data, define dashboard links and change the interactions available. Exporting This lets you enable or disable the export capabilities.
Dashboard Interactions	This opens the Dashboard Interactions screen, from where you can define Cross-Source Links and/or Cross-Visual Filtering for the dashboard.
Dashboard Links	This opens the Dashboard Links screen from where you can view existing links, or add new links from a visual to another dashboard. While working with your dashboard, you may need to analyze data from other dashboards. You can link a visual from your dashboard to another dashboard, allowing you to quickly access other dashboards with related information. When linking one dashboard to another, you can also elect to have the target dashboard inherit the filters from the source dashboard. From the Dashboard Links screen, use the Add Link function to select which visual or dashboard you want to link to. By default, the Inherit Visual Filter option is enabled, and the dashboard passes the filters currently used on the dashboard (or the filters applied based on what is selected when the dashboard link occurs) to the linked dashboard. If you do not want the filters from the dashboard carried over, disable Inherit Visual Filter. The filters are only carried over if the dashboards are using the same data source configuration.
Export	This function is soon to be deprecated. For dashboard migration capabilities, please use the Embedded Analytics Export and Embedded Analytics Import programs. This lets you export the current dashboard in a variety of formats: Image (PNG) Document (PDF) Configuration file (JSON) When you select this format, dashboard interactivity profile settings are also exported with the other dashboard settings. This ensures that the exported dashboard can be imported with the same interactivity profile. Exported dashboards enable you to share your data with others or in the case of the JSON configuration export, to transfer a dashboard to another environment. Considerations: Exported dashboard JSON files can only be imported into other SYSPRO environments running the same version. When exporting, be aware that special characters are not supported. If your visual name or the name of the data source contains special characters, you need to update the name before continuing.
Refresh	This bypasses any available caches and queries the latest data from your data source(s). For example: If you have changes to the fields that are coming from the database, this function refreshes the meta data associated with each field.
Dashboard Description	This lets you toggle the display of the dashboard's description within the canvas.
Delete Dashboard	This lets you remove the current dashboard and delete it's design.
Add Visual	This lets you add an additional visual to the dashboard canvas: An existing visual from the Visual Gallery A new visual that you want to create from one of your data sources. Once selected, the visual is immediately added to the dashboard canvas. Functionality available: You can add as many visuals as you require within the dashboard canvas. You can re-size the visuals and move them around on your dashboard canvas as required. Use the context menu that appears on each visual to customize the dashboard visuals further.
Save As	This lets you save the current dashboard (along with its customization) as a new dashboard. This is useful as it saves time if you have a complex dashboards which you require variations for.
Save	This saves your newly created dashboard and adds it to the list of available dashboards within the Library. After a dashboard is created, you can explore its data and work directly with its various visuals: You can modify, copy, export or delete its visuals. The data on the visual can be filtered. You can share, export, or delete the dashboard. Selecting the dashboard from within the Library listview again lets you preview (or edit it). Previewing a dashboard is useful for dashboard authors to test what the end user experience will be like once the dashboard is embedded in SYSPRO.

Visual Customization Context Menu

The following options are presented when you select the ellipses icon () from one of the visuals within the dashboard:

Option	Description
Maximize	This lets you expand the visual to fill the entire canvas.
Edit Visual	This opens the visual's Sidebar Customization Options from where you can edit the visual's properties. This pane remains open so that you can click through your visuals on the canvas to edit accordingly without having to open the settings menu again.
Create Keyset	Selecting this opens the Save Keyset menu from where you can define the keyset properties and preview it before saving it.
Copy Visual	This creates a new visual based on the current visual selected and adds it to the canvas.
Export	This lets you save (i.e. export) the visual in one of the following formats: Image (PNG) Document (PDF) Visual Data (CSV) Raw Data (CSV)
Save As	This lets you save the current visual (along with its customization) as a new visualization. This is useful as it saves time if you have a complex visual which you require variations for.
Permissions	This opens the Visual Permissions window from where you can view and maintain the visuals access permissions for each user.
Remove Visual	This removes the visual from the dashboard.