Cognos Lab Instructions

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IBM Training
Student Exercises
IBM Cognos Analytics
Hands-On
IBM Technical Enablement

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January 2017 edition
The information contained in this document has not been submitted to any formal IBM test and is distributed on an “as is” basis
without any warranty either express or implied. The use of this information or the implementation of any of these techniques is a
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environment. While each item may have been reviewed by IBM for accuracy in a specific situation, there is no guarantee that the
same or similar results will result elsewhere. Customers attempting to adapt these techniques to their own environments do so at
their own risk.

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Exercises description
This lab guide is intended to provide you with hands-on experience in using
Watson Assistant to build a retail chatbot.
This course includes the following exercises:
• Exercise: Explore Cognos Reports and Visualizations
• Exercise: Upload data into Cognos
• Exercise: Explore Cognos data integration
• Exercise: Build a Dashboard
• Exercise: Embed the Cognos Dashboard into our Application
The exercises should be completed in the same order as listed before moving
on to the next exercise.

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Course materials may not be reproduced in whole or in part without the prior
written permission of IBM

Pre-requisites:
a) An IBM Cloud account. The account is free and provides access to
everything you need to develop, track, plan, and deploy apps. Sign up for
a trial. The account requires an IBMid. If you don’t have an IBM ID, you
can create one when you register. Open up https://www.ibm.com/cloud/
b) A Cognos account.
Note: The illustrating screenshots provided in this lab guide could be slightly
different from what you see in the IBM Cloud interface you are using because
of updates to IBM Cloud since the lab guide was created.

© Copyright IBM Corp. 2018
Course materials may not be reproduced in whole or in part without the prior
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Exercise 01: Explore Cognos Reports and
Visualizations.
Exercise Instructions
Lesson 1.1 Sign up for IBM Cognos and explore parts of
the dashboard.
Pre-requisites:
-

For this step, you should be able to log into IBM Cloud and navigate to your
dashboard.

1. Open https://www.ibm.com/account/us-en/signup/register.html?a=CognosAnalytics in Chrome.
2. Enter relevant information and click Continue.

3. You should be greeted by the Cognos Analytics Dashboard.

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4. Note the different parts of the home page contents.
Recent. These tiles will not be visible until content is added. The default view of the
homepage is show tiles that represent the most recently modified content. The most recent
six (6) are presented. The recent list may be expanded out to the most recent twenty (20) by
selecting the Show more… Select Show less… to collapse the view back to the most recent
six 6).

Drop Zone. Users may now easily upload files to Cognos Analytics using the Drag and
drop your files or browse section at the bottom of the home page.

Quick Reference. Users will find resources to help them get started in Cognos Analytics
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including videos, same data sets and links to the Cognos Analytics User Community and the
IBM Knowledge Center.
5. Note the different parts of the Navigation panel on the left.

Home. The Home button appears in the top-left corner of the navigation panel. Users may
return to this homepage at any time with the click of this button.

Search. Search. The New Smart Search in Cognos Analytics provides a modernized search
engine that uses a smart, intent-driven search algorithm to assist the User. Click on Search
to open the search panel. Type “Sales” in the search dialog box. As you type, an auto-fill
feature will launch and render search suggestions for related terms. We will work more with
this feature in an upcoming exercise. Click outside the Search panel to close it.
My Content. The My Content folder provides the User with direct access to the content
they have saved. This is content owned by the User and may only be viewed by the User.
You will be saving your work from today’s workshop in this folder. Click on My Content to
open the navigation panel to see if there is any User content in your environment. Click
outside the My Content panel to close it.
Team Content. The Team Content folder contains all the published enterprise and shared
content the user hats permissions to view. Click on Team Content to open the navigation
panel. Notice there is a list of folders. We will go deeper into these later in the exercises.
Click outside the Team Content panel to close it.

Recent. The Recent button shows the User the most recently used list of content, up to 20
objects (reports, dashboards, data modules, etc.). Objects appear in order based on most
recently
used. Once an object is viewed, it will move to the top of the list. Click on Recent to see
what, if any, are the most recently used objects in your environment. Hover your mouse over
the icon to the left of each object to identify the type of object. Click outside the Recent panel
to close it.

New. The New button is used by Users to create new content. It is intent-driven, meaning
that it allows Users to select what type of content they wish to create, and the Cognos
Analytics UI will open the associated capabilities in the canvas. From here, Users may
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create new Reports, Dashboards, Stories, Data Modules, access Other Companion
Applications (legacy studios from previous versions of Cognos) and upload files.

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6. Note the different parts of the application toolbar at the top.

Switcher Menu. The switcher menu in the center of the application toolbar
provides a dropdown button that allows Users to easily move between the
different objects they have worked with during their current session, without
opening additional browser windows. (None will currently show as we have not
opened any objects so far, but sample below shows example). The Switcher
menu will display the name of the object currently active in the canvas.

More (3 horizontal ellipses). The More button provides the User with options
to customize their User Experience. The options presented dynamically update
based the type of object open in the canvas. Click outside the More menu to
close it.

Notifications. Users may subscribe to Cognos Analytics content and receive
notifications when that content has been updated and is ready for review. An
indicator is provided to provide Users with the number of new notifications.
Clicking on the Notifications button will open a listing of all unread notifications.

Personal Menu. The Personal Menu allows Users to change personal
preferences for their environment and to manage their subscriptions. Click on
the Personal Menu to see the capabilities available. Click outside the Personal
Menu to close it.

Help. The Help button allows users to access more information regarding
Cognos Analytics.

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7. Click on team content. Navigate to Samples>Dashboards. Click on Country comparison.

8. This is a dashboard built for an outdoors equipment retailer to compare their sales
between countries. Cognos dashboards are fully interactive. Click on list elements or on
the graph to adjust the dashboard. Dashboards are embeddable in websites or
applications or can be built in report form. Later in the lab, we will build our own
dashboard and embed it into our web application.

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9. Click on the Home button to return to your home page.

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Lesson 1.3 Upload Data and Build a Data Module
1. Go to the IBM cloud dashboard https://console.bluemix.net/dashboard/apps.
2. Click on your watson-online-store app.

3. You will be brought to the dashboard for your app.

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4. From the menu on the left, click Runtime. Then Click the Environment variables tab.

5. Scroll down to the “User defined” section.
6. Set the value of SLACK_BOT_TOKEN to the API token you copied to your clipboard
earlier.
7. Set the value of SLACK_BOT_USER to the name of your bot.

8. Click Save. Your application will automatically restart.
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9. Once the application is running, you should also check your bot status on Slack. When
the application is running and the bot status is green/online, then you can chat.

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Lesson 1.4 Chat with your bot.
Pre-requisites:
-

Completion of Lessons 1.1 – 1.3.

1. Go to the Slack channel that you created. Your bot user should be a member of the
channel. Start a conversation in the channel by typing “@ What can
I buy here?” in the chat window. The bot returns a partial list of items.

2. Choose an item to add to your cart by typing the item number. For example, to add the
Eye-Bee-M Sweatshirt to your cart, type @ 1.

3. When the bot asks “Which item number do you want to delete?“, you can respond with a
0 to continue. Add a few more items to your cart. The online store lists your cart every
time you add or remove an item.
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Course materials may not be reproduced in whole or in part without the prior
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© Copyright IBM Corp. 2017
Course materials may not be reproduced in whole or in part without the prior
written permission of IBM

Lesson 1.5 Update the Python code to add the checkout
function and redeploy the app.
Pre-requisites:
-

Completion of Lessons 1.1 – 1.4.

1. Go to the IBM cloud dashboard https://console.bluemix.net/dashboard/apps.
2. Click on your watson-online-store app.

3. You will be brought to the dashboard for your app.

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4. Scroll down and click “View Toolchain.”

5. Review the toolchain. In the toolchain, click Eclipse Orion Web IDE to open the editor
and make changes to the Python code. From the left navigation menu of the editor,
expand the watsononlinestore folder and click watson_online_store.py.

Note: Python is particular about indentation. Copy and paste might not work properly
when you move the code to the cards. If you see errors that indicate indentation
problems in the log on the IBM Cloud App Dashboard for your app, type the code by
hand, being sure to comply with Python indentation rules.
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6. Add the following code, including a blank line, after line 810. This code calls the checkout
handler when checkout is requested in the chatbot.

if ('shopping_cart' in self.context.keys() and
self.context['shopping_cart'] == 'checkout'):
return self.handle_checkout()

7. Add the following code at line 821 above “def run(self):”. This code processes the
checkout by removing all items from the cart in the Cloudant database.
def handle_checkout(self):
""" Removes all items from the cart"""
email = self.customer.email
shopping_list = self.cloudant_online_store.list_shopping_cart(email)
for _index, item in enumerate(shopping_list):
self.cloudant_online_store.delete_item_shopping_cart(email, item)
self.clear_shopping_cart() # this actually clears the context
return False

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8. From the file menu click Save.

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9. Open Git by clicking the Git icon below the pencil icon from the left navigation.

10. In the Working Directory Changes section, the changes to the Python file are shown.
Type a commit message, such as “Updated to implement the Checkout function” and
click Commit.

11. Click Sync to push the code. You can use the back browser arrow to go back to the
toolchain.

12. Click on “Delivery Pipeline”

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13. Because of the way the pipeline is configured, when the sync is complete, the pipeline
automatically runs to build and deploy the changes to the app. Watch the pipeline until it
completes the deploy stage. When it is finished, your modified app is up-and-running on
IBM Cloud.

© Copyright IBM Corp. 2017
Course materials may not be reproduced in whole or in part without the prior
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Lesson 1.6 Update the Python code to add the checkout
function and redeploy the app.
Pre-requisites:
-

Completion of Lessons 1.1 – 1.5.

14. Go to the IBM cloud dashboard https://console.bluemix.net/dashboard/apps.
15. Click on your watson-online-store app.

16. You will be brought to the dashboard for your app. On the left-side navigation panel,
click on Connections.

17. Click on your conversation service.

18. Click Launch Tool to open the Watson Assistant page.
19. Click on the Workspaces tab.
20. Click on your app workspace “watson-online-store.”

21. Click on the Dialog tab.
22. Click on the blue arrows on the left side of the nodes to expand them.
23. You will be making changes to the configured dialog to allow for the processing of
Checkout by the bot. The changes will occur in and after the “list after delete” in
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conversation configuration. Open the configuration by clicking the arrows on the nodes to
expand the dialog until you see the "List after delete" node. You will be adding new
nodes and several jumps in the conversation configuration. As you review the figure
below, note that you will be adding everything that occurs after the "List after delete"
node.
Note: Copy and paste might not work when you move the code to the nodes. If you see
errors in the code entry box after you copy and paste the code, type the code by hand.

24. Click on the three dots on the right side of the “List after delete node” and then click Add
child node.
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25. For the name of the new node, type “list items”
26. Type “true” in the If bot recognizes field.
27. In the “Then respond with” section, click the menu icon next to Add response condition
and select Open JSON editor.

28. Replace the existing JSON with the following code:
{
"context": {
"get_input": "no"
},
"output": {
"text": {
"values": [
"Items in your cart are now:\n$shopping_cart"
],
"selection_policy": "sequential"
}
}
}

29. Add a “checkout node after the “list items” node by adding another child node.
30. For the name, type “Checkout”
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31. Type true in the If bot recognizes field.
32. In the “Then respond with” section, click the menu icon next to add response condition
and select Open JSON editor.
33. Add the following code to the response:
{
"output": {
"text": {
"values": [
"Would you like to checkout and clear the cart?"],
"selection_policy": "sequential"
}
},
"context": {
"cart_item": "",
"get_input": "yes"
}
}

After the checkout node, you will be adding two nodes which are used to respond to the positive
response to checkout and the negative response indicating that the customer wants to continue
shopping.
34. Add a “Clear the Cart” child node after “Checkout”
35. For the name, type “Clear the cart”
36. Type @PositiveResponse in the If bot recognizes field.
37. In the “Responses” section, click the menu icon and select JSON.
38. Add the following code to the response:
{
"output": {
"text": {
"values": [
"Ok, let's clear your cart."],
"selection_policy": "sequential"
}
},
"context": {
"get_input": "no",
"shopping_cart": "checkout"
}
}

39. Add a “Keep shopping” child node after “Checkout”
40. For the name, type “Keep shopping”
41. Type @NegativeResponse in the If bot recognizes field.
42. In the “Responses” section, click the menu icon and select JSON.
43. Add the following code to the response:
{
"output": {
"text": {
"values": [
"Ok, let's keep shopping!"],
"selection_policy": "sequential"
}
},
"context": {
"get_input": "no"
}
}

44. When a user wants to keep shopping, the cart is listed and they can continue shopping.
You can do this by moving the “List and jump to help” node to after the negative
response to the right of the "Keep shopping" card. To do this, you click the menu icon in
the "List and jump to help" node and then click Move. A banner at the top of the screen
says Select where you want to move the node to.

45. Click the “Keep shopping” node and then click As child node.
46. When the user has selected to clear the cart, they will want to go back to shopping. To
allow this, you will add a "Go back to shopping" card followed by a jump that will take the
user back to the place in the conversation where they can add more items to the cart.
47. Add a “Go back to shopping” child node after “Clear the cart”
48. For the name, type “Go back to shopping”
49. Type true in the If bot recognizes field.
50. In the list of Responses, type “Shopping cart has been cleared!”

51. Add a “Jump to Shopping Intent” node after the “Go back to shopping” node. This node
takes you back to the start of a new conversation with the bot.
52. Click the menu (three dots on the right side of the node) on the “Go back to shopping
cart” node and then click Jump to. A blue banner at the top of the screen says “Select a
destination node (origin: Go back to shopping)”
53. Scroll to the beginning of the conversation, click the “Shopping Intent” node, and then
click Respond.

54. A card like the following example is added to the conversation.

55. Add a “Jump to Shopping Intent” node after the “list and jump to help node.
56. Click the menu on the “list and jump to help” node and then click Jump to.
57. Scroll to the beginning of the conversation, click the “Shopping Intent” node, and then
click Respond.
58. Make sure the conversation nodes you added and modified look like the following figure:

Lesson 1.7 Update the Python code to add the checkout
function and redeploy the app.
Pre-requisites:
-

Completion of Lessons 1.1 – 1.6.

1. Return to the watson-online-store Slack channel and verify that your bot is still active. If
the bot is not active, repeat lesson 1.3 to verify that your environment variables are still
set to the correct values.
2. Talk with your chatbot. Try the checkout function after you have added an item to your
cart and deleted an item.

You have completed the lab.

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