Dashboard Technical Training - panintelligence.com · Dashboard Training Technical Course Prepared...

Dashboard Training Technical Course

Prepared by KMiller/SKidner

Date 24 Oct 2017

version 5.0 24 Oct 2017 Dashboard Technical Training

© Panintelligence 2017 Technical Course With HTML5 Screenshots page 2 of 294 company confidential

CONTENTS

1 INTRODUCTION 6

1.1 Objective 6 1.2 Outline 7 1.3 Dashboard Basics 10

2 WORKSHOP – EDIT & CREATE CHARTS17

2.1 Notes 17 2.2 Practical 19

3 WORK SHOP – DRILL AND FILTER 26


4 SESSION FILTERS 47


5 WORK SHOP - LAYOUTS 64


6 WORK SHOP – ADD USERS 84




7 CATEGORIES 99

7.1 Notes 99 7.2 Roles 113 7.3 Practical 116

8 WORK SHOP - METADATA 122


9 WORKSHOP KPI 158


10 WORK SHOP DYNAMIC DRILLING 173

How to Configure Dynamic Drilling 176

11 STYLING 198

11.1 Notes 198 11.2 Replace the Logo 200 11.3 Edit the style sheet 202 11.4 Practical 207

12 ADDITIONAL TOPICS 208

13 WORKSHOP – KPI USER LINKS 209




14 WORKSHOP - SYNCHRONIZE USERS 227


15 WORK SHOP - EXPORT 251


16 COLLABORATION 269


17 THE API 274

17.1 Notes 274 17.2 Solution 274 17.3 Example 285

18 APPLICATION CHAINING 291

18.1 Calling your app from the dashboard 291 18.2 Passing restrictions to the Dashboard 292

19 SINGLE CHART MODE 293

20 ANONYMOUS CHARTS 294





1 Introduction 1.1 Objective By the end of this course you will have the skills to construct our example Dashboard which presents data coming from a fictional call centre.



1.2 Outline The training data is held in a HyperSQL database. We will measure the performance of the organisation through KPI’s, which will be split and measured through group, division, branch and employee level. This will allow the head office to monitor everyone’s contribution. For training purposes, we will be doing some steps out of sequence. In the real world, you might typically undertake some or all of the following steps;

• Install the Dashboard

• Configuration

• Connect to a Data Source, specify Metadata

• Create new Users

• Import Users

• Create and schedule a KPI

• Edit and Create New Charts

• Drill / Filter Charts and Tables

• Design and Publish Layouts



We will actually learn how to configure the Dashboard in the following order.

• Edit and Create New Charts You will learn how to edit an existing chart, change its type and the variables used within it. You will also learn how to create a new chart from scratch.

• Drill / Filter Charts and Tables You will learn how to create a drill path on a chart. This will introduce you to chart filters, how to create your own filters, and finally how to filter charts within the Dashboard at display time.

• Design and Publish Layouts You will learn how to create a new tab and how to change the order of tabs. You will then be able to publish the layout you have created and define a layout as a default layout.

• Connect to a Data Source, including design of Metadata You will be able to use everything you learnt above to build some charts against your new connection.

• Create new Users Create a new user, login and test the user account. Constrain the user so that they can only see the charts and data that we want them to see. Import users from a data connection. Move users within the organisational structure. NT Authentication, IIS single sign on re-use of windows credentials

• Export and share Metadata Export the data connection you just created, share with your neighbour and import.



• Set up collaboration Send and receive messages from users – use SMTP to send messages

-- Optional End of Day –

• Install the Dashboard How to install on a windows server, brand and style the dashboard.

• Configuration This course is designed to be very hands on, so all the learning is through example. If at any point during the day you need help or clarification with any of the points then please feel free to question the instructor.



1.3 Dashboard Basics

Throughout this course you will be asked to perform key tasks repeatedly, these will become second nature during the course, but it’s worth running though the key features now.

1.3.1 Logging in

The dashboard is a browser based application; you can run it from any browser including Internet Explorer or Mozilla Firefox. On entering the URL http://localhost:8224 you will be directed to the logon page, and will be able to see the login prompt as below. If this is a brand-new install of the Dashboard then the default criteria are: Username: admin Password: dashboard

http://localhost:8224/



1.3.2 Chart Cell

We call any cell that holds a chart or a table a chart cell.



1.3.3 Chart Tools

On each chart cell there are a set of buttons in the top right corner. Which buttons are available depending on the chart and data.

The button with three stacked dots opens the full toolbar for the selected chart.



1.3.4 Pop-up windows Any pop-up windows, such as the toolbar, can be closed or hidden by clicking the close button as shown below.



1.3.5 Tree Lists Tree lists are used to display data in many places. A filter is available next to the magnifying glass, by default this does a ‘contains’ search amongst the relevant items.



1.3.6 Tabs \ Categories The tabs are displayed down the left-hand side of the dashboard. You access them by pressing the three stacked lines button. You can change the tab you are looking at by clicking on the name of a different tab.



1.3.7 Search Buttons You will notice search buttons (which look a little like a tennis bat)

These provide search facilities.



2 Workshop – Edit & Create Charts

2.1 Notes The buttons you require in this section of the course are all grouped together in the toolbar.

In addition, ‘Replace chart from library’ opens up the list of existing charts so that one chart can be replaced with another.



The ‘Edit chart’ and ‘Create new chart’ buttons both open up the chart explorer window.



2.2 Practical We are going to edit the chart ‘Last 10 Days Call Durations by Region’ 1. Change the chart type from a bar chart to a pie chart. Save the chart so that it now appears as a pie

chart on the front screen.



2. Edit the chart to show the average call duration by product.



3. Edit the chart, change into a stacked bar chart, showing the Insurer makeup for each Product Type.



4. Rename the chart to ‘Insurer makeup by Product’.

Now save the chart with the updated name (don’t save as a new chart).



5. In the ‘Morning’ category create a new chart in the bottom left hand chart cell.

This chart to display the trends of the number of calls received, showing the difference between renewals and new business. 6. Use the objects shown below to create the chart. Change the chart type to a line chart.

Add a trend line to the chart.



7. Name and Save the chart.

8. Open the chart in full screen mode.



You can hover over any points on the chart to get more information.



3 Work Shop – Drill and Filter 3.1 Notes In this workshop, we are going to explore how we drill and filter charts. Charts that have a drill path specified allow you to drill from the top level down to the underlying detail within the data. Take the chart we edited in Workshop 1. When I hover over one of the chart blocks my pointer changes into a hand to show that I can drill down on this chart.



If I click on the chart cell it will drill to the next level.



When drilling into a chart you can use the drill up button (one chevron) to drill back up or the home button (two chevrons) to jump right back up to the top level.

If we edit the chart; the drill path is displayed at the left-hand side. This allows you to see how the chart will behave when the user drills into it.



To select a chart type for a drill node, you click on the chart heading and select the type of chart you want.



To select items to show in the chart; select the data tab, select the X or Y Axis (or in the case of a table; press the + icon to add a Colum) and select the Item you wish to show from the list of available dimensions / measures



You can add or remove nodes using the links shown on the last node.



For each drill node you can decide whether the drill action will apply a filter or not.

If the drill box next to the dimension object is ticked, then a filter will be applied, so in the example above clicking on a given region and campaign will then only display data for that Region & Campaign at the next level of drill-down.



The best way to see this is to drill into the chart in the edit window, you will see the filter being applied in the bottom filter view.



Chart titles can be overridden as the user drills, and you can use {{ }} enclosing an object name (Case sensitive!) to make the title drill sensitive as shown below.



Filters

You can apply filters to the top level of a chart, these will then remain in place.

Select the dimension or measure you wish to filter on, select the operator, and select the value you wish to filter on. The chart will automatically refresh to reflect your change.



The user can also apply their own filters without editing the chart. These are called session filters and you will find out more about these in the next section.

You can click on any legend items in the chart and they will toggle on or off, to include or exclude those values from the chart.



3.2 Practical 1. Create a new chart (anywhere you like), showing the call count by region.



2. Edit the chart and add a drill path to drill through from Region -> Broker -> Sales Person.

3. Save and test the drill.



4. Edit and change the chart to drill from a bar chart to a pie chart to a pyramid.

5. Save and test the chart.



6. Now make the chart titles drill sensitive, so that the title changes as you drill down and reflects the item(s) drilled on in the prior step(s).




8. Edit the chart so that it only shows policies where ‘Call Days Ago’ was less than 5.




10. Edit the chart, add a new drill node and make the chart drill down into a data table, showing Customer Name, Policy Number and Call Count.



11. In this chart I can now see the details of customers that have been called multiple times.



I want to see why they were called so many times. Add another drill node to the chart to show Customer Name, Call Contact Date, Call Outcome and Average Premium.



12. Save and test the chart (remember that to drill on a table requires you to double click on the row; not

single click)

Find some customers that have been called multiple times.



13. Edit the chart to look like this:

Experiment with filters – by clicking on the legend and using the filter window.



4 Session filters The Dashboard allows users to filter data at run time. These filters are not saved in the chart and apply only to the session in which they are created.

These filters are all reset when you close the Dashboard and re-login.

4.1 Notes Legend Filters If the chart contains a legend….



…. then you can apply a filter by selecting the items in the legend.



The items in the legend will be highlighted to show that they are selected and the chart will only display data



relating to the selected criteria. Clicking a selected item again removes the selection. Removing all items in the legend is the same as having all items selected ; both show all the data in the chart. Notice in the example above that {{Product}} has been used in the title so that the user will see that the filter is applied. The variable replacements in titles are not only limited to drilling – they can relate to any filters applied as well.



Category Filters We will see in the next chapter how to create category filters. These are the filters that appear in the category (‘tab’) filter menu via the funnel icon.



The dashboard will apply these filters to all the charts in the category that it is possible to apply them to. If you have a category object filter on ‘Salesman’ however and one of the charts in a category comes from a data connection (‘Sick Days’ for example) that doesn’t have an object called Salesman then it won’t attempt to apply the category filter to that particular chart.



To reset the category filters back to their default values; simply press the “Reset button” on the filter menu.

Drag out filter

On line, bar and area charts you can use the mouse to draw out a filter region

This has the effect of zooming into the selected area.



Parent Child We can set a chart to be a parent chart and apply filters to all other charts on the page when a value is clicked on the parent chart.





To achieve this, we define a chart as a parent chart.

A chart is defined as a parent chart in the chart configuration section. Once defined as a parent chart its own drill path is not taken into account. Instead when a hart item (or a row if it is a data grid) is selected then filters are applied to other charts on the page.



You can tell that a chart is a parent chart as a parent chart icon is shown in its chart cell.

Clicking on an item (data table row, line chart intersection, pie chart slice etc) in the parent chart will filter other charts on the page. If the chart contains a legend then you can also click on the legend in the chart to filter the other charts in the category. You can create as many parent charts as you like on a page, and use combinations of charts and tables.



4.2 Practical In this practical we are going to filter some charts to use session constraints. We are going to modify the Filters Tab.



1. Apply a drag out filter to the ‘Policy Count By Date’ Chart. Then click the Refresh button on the chart to remove the filter.

2. Now experiment with a legend filter. Alter the ‘Products and Insurers’ chart to compare the

Admiral, Hastings and Tesco insurers.



Experiment with the filters at the top of the page.

Notice that as you select “North” in the first filter, the values in the second and third filters are automatically restricted.



3. Remove the page filters by selecting “All – Region” in the first drop list. This will reset the

next two drop lists, you will also need to drag out the date filter in the picker.

This functionality is controlled by cascading the category object values. You will see how to do this in the Categories workshop.



4. Finally change the top table to be a parent chart and filter other items on the page.

Edit the Product Details Table chart and set it to be a parent chart



It is a table so we also need to make sure that the Drill Down is ticked in the drill path.

Save the Table.

The icon will now show that this is a parent chart.

Single clicking on a row in the table will now limit the other charts on the page to show only data for the selected product.



5 Work Shop - Layouts 5.1 Notes

The Dashboard allows you to quickly change a layout, with the ability to insert charts, split chart cells and remove chart cells. The buttons that are important here are:



The Chart Library

The Chart Library enables the user to see charts which have previously been saved, grouped by category. Each category will show the charts owned by that category. These can then be clicked on to swap out the existing chart for the selected one or add the chart to an empty cell.



In addition, there is a filter section which enables the user to filter for a specific chart or charts.



Delete a chart In the Flash version if you hover over a chart node a delete box will appear. If the chart is used by anyone then you will receive a question asking if you really wanted to delete the chart.



Layouts The Flash Chart Library also stores any saved layouts as shown in the following screen shot. Previously saved layouts can also be deleted from the library using the ‘cross’ delete button.

You can drag and drop a chart out from the chart library onto an existing chart cell. This will replace that chart on the Layout. This change is automatically saved so that the next time that user logs in, that is the view presented.



Split Chart Cell Horizontally

This button will split the currently selected cell into two equally sized cells, one of which will have the existing chart in it, and the other will be empty. For example, it would change the following cell;

….. into the following……



…… where an additional chart can now be placed in the ‘empty’ cell on the right.



Split Chart Cell Vertically

This button works in the same way as the previous button, but splits an existing cell vertically rather than horizontally.



Remove Chart Cell

This button will remove the currently selected chart cell. Any charts contained therein are placed back in the library. An adjacent chart will ‘expand’ to fill the vacated space. Thus, the two cells below could change from;



…. to the following single cell ……



Publish Chart Layout

In Flash this button enables a user to ‘Publish’ a preferred layout of charts for a given category. Other users with appropriate access to the same category will then see the published layout in the Chart Library and can then choose to adopt the same layout en masse.



There is a checkbox on the Publish Chart Layout Window and on the chart library layouts list.

If this checkbox is ticked, then this becomes the default layout for the category (there is only ever one default layout for each category). Any new users created with this category or any users who have that category added to them will be set up with the default layout.



Applying a Layout In Flash you can apply a layout to a category tab simply by dragging and dropping it anywhere on the page.



Preview a Layout Before applying a layout, you can view it as it would appear on the tab.





Delete a Layout In Flash, if you have admin or chart designer privileges then you can delete the Layout.



5.2 Practical In this exercise, we will create and publish a new layout on the Call Volume Tab.

1. Select the Call Volume tab, and remove all chart cells except one.



2. This may take some trial and error but create the following layout. 3.



HINTS: You will need to create the following charts from scratch: o New Call Trend Analysis o Todays Average Call Duration o Call Count

In Flash publish the layout as the default layout for Call Volume.



4. Delete all chart cells apart from one again, then re-apply the Layout you created.



6 Work Shop – Add users 6.1 Notes Creating and editing Users Unlike most of the other configuration tabs (apart from Chart Colours) the ‘Users’ configuration tab has parameters at the highest level, so double clicking on ‘User’ in the Object List produces the following window;



From here the following global user parameters can be set for all users;

• Password Expires After X Days;

The number of days before a user is forced to change password.

• Minimum Password Length;

The minimum number of characters that have to be entered for a new password.

• Prevent Users From Using Last X Password(s);

The parameter entered here will prevent the user from recycling recent passwords.

• User Sessions Timeout After X Minutes Of Inactivity; The number of minutes of activity after which user sessions will be automatically timed out of the Dashboard (forcing the user to log on again)



Dashboard has to have a single root user which is shipped as ‘Admin’ therefore the new user button only appears alongside this shipped admin user in the Object List, rather than alongside ‘Users’, clicking this will allow the creation of a new user. The User Details panel provides the following enterable fields.

• Forename; The users forename

• Surname; The users surname

• Usercode; Username, this is the name actually entered when logging in and is not case sensitive. This value cannot be changed after the user is created.

• Email;The email address of this user.

• Image File; the name of a picture file for this user. The matching file should be placed in the directory "Dashboard/Dashboard/tomcat/webapps/panMISDashboardResources/users/" under the directory the Dashboard server was installed in.



• Role; The role this user has been assigned. There are five roles within Dashboard listed below in increasing order of authority;

o Chart Viewer; has basic ability to view and drill down on existing charts and browse the Chart Library to select new charts for display. No changes are saved.

o User; can do everything a Chart Viewer can do, but changes to layouts are saved for the next time the User logs in.

o Chart Explorer; can do everything a User can do, but can also edit, but not save, existing charts.

o Designer; can do everything a Chart Explorer can do, plus can create new charts and alter existing charts.

o Administrator; can do everything a Chart Designer can do, plus can setup and alter ‘Configuration’ parameters, indeed only users with this role will see the ‘Configuration’ category.

• Individual/Team; This is a description and does not change any functionality.

• Parent User; This is the Users' Parent User, for building a User hierarchy. It also enables default values to be passed down from the parent to the user.



The User Privileges panel provides the Administrator with the ability to enable, or revoke, one or more Dashboard functions for a User. The Administrator will always have the ability to perform all functions within the Dashboard and the setting/unsetting of these options have no effect on this user.



These include functions such as:

• Show Home Page; Enables the User to view the Dashboard’s Home Category.

• Collaborate; Enables the User to send emails from within the Dashboard.

• Edit Own Chart Targets; Enables the User to change their own KPI targets.

• Edit Variables; Enables the User to change Dashboard variables.

• Edit Chart SQL; Enables the User to modify a Charts' SQL.



The Security panel provides the Administrator with the following options:

• Disable User; Disables the user and prevents them logging in to the Dashboard in the future. The User will still exist in the Dashboard, but purely for historic and reporting reasons.

• Allow External Login; Indicates whether or not the User can log in to the Dashboard via the API.

• Password; User password for setup.

• Confirm Password; Confirmation of the above.

• Password Expires; Determines whether the password automatically expires. If ticked will prompt the User to change their password when first logged in, as well as when the password expiry number of days has been reached.



Then we have the following two drag and drop panels;

•

• KPI Links and Chart Targets; The administrator can drag Data Connections into here from the Objects Lists and then add the applicable user code. Used to ‘personalise’ KPIs; e.g. if this user is only to see Sales KPI’s related to their own sales performance. Used to link this Dashboard user to the equivalent user in the external database(s).

• Allocated Categories and Roles; The administrator can drag categories into here from Categories or Roles in the Objects List. This determines which Categories this user is allowed to view. Roles, in this context, are simply groups of categories.



Finally, we have the following two panels:



User Restrictions; The administrator can drag column(s) into here from Data Connections in the Objects Lists and then enter a restriction value. This can be used so that a given user only sees information for their own user/company/department without having to create separate charts for each of these areas. Effectively this automatically adds an extra ‘Where’ clause to the SQL generated by the Dashboard when the database is interrogated.

User Variables; The administrator can create additional User, non-System, variables which can be used within the Dashboard to provide information that the Dashboard wouldn't normally have access to. A common use is for providing the name of a SQL Server Database Instance, for use within Objects and Tables.



6.2 Practical

1. Create a new user for yourself. Forename: ________________ Surname:________________ UserCode:________________ Password:_______________

2. Grant access to 1 category. Category:________________

3. Log in as the new user. The user account should only have access to the category that you have granted access.



4. Restrict the user so that you can only get access to Data for the "Pet Insurance"

Product. Explain how you restricted the user account;

5. Restrict the user account so that you cannot get access to the configuration

panel.

6. Restrict the user account so that you cannot edit or create new charts.



7. Create two more users. Drag and drop them as children of the first user.



Open up the KPI tree by clicking the user icon on the glance panel.



You will notice that the user structure is mapped in the KPI. In a later workshop we will link the KPI to the user id.



7 Categories 7.1 Notes

Categories form the lists along the side of the Dashboard.



But they also perform other important jobs. The most important is security. If we look at charts (or later in the course, Data Connections & Objects) all have a category assigned to them.



Also, you will have noticed when creating a user, that the user has categories and roles allocated to them as well.

To put it simply a user only has access to entities within the dashboard that are assigned to categories he or she has been granted access to. A role is simply a way of grouping categories together.



To add a new category, you click the add category button.



Type in a name for the category, then save it. The category then appears (it is automatically assigned to you!)



This category behaves as all existing categories, so you can start to add charts and publishing layouts etc. Don’t forget to create a default layout for the category.



Categories can also be setup to nest within other category tabs. This is achieved by dragging and dropping onto another category.



Refreshing the browser will rebuild the categories. In flash, press the little lightning strike icon at the top left hand side to rebuild the categories.



We now have nested tabs



Note: The parent tab can’t now display any charts of its own as it is used to hold other tabs. It can however still be used for security purposes. We can also add object drop lists, effectively category level filters. We do this by dragging and dropping an object from a Data Connection into the Category Objects section.



Now when the tabs are rebuilt the Category Object ‘Drop List’ filter appears.

If you change the value in the drop list then this is applied to all the charts on the page. NOTE: Where charts come from the same data connection as the drop list object, then a filter is applied directly - any other charts will only have a filtered applied if there is also an object with the same name in their data connection.



You can apply more than one filter object to a tab/category.

Use as display tab: If you want to use a category only for security purposes and not as a tab, then you untick this box. Parent category: Can be used to move the category to or from a parent category without needing to drag and drop. Default position: The order the tab will appear in.



Manage Category Users: can be used to assign groups of users to a category. The following window is displayed on clicking the people icon:



To select multiple users either hold down the CTRL key and click on the relevant users, or select a user then hold down the SHIFT key and select a user further down the list to highlight all users between, and including, those two. Use the relevant button to either allocate or de-allocate the selected users to/from the Category.



7.2 Roles Roles are a way of pre-defining groups of Categories and User Privileges and these can then be assigned to a User in the same way as Categories.



Simply by creating a new Role, dragging and dropping Categories into the Allocated Categories panel and setting the relevant User Privileges, we have the ability to quickly recreate User set-up without having to manually perform each task for each User. To apply a Role to a User, drag and drop it into the Allocated Categories and Roles panel. The User will then automatically be assigned the Categories and User Privileges from within that Role. If the Role is subsequently changed any User who has that Role assigned to them will pick up the changes the next time they log in.



Multiple Roles can be assigned to a User and each unique Category and User Privilege will be applied.

NOTE: User Privileges are applied using the positive of both User and Role settings, therefore if something is turned on against the User but off against any allocated Role, then the privilege is On. Similarly, if turned off at User level but on at Role level then the Privilege is On. If you'd like the User Privileges to always be applied from the allocated Role(s) then ensure the settings are all turned off against the User.



7.3 Practical

1. Create a new category named Call Details.

2. Make the existing categories, Call Durations and Call Volume children of the new category.



3. Edit the Call Durations category and add droplists for Region, Broker and Sales Person.



4. Rebuild the tabs and try out the category drop lists.



Note: If you select North as a region, then the subsequent drop lists will automatically update to reflect the change.

5. Create a new Role called Call Centre Users.

6. Apply two categories to the Role and setup some User Privileges.

7. Allocate the Role to one of your Users.

8. Log In as the above User and ensure that the Categories and User Privileges have been applied.



LUNCH – APPLY EMPTY REPOSITORY





8 Work Shop - Metadata 8.1 Notes In this work shop we will learn how to connect to and model a new Data Connection. This is the area of the application where connections to external databases or spreadsheets are configured and where existing Data Connections can be edited or deleted.



To Create A New Data Connection Click the ‘new’ icon to the right of the word ‘Data Connections’ as shown below;



You will then need to complete the data connection fields shown below;

Name; The name by which the connection is known within the Dashboard. This is descriptive only and has no effect on the technical aspects of making the connection across your network. Can be renamed with no knock-on effects. Type; The type of data source (the underlying database engine) should be selected here from the pull down list. Username: The database username to be used to make the connection. Password: The appropriate password to be used in conjunction with the username specified in the previous step. Users should check the status of the caps lock key before entering the password. Category: Each data connection is constrained to one Category using this pull down menu. Only users who have access to the category specified will be able to edit or create a new chart against this connection.



Database Name: The name of the database to connect to. Host Name: The name (or IP address) of the machine hosting the database. Database Instance: Required for Informix and some SQL Server installations. Port Number: The port on the database server that should be used to make the data connection, this will default to ‘1433’ if SQL Server is chosen as the database type. Connection Pool: Allows the user to define how many connections will be held to a data source by the dashboard. Instead of having to create a new connection every time a query is run dashboard will pick a connection from this pool and use that. Chart Cache Period: The number of minutes that any data returned from a database will be pooled for. So if another user re-requests the same data within that period then they will be returned the values that where fetched from the database by the first request. It is possible to view the cache period of a chart. If you select the chart and click the view XML button the two fields at the bottom right tell you when the data was originally collected, and when the next refresh against the database would be triggered.



Once the user has completed the relevant boxes clicking on the ‘Connection Error’ warning will attempt to connect to the database specified and if it is successful that box will change to ‘Connection active’. A completed connection definition may therefore look something like this;

When the connection is working the user can click the disk icon next to the text ‘Object List’ to save the new connection. Alternatively hovering the mouse pointer over the connection name will reveal a red ‘X’, clicking this will also prompt the user to save the connection.



Once saved, the new connection will be added to the list of available Data Connections.



Adding Tables to A Data Connection Once the database connection has been created tables (or views) need to be added to it, to achieve this single click the ‘Add New Tables’ button on the floating ‘Tools’ palette and drag the mouse pointer (which should change to match the button) onto the black workspace and then click again to continue to the next step.



After clicking the user is presented with a window like this;



Here the user can manually type in the name of the table and a suitable alias or alternatively click on the magnifying glass circled above to open a table picker as shown below.



Again this screen also has a magnifying glass and clicking this will open search window as shown below.



To search the available data enter the search criteria into the search box to see the results in the grid below. E.g. searching the word 'AUDIT' would display any of the tables (or views) beginning with the text 'AUDIT'. Searching '.*AUDIT' would display any of the required tables (or views) containing the word 'AUDIT'. When the required table has been located it can be added to the data connection by double clicking on it. The user will then be returned to the screen shown on the previous page to enter the table alias.



When this is done the table can be saved by again clicking on the ‘Save’ icon or alternatively by using the red cross button that appears next to the connection name if the user hovers over it in the tab (a Save dialogue box will be displayed in this case).



Adding Columns to a Table To add columns (also known as ‘Fields’) to a new table definition simply highlight the relevant table first and then click on the ‘Add New Column’ icon on the Tools palette.



A new object definition screen will then appear at the foot of the table;



Name; This is the name by which the data object will be known within the Dashboard, it is not used in selecting the object from the database. Aggregate; If you select a ‘Type’ (see below) of ‘Measure’ or ‘KPI’ then you need to select one of the following options from this pull-down list;

• Max; return the maximum value

• Min; return the minimum value

• Sum; Sum up the values and return the total

• Cumulative Sum; This function generates a cumulative sum for a group of rows in a table. For example if you wanted to see cumulative turnover by day and the first 3 days were 1000, 2000 and 750 ; for the third row instead of adding each of the preceding rows (with a cumulatively negative effect on performance) it simply uses the running total from the previous row (3000) and adds on the current row to get a new running total of 3750 which can then in turn be used on the fourth row. When this methodology is applied to very large tables it can lead to massive performance benefits. An example of creating a cumulative sum is shown on the next page.

• De-Cumulative Sum; This is the same logic as the Cumulative Sum, but instead of showing and using the preceding data it instead looks at future data.

• Count; Count the number of rows

• Avg; Return the average value This therefore determines what calculation to perform on the Measure or KPI per Dimension. If you enter a type of

‘Dimension’ then this menu is greyed-out. Type; Select what type of data this object represents, the options are;

• Measure, an item to be measured, for example ‘Balance’ or ‘Turnover’ or ‘Number of Customers’ etc.

• Dimension, the item which you wish to compare the measure against, for example ‘Live Date’, ‘Branch’, Salesman’, ‘Product’, ‘Stock Line’ etc.

• KPI. Key Performance Indicator. There is a separate chapter on this.



Data Type; Select the data type of this object, the options are;

• Number; A numeric value object.

• Character; A character string value object.

• Date; A Date value object. Category; The category this data item belongs to, the options available in this pull down will match the categories available in the main Dashboard tabs. This is a security measure. The final four fields are used to enter the SQL logic required to bring back the data item in question, for example;



Clicking the ‘Test Object’ button (circled on the prior screenshot) after entering the required information should produce a window like the one below, verifying that the SQL can be executed and that it is efficient. Otherwise the SQL logic should be rewritten correctly.



Cumulative Sum Example The user wants to show daily and cumulative sales. Two columns are set up, firstly the ‘normal’ aggregated value:



And then the ‘Cumulative’ value:

We can see that the only difference between the two is the aggregate function. In a new chart we then use an existing column ‘Year Month’ as the Dimension and ‘Sale Value’ as the Measure, with ‘Cumulative Sale Value’ as an additional Measure. As a line chart this gives us the following chart.





8.2 Practical In this exercise, we are going to create a data connection, the parameters you require are

Type: HyperSQL

Username: sa

Password: (Leave blank)

Database Name: dashboard

Host Name: localhost

Port Number: 9910

There are 2 tables that we are going to model



1. Create a connection and make sure you connect to the database.



2. Add a table definition for PUBLIC.SALES_DETAILS_R (Use the introspection) – Make sure you add a table alias (e.g. SALES) – You will need to expand the PANREP node in the data structure.





Add an object for the customer’s Gender. Its type should be a Dimension.



3. Add an object for Sale Value. Its type should be a Measure.



4. Save the data connection and create a new chart on the Morning tab showing the sales volume comparing Male and Female customers.



5. Return to the data connection and add a reference to a new table, SALES_CALLS_DETAILS, and give it an alias (e.g. CALLS).



Add an object to the new table, referencing Call Status.



6. Join the tables together. To do this click the Add New Joins button and then click on the SALES table then the CALLS table.



7. Edit the chart and add the Call Status.



8. Add the following objects to the data connection.

Table Name Type Select

SALES_DETAILS_R Policy No Dimension SALES.AGREEMENT_NUMBER

SALES_DETAILS_R Product Dimension SALES.PRODUCT

SALES_DETAILS_R Sales Person Dimension SALES.SALES_PERSON

SALES_DETAILS_R City Dimension SALES.CITY

SALES_DETAILS_R Region Dimension SALES.REGION

SALES_DETAILS_R Policy Count Measure COUNT(*)

SALES_CALLS_DETAILS Call Count Measure COUNT(CALLS.DATE_TIME)



Your data connection should now have the following tables and objects:



9. Create the following charts and tables.



Chart Objects

Call Count By Product Call Count, Product

Chart That Drills Policy Count, Region

Sales Person Details Sales Person, Policy Count, Call Count,

Sale Value

Gender to Sales Comparison Already completed.



Put a drill path behind the chart in the top right corner (chart that drills) allowing you to drill from region to city to sales person to the policy number.



9 KPI Workshop 9.1 Notes

The glance panel is designed to track the value of a number of Key Performance Indicators (KPI). These values are designed to track key elements within the organisation that could have either a positive or negative impact on the performance of the organisation.



A KPI can be dragged and dropped over a chart for a better visual representation, to do this simply grab the KPI line in the glance panel that you are interested in and drag and drop it over an existing chart.



The chart will be temporarily changed to display a speedometer reading of the KPI.



Each glance panel line tells us three things about the KPI.

1. The name of the KPI

2. The KPI Trend

If the value is increasing the trend tick would point up, if it was decreasing the trend tick would point down. The colour of the arrow will also change depending on whether the move is desired. Thus with a value such as bad debt it is beneficial when it decreases so indicator would be green when pointing downwards.



3. The current value

A small coloured circle is shown next to the value which shows how the value relates to the target. Here we can see the value lies in a yellow zone. The idea with the glance panel is that it should draw the user’s attention quickly to a poor result, or a KPI requiring attention.



Consider the following Glance Panel ;

We can see very quickly that there are two KPI’s that the user should be concerned about; Rejection Rate; which has increased 1.2 points, and is currently in an Amber zone. Promise Kept Rate; whilst this is increasing (which is good) the overall rate is still within a red zone.



Creating a KPI When a KPI data object is created you can see that the first screen looks very similar to a ‘normal’ data object, however note that there are also two new tabs; ‘Schedule’ and ‘Scheduler Runs’.



The ‘Schedule’ tab shows the following information about the configuration of the KPI scheduler.



User Column; This optional parameter breaks the KPI down by the Dashboard user hierarchy. Thus, if the KPI related to sales, and this field was populated appropriately, then each user would see a KPI that just related to their own sales. If this is used then the User Column selected from the database (drag and drop from the Object List) should contain the same values as held in ‘Usercode’ in the User configuration.

• Preserve Previous; Used to select how many of the historic KPI values should be retained.

• Compare Previous; Used to select how many of the historic KPI values should be used to perform the calculation to ascertain the KPI. So, the last 120 values could be ‘Preserved’ for example but only the most recent 50 values might be used to ‘Compare’ for the trend.

• Refresh Every; Use a combination of the number field and the drop-down list to define how frequently the KPI value should be refreshed.

• Between Hours: The two sliders will determine the period during which this KPI will be calculated (at the frequency determined by the previous parameter).

• Days Of Week: This can be used to limit the scheduler to run minute and hourly refreshes of KPI’s only on certain days of the week. If all days are unticked then the scheduler runs on every day.



The ‘Scheduler Runs’ tab show the more recent runs of the KPI SQL;

With a green flag signifying a successful run and a red flag an unsuccessful run.

This window has the normal ‘Refresh’ Button and a ‘Run Now’ button which sets the process date/time of any waiting jobs to the current date and time. The scheduler will then pick this job up the next time it looks for overdue jobs; which means it will run within 60 seconds of pressing the button.



9.2 Practical 1. Convert the Sale Value object into a KPI.

Set it to run every minute. Change the select statement to ROUND(SUM(SALES.SALE_VALUE ) * rand(), 2 )

This will force it to produce a random value whenever it refreshes.



2. Click on the schedule tab, set values for Preserve Previous and Compare Previous.

3. Set the KPI to schedule every minute. NB: make sure that you drag the slider to set the Between

Hours values.



4. Save the data connection. 5. Reselect the KPI and go to the Scheduler Runs tab.

Wait until the KPI has run through successfully once.



Note: you can click the run now button to force the KPI to be refreshed as soon as possible. (Only push this once as each time you do it will reset the start time).

And use the refresh button to update the status.



6. Check that the KPI is shown on the glance panel.

NOTE: There is an additional section in this manual that will take you through creating KPI’s that are tracked by individuals.



10 Work Shop Dynamic Drilling Dynamic drilling allows you to drill into different areas depending on the value selected. In the example below, I have a chart that lists the total number of policies by Outcome.

The policy application may be Pending, Rejected, Not Taken Up, Accepted or Cancelled, which are the five different coloured bars.



If we didn’t use Dynamic Drilling the chart would drill down into the detail of each of the nodes showing the detail by different Dimensions or Measures. Whilst the data itself would be different depending on the item chosen, the objects themselves would be the same, so the same drill path was always linear. In the example above, we want to drill down and view different data, depending on which Outcome is chosen, so if we click on Pending we want to see why it’s Pending – or maybe how long it’s been pending for. Whereas if we click on Rejected we want to know why those applications were Rejected. This is where dynamic drilling becomes useful. Each individual outcome can have a different chart associated with it.



Dynamic drilling can be configured on any chart type or data grid.



How to Configure Dynamic Drilling A dynamic drill path is configured from within the regular Drill Path window. To create a dynamic drill path, add a new drill step then click on the “Chart” section and select “Drill to Chart” from the Chart Types.



This will create a dynamic drill step with the first node automatically created. To add additional nodes, you click the OR button.



This will then create a second child node as shown below.



You can add as many child nodes as required so that depending on the outcome the chart will drill to a different outcome.



Child nodes can themselves become parent nodes by clicking the add node button on them.



The tree can have as many nested child nodes as you require. As you will see further down this will allow you to create complex decision trees.

Nodes can be removed by clicking the remove node button, as shown below. If you remove a parent node then it’s children are also removed from the structure.



Setting a rule We are now going to set a rule to create a dynamic drill path which depends on the outcome of a data object. The example chart below lists the total number of policies by Outcome. The policy application may be Pending, Rejected, Not taken up, Accepted or Cancelled.



Click the button to edit the details. This will open the node detail panel.



Use the object drop list to select an object from the chart or drill path above.



Then set the operator and value.



Finally search for the chart that you want to drill depending on the outcome selected.



The node now goes green to state that this is a valid rule which leads to an outcome. The rule is summarised in the text. So here we have: If the Outcome selected is equal to Pending then show the Pending detail chart.



So with this set-up

If I click on the Pending segment in the chart, then I will get the Pending Detail Pyramid. Clicking on any other block will give a message stating that No drill path has been defined, as shown above.



Default Drill stage.

To mark a drill node as the default; you simply need to press the “set as default” button on the rule that you wish to make the default. If you set the first node to default, don’t define a rule and define a chart to drill too; all drill interactions with the top chart will take the user to the defined chart. The "set to default / not default” button will follow the node that is defined as the default route.



Now the example chart will drill.



We can add outcomes for all data blocks



So now, each separate outcome will lead to a different chart.



Decision Tree We can also create more complex decisions. These decisions will create branches so the structure starts to resemble a tree structure. So, if the measure in the chart is greater than a value then it will drill down a different route. For example, if I add a couple of child nodes under the Rejected stage, which is highlighted in orange below then the stage goes grey. This means it is valid but is a rule that does not lead directly to an outcome.



So I must now configure the rules for these child nodes.

I can also set-up a default node on this branch of the decision tree, which turns the node green.



So now we have.





The tree structure can be as complex as you want and the tree structure can be any depth, with unlimited nodes. It can also hang off a normal drill path. You can create a very complex drill structure but you must be careful to make sure that it is understandable to your target users. If it is too complex then the outcomes may seem unexpected and could lead to disorientation. This is where the chart home button is going to come in very handy. Also bear in mind that each chart you drill to could now have a complex drill path associated with it. What else can this achieve?

- Before V9 you would have had to create lots of similar drill down charts, i.e. your charts may have drilled to

the same detail table. This can now be simplified as you can create one detail table and drill to this from all

of your charts. Now you only need to create it once, and more importantly, you can change the one chart

and it is reflected in all charts drilling down.

- You may have ended up creating multiple charts that are similar, but they start at different places, so that

users with different access levels come in at the right level. Now this can be done creating each chart once

and linking them with a dynamic drill path.

- You can drill from one database to another, because you are drilling to a different chart this chart need not

be on the same database.

- Jumping through tables at different level of summarisation. So you could put a rule in place which would

force an extra step in a drill path if the data is still greater than a set number of rows, i.e. ask the user to filter

further before showing a detail table with > 1000 rows of data.



11 Styling 11.1 Notes

A common requirement is to apply your own logo and styles to the Dashboard. Everything you require to do this is held in the panMISDashboardResources website. This is part of the standard windows install, and is never overwritten, so any changes you make will not get replaced by an upgrade.





11.2 Replace the Logo To replace the logo, you need to swap the file named dashboard.png in the images directory of panMISDashboardResources. In a standard install this directory can be found at: C:\Program Files\Dashboard\Dashboard\tomcat\webapps\panMISDashboardResources\images Step 1. Try and get a nice .png graphic for your logo. This will always look best if it has a transparent background.

The image size is not constrained but you will need to resize to fit well with other style sheet elements, (the standard image is 150 px wide by 45 px high). If you don’t want a logo; create an empty.png file Step 2. Name the file dashboard.png



Step 3. Copy the file into C:\Program files\Dashboard\Dashboard\tomcat\webapps\panMISDashboardResources\images Step 4. Start a new browser session and navigate to the Dashboard. The new logo should now be used by your Dashboard instance.



11.3 Edit the style sheet The style sheet is a text file which contains all the information required to set the look and feel of the dashboard. If you edit the file C:\Program Files\Dashboard\Dashboard\tomcat\webapps\panMISDashboardResources\styles\ configurableStyles.css You will see that it contains lots and lots of style references to objects in the Dashboard.



A really useful resource to help with styling can be found at http://web.archive.org/web/20120516031743/http://examples.adobe.com/flex3/consulting/styleexplorer/Flex3StyleExplorer.html# This has moved in the past! – we have a copy of the application at pan – so if you are struggling to get to it let us know we can supply you with the file. This lets you build your own style sheet descriptions.

http://web.archive.org/web/20120516031743/http:/examples.adobe.com/flex3/consulting/styleexplorer/Flex3StyleExplorer.html

http://web.archive.org/web/20120516031743/http:/examples.adobe.com/flex3/consulting/styleexplorer/Flex3StyleExplorer.html



So, for example you wish to change the style of the main tabs in the Dashboard.

The style explorer will generate the style sheet you require on the right-hand side. You then find the corresponding items in the style sheet that you wish to change,



Replace the text and save.



Then start a new browser session and log into the Dashboard.



11.4 Practical If you look in the file locations on panMISDashboardResources you will find the file demoLogo.png. Use this file to change the logo within your Dashboard. Now have a go at changing the login window, the background and the category tabs in your application.



12 ADDITIONAL TOPICS

The remaining sections in this course are discussed during the course. You are welcome to complete these sections in your own time.. They build on from the topics that you have worked through in the course so far.



13 Workshop – KPI User Links 13.1 Notes To link a KPI to users within your database you need to consider THE TRIANGLE! This explains exactly what we need to do to maintain the links from our metadata to the database and back to the user.





We have already linked the KPI to the database through its select statement. We then need to tell the KPI which field to use to subtotal the KPI by user. This is generally the field in the database which holds the user code. Finally, for each user we then need to tell the dashboard which value returned by the user column relates to which user on each data connection. The best way to see how the system will proportion a value is to look at the data in a normal chart. So create a chart showing the Sale Value broken by sales person for example.





I then assign the values in the Sales person to my users.



I then tell the KPI which field to use to lookup the user id. The Next time the KPI runs the values from the table which relate to corresponding user ids will be assigned to that user. These values are then calculated up through the organisational hierarchy.





13.2 Practical 1. Take the random function out of the Sales Value KPI!! i.e. remove *rand()

2. Create the chart that shows a breakdown of the sales value by sales person



3. Now pick two sales people and create users for them. Make sure you set the User Code for the data connection as it appears in your chart.

Repeat the above process for the second Sales Person.



4. Run the KPI.

5. Go to the homepage and click on the KPI Tree button next to the KPI.

You should see your users in the tree, but all will have the same value as the KPI has only two parts of the triangle completed.





6. We need to complete the third leg of the triangle.

So that we make the final link from the KPI to the users. Edit the KPI and drag the sales person onto the user column field.



7. Save the data connection.

8. Run the KPI.



9. Go to the homepage and open the KPI tree.

The users will now have individual values.



10. In the KPI tree use the speedometer button to create user targets.







11. You can now either set targets for each individual user, or use the Copy Targets To Children button

to push the targets down through the organisation.



14 Workshop - Synchronize Users

14.1 Notes This function can be used to synchronise users between the Dashboard and your own application.

Clicking the synchronise users button brings up the following screen.



You will use a data connection as the source of the user table. You will either use an existing data connection which contains your user credentials or, you will need to create a data connection that contains these credentials.



Step 1. I select my data connections in the drop list



Step 2 I select the field I want to use as the usercode.



Step 3 I can also select values for the optional fields. (First Name, Surname, Email Address, Image File and Parent User Code)



Step 4 Select the seed user, this is the user that will be used as the template for all the users created. They will be given the same role and categories. Connection user id’s and restrictions will also be copied although the user code will be replaced as the value.



Step 5 Provide a default password. Click the Synchronise button.

You will then get to the confirm import function. This will show you firstly which users can be added by the import. You can click on the Select All button to add all of the suggested users. Alternatively, you can select only the users you wish to import.



You also have a list of users who exist in the target table but not in the Dashboard user list. Again you can select any users you wish to delete. NOTE: This does not give you the option to delete the top admin user. If you choose to delete a user who has children then those children will be moved up a level in the user hierarchy. You are also not given the option to delete the seed user if they do not exist in the target database. When happy click on the Synchronise Button, and the user creation / deletion will begin.



This was the user that was chosen as the seed in the import.



If I open up a user created by the import





A few things to note. 1. Because I did not supply a forename which is mandatory in the user screen, I am not allowed to resave this

user through the app without providing a name. 2. The connection user ID and user restriction Value and user code have been replaced with the user code from

the import. 3. The password is set to Password expire. As we have had to provide a default password we want to force the

user to change their password at first login.



14.2 Practical

1. Remove the two users you created in the above exercise.

2. Import the Regions.



Now it will look like....

3. Edit the regions and make role users, not admin. You will need to type ‘Region’ into the surname to save.





4. Import the Cities.





5. Check that the cities have been applied to the correct regions.

6. Import users from the data connection for all Sales People. This time making sure that you set the user code column for your data connection.



7. Check that the users have been linked to the KPI.



8. Run your KPI.





9. Open the KPI Tree.



10. Set tree depth to 4 and refresh



11. Set and push targets within the tree.



15 Work Shop - Export 15.1 Notes In this section we will learn how to export and import a data connection.

Exporting A Data Connection Data connections and the charts which use them can be exported from one iteration of Dashboard and imported into another (see next section). To do this click the ‘Export’ button to the right of the Data Connection name as shown below.



This will open the window shown below where the export can be named and its destination determined.

Importing A Data Connection Always make sure your repository is backed up before importing new Data Connections. A data connection can be imported using the ‘Import’ button on the top data connection node (make sure that if the data connection already exists that it is saved and not open – i.e. there is no tab).



The Data Source file upload window will appear. You can either type in the name and path of the file, or use the browse button to find it.

The tick box allows you to decide if you want to import any charts that reside with the Data Connection. Clicking on the browse button will open the file browsing window When you click the import button you will be presented with a changes summary screen.



This screen tells gives you a detailed list for the data connection that you are about to import. The colour of the node text and its hover over colour tell you what action is to be performed.



When importing the dashboard uses the names (as displayed in the changes screen) to match items in the repository. In the example above ‘Internal DCS’ is the name of the data connection. The dashboard looks to see if there is already a connection with the same name in the repository. If it finds a match then it will overwrite the existing data connection with the one you are about to import. The same is true for charts, which is why chart names are unique. Within a data connection the dashboard also matches the following; Tables – by Alias name Columns – by name Table joins – by tables joined to. The import also creates any categories that are required. Categories are created whenever any category that has been referenced in the import Data Connection does not exist in the repository. There is comprehensive help text attached to this window. The colours of the text can be ; Green = New attribute. Black = Existing unchanged attribute. Blue = Update attribute (hover over details icon for more update information). Red = An attribute which exists in the local Data Connection but not in the Data Connection file that you are importing. You have the choice to tick the checkbox to delete the attribute or keep it and merge the local changes with the new changes.



15.1.1.1 Example 1: Importing a data connection which does not exist in your repository

In this case all the items in the changes summary will be green as they are new. Note: pay particular attention to charts at this juncture; you could well have an existing chart with an entirely unrelated data connection which will be replaced by this import, solely because it has the same name as a chart you are about to import.



Click Close to abort the import (note no changes have been made at this point), or save to accept the changes and continue with the import.



If the connection is not active you will need to change this to point at a valid database. Example 2 – Importing an existing data connection without any changes



If you import objects that are unchanged they will show as black text. Example 3 – Importing a data connection which does not match the local repository version If changes have been made to the data connections which are not repeated in the file being imported, then the dashboard will highlight them in red.



By default the Dashboard will preserve the local additions. So if the user takes no action the imported data connection and the one currently in the repository will be merged together. If the user decides to fully synchronize the local data connection they can tick the boxes next to the changed objects and ask the dashboard to delete them when it does the import. If there are any dashboard objects which rely on these objects being present then the import will not complete and the user will be told that they cannot delete the objects.



If the changes exist in the file but not in the local repository, then they show up as green.



15.2 Practical

12. Export your data connection.

13. Re-Import the data connection.





14. Delete your charts, and then the data connection



Then Re-import the data connection.



Reset the connection criteria.

Then re-drag the charts from the chart library





15. Share your data connection with your next door neighbours, let them import it. 16. Now delete the charts and data connections.

17. Import the Sales data connection supplied by the instructor.



16 Collaboration 16.1 Notes

Collaboration is used to allow users to send and receive messages. These messages can be replicated through SMTP so also received via email clients i.e. Outlook. You turn collaboration from a checkbox on the user screen.





You can also enter an external email address from this screen.

You then setup the email server by opening the server settings. You can set up KPI messages to send automatic alert messages through the KPI targets.



Users can also send messages from the chart toolbar



16.2 Practical 1. Setup collaboration on two user accounts. 2. Send a message from one user to another. 3. Log in as the second user and view the message. 4. Set the SMTP server as zeus. 5. Change your KPI so that it sends an alert.



17 The API 17.1 Notes

Many customers request programmatical access to functions in the dashboard. We have currently been letting them use some of our basic back end SOAP services (most commonly Login) directly.

This will be problematic going forward, because it restricts us in what we can do to these services when making changes to the dashboard for new features and bug fixing. Any change could cause a customer system that called these web services to break, and we don’t want them to have to make changes just because we need to add new internal data.

17.2 Solution

The solution is to add an API specifically for external use, exposing the core dashboard functionality that is needed by customers so that they can access it from their own software and scripts.

This API is implemented as a set of REST style HTTP based services, returning XML. The rest of this document is dedicated to documenting this new API.



Login and Tokens

Login

To login to the application, perform a POST to /panMISDashboardWebServices/api/token/ passing in username and password as parameters. This will return a list of resources available.

<UserDetails>

<Token>ABC123</Token>

<Username>ADMIN</Username>

<Links>

<Users>/panMISDashboardWebServices/api/ABC123/user/</Users>

<Categories>/panMISDashboardWebServices/api/ABC123/category/</Categories>

<Charts>/panMISDashboardWebServices/api/ABC123/chart/</Charts>

<Connections>/panMISDashboardWebServices/api/ABC123/connection/</Connections>

<Layouts>/panMISDashboardWebServices/api/ABC123/layout/</Layouts>

</Links>

</UserDetails>

Notice that we return the URL of each top-level resource and that URL has the security token included inside it.

For convenience, there is a HTML form available by GET at /panMISDashboardWebServices/api/ which will call this service. This is the start point you should use when investigating the api.



Users

These services are provided to allow users to be manipulated.

Get User List

Performing a GET on /panMISDashboardWebServices/api/token/user/ will list the current users in the system.

<Users>

<User href='/panMISDashboardWebServices/api/ABC123/user/1/'>ADMIN</User>

<User href='/panMISDashboardWebServices/api/ABC123/user/2/'>RESTRICTED</User>

</Users>



Get User

Performing a GET on /panMISDashboardWebServices/api/token/user/id/ will return details of that particular user.

<User>

<Username>ADMIN</Username>

<Email></Email>

<Forenames>Welcome</Forenames>

<Surname>Administrator</Surname>

<PersonTeam>I</PersonTeam>

<Picture></Picture>

<Id>1</Id>

<ParentId>0</ParentId>

<Role>0</Role>

<RoleDescription>Administrator</RoleDescription>

<Collaborate>true</Collaborate>

<Disabled>false</Disabled>

<ExcludePasswordExpiry>false</ExcludePasswordExpiry>

<InheritChartPreferences>false</InheritChartPreferences>

<InheritStyles>false</InheritStyles>

</User>

Create User

To create a new user, perform a POST to /panMISDashboardWebServices/api/token/user/ passing in parameters with the same name as the tags in the Get User example above, plus Password This will return the details of the new user as per Get User above. If there are problems, a HTTP 500 will be returned with exception details.



Maintain User

To maintain a user, perform POST on /panMISDashboardWebServices/api/token/user/id/ passing in the values to update for the user, using the parameters with the same name as the Get User call above. Not all parameters need to be specified.

Delete User

To delete a user, perform a DELETE to /panMISDashboardWebServices/api/token/user/id/. This will return a HTTP 200 on success, or HTTP 500 on failure. If the id specified does not exist, a HTTP 500 will be returned.

Categories

These URLs are provided so that categories can be manipulated.

List Categories

To list categories, perform a GET on /panMISDashboardWebServices/api/token/category/. This will return a list of all categories, for example:

<Categories> <Category href=”=”/panMISDashboardWebServices/api/ABC123/category/1/”>Home

</Category>

<Category href=”=”/panMISDashboardWebServices/api/ABC123/category/4/”>Accounts

</Category>



</Categories>

Get Category Details

To get details of a given category, perform a GET on /panMISDashboardWebServices/api/token/category/serial/. This will return details about that particular category.

<Category>

<Name>Home</Name>

<Parent>null</Parent>

<Position>1</Position>

</Category>



Create Category

To create a new category, perform a POST on /panMISDashboardWebServices/api/token/category/ passing in parameters with the same name as the sub tags above.

Maintain Category

To maintain a category, perform a POST on /panMISDashboardWebServices/api/token/category/serial/ passing in the parameters that need to be changed. The same parameters as for Create Category are supported. Not all parameters need to be specified.

Delete Category

To delete a category, perform a DELETE on /panMISDashboardWebServices/api/token/category/serial/. If the delete succeeds, a HTTP 200 will be returned. If the DELETE fails, a HTTP 500 will be returned. If the category does not exist with the specified serial, a HTTP 500 will be returned.



Variables

These URLs are provided so that categories can be manipulated.

List Variables

To list variables, perform a GET on /panMISDashboardWebServices/api/token/variable/. This will return a list of all variables, for example:

<Variables>

<Variable href=”/panMISDashbaordWebServices/api/ABC123/variable/1/”>Home </Variable>

<Variable href=”/panMISDashbaordWebServices/api/ABC123/variable/4/”>Accounts

</Variable>

</Variables>



Get Variable Details

To get details of a given variable, perform a GET on /panMISDashboardWebServices/api/token/variable/serial/. This will return details about that particular variable.

<Category>

<ID>2</ID>

<Name>YAHOO_MAP_ZOOM</Name>

<Value>13</Value>

<SystemInd>true</SystemInd>

<UserId>null</UserId>

</Category>

Create Variable

To create a new variable, perform a POST on /panMISDashboardWebServices/api/token/variable/ passing in parameters with the same name as the sub tags above..

Maintain Variable

To maintain a variable, perform a POST on /panMISDashboardWebServices/api/token/variable/serial/ passing in the parameters that need to be changed. The same parameters as for Create Variable are supported. Not all parameters need to be specified.



Delete Variable

To delete a variable, perform a DELETE on /panMISDashboardWebServices/api/token/variable/serial/. If the delete succeeds, a HTTP 200 will be returned. If the DELETE fails, the a HTTP 500 will be returned. If the variable does not exist with the specified serial, a HTTP 500 will be returned.

Data Connections

These URLs provide basic connection functionality.

Listing Connections

Perform a GET on /panMISDashboardWebServices/api/token/dataconnection. This will list all of the available connections.

<Connections> <Connection href=”http://localhost:8224/ABC123/dataconnection/2/”>Sales</Connection> </Connections>

Fetching Connection Details

Perform a GET on /panMISDashboardWebServices/api/token/dataconnection/serial/. This will return details of the connection, in the same format as the file created when exporting a connection from the dashboard front end.

http://localhost:8224/ABC123/dataconnection/2/



Import Connection

To import a connection, perform a POST on /panMISDashboardWebServices/api/token/connection/.

Pass in the single parameter ImportXml which has the value of the contents of the exported connection xml. This can also be used with xml taken from a file exported from the dashboard. If the data connection is password protected then an extra parameter MaintainPassword should be passed in to authorise the update.

Deleting a Connection

Perform a DELETE on /panMISDashboardWebServices/api/token/connection/serial/. If the delete succeeds, a HTTP 200 will be returned. If the DELETE fails, the a HTTP 500 will be returned. If the connection does not exist with the specified serial, a HTTP 500 will be returned. If the data connection is password protected then an extra parameter MaintainPassword should be passed in to authorise the delete.



17.3 Example Firstly I can login into the API through my browser. http://localhost:8224/panMISDashboardWebServices/api/ (Note the slash on the end!!)

If I login this will then pass me the url’s I need. (They have the dashboard security token already in place)

http://localhost:8224/panMISDashboardWebServices/api/



If I wanted to do this programmatically then I would call the post from my code. (i.e. in Python this would look like import httplib, urllib from xml.etree.ElementTree import fromstring



lConnection = httplib.HTTPConnection('localhost:8224') lHeaders = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"} lParams={'username':'admin', 'password':'pancredit'} lConnection.request(‘POST’, ‘/panMISDashboardWebServices/api/token/’, urllib.urlencode(lParams), lHeaders) lResponseObject = lConnection.getresponse() lStatusCode = lResponseObject.status lResponse = lResponseObject.read() lTree = fromstring(lResponse) lToken = lTree.findtext("Token") The Python code above will return a security token for the requested user (here it was hard coded for my admin user). I could then use other calls to fetch data. So if I want a list of the users I would call. http://localhost:8224/panMISDashboardWebServices/api/5E9mtdch69NQcjiEZTgAd2e5RzViPwUWq1nmpuIlGfafD5SpT1/user/

http://localhost:8224/panMISDashboardWebServices/api/5E9mtdch69NQcjiEZTgAd2e5RzViPwUWq1nmpuIlGfafD5SpT1/user/

http://localhost:8224/panMISDashboardWebServices/api/5E9mtdch69NQcjiEZTgAd2e5RzViPwUWq1nmpuIlGfafD5SpT1/user/





If I want to fetch a particular user I then call the relevant user I can select a particular user.



If I wanted to update H PATEL (I’ll set his password to expire!) I would do a post to the same url. In Python the code would look like this: lHeaders = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"} lParams={‘ExcludePasswordExpiry’:'true'} lConnection.request(‘POST’, ‘/panMISDashboardWebServices/api/5E9mtdch69NQcjiEZTgAd2e5RzViPwUWq1nmpuIlGfafD5SpT1/user/’, urllib.urlencode(lParams), lHeaders)



18 Application Chaining

18.1 Calling your app from the dashboard You can apply a drill path that will allow you to drill out to your own application, via url.

Any items enclosed in {{ }} will be replaced with the drilled object values. So if I have drilled into a Pet Insurance



product, then {{Product}} will be replaced with Pet Insurance. You can also use [[ ]] to be replaced with a user or system variable.

18.2 Passing restrictions to the Dashboard

You can pass filter restrictions into the dashboard through the URL. http://localhost:8081/MISDashboard/?dashboardToken=zq5FGhEh6E8vjrjiT7b4OQ6ofv0ufk2Yr72BEUYH4uJ5KEQeUg&chartID=137&filters=[[Region]] LIKE '%25o%25' AND [[City]] = ‘Middlesbrough’ You define the where clause in filters, and put [[ ]] around the object you want to replace. NOTE: It does not allow an OR.

http://localhost:8081/MISDashboard/?dashboardToken=zq5FGhEh6E8vjrjiT7b4OQ6ofv0ufk2Yr72BEUYH4uJ5KEQeUg&chartID=137&filters=%5b%5bRegion

http://localhost:8081/MISDashboard/?dashboardToken=zq5FGhEh6E8vjrjiT7b4OQ6ofv0ufk2Yr72BEUYH4uJ5KEQeUg&chartID=137&filters=%5b%5bRegion



19 Single Chart Mode

The Dashboard can be embedded as many times as you want in your app and called in single chart mode. Here a single chart can be displayed wherever you want it in your application.

https://localhost:8224//MISDashboard?dashboardToken=HVSVkU5G8r97FSGKTLz0WZXri9GCxL9dUneDFAlHk0cOVjq5W7&chartID=141

The Chart ID can be found by looking at the XML for a chart in the Dashboard.

https://localhost:8224/MISDashboard?dashboardToken=HVSVkU5G8r97FSGKTLz0WZXri9GCxL9dUneDFAlHk0cOVjq5W7&chartID=141

https://localhost:8224/MISDashboard?dashboardToken=HVSVkU5G8r97FSGKTLz0WZXri9GCxL9dUneDFAlHk0cOVjq5W7&chartID=141



20 Anonymous Charts You can make a chart anonymous, this means that it can be called or embedded as above and requires no authentication.

Date post:	30-Aug-2019
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