Formulae in Excel aren’t always easy to decode – even a
relatively simple formula, like the volume of a right rectangular pyramid below,
can be a little cryptic with the A2 type cell identifiers.
You can name ranges and use range names to make a formula easier to understand. Highlight a data set – in this case, I am highlighting the “length” values – column A. On the “Formulas” ribbon bar, click on “Define Name” (you don’t need to hit the inverted caret on the right of the button – just click the ‘define name’ text).
Supply a name for the range – in this case, I am calling it “Base_Length”
(range names need to start with a letter or underscore and cannot contain
spaces). Click OK to save the range name. Repeat this operation with all of the
other data groups – in my case, I named Column B “Base_Width” and Column C “Height”.
Use the name instead of the cell identifier – as you type
your formula, the range names matching your typed text will appear.
It is now a lot clearer
what this formula means – base length
times base width time height all divided by three. Which is the formula to calculate the volume of a right rectangular
pyramid.
The calculated answer is the same either way – but this
makes it easier to figure out what exactly you were computing when you open the
spreadsheet again in six months 😊 (Or share the
spreadsheet with others).
There are times when it is easy to tell who is speaking – there aren’t a lot of women in my group, so “the female voice” is usually me. My friend Richard is generally the only person with a New Zealand accent on any call (although someone who didn’t grow up in a Commonwealth country may have trouble distinguishing him from the guy from Australia). And after you work with someone for a while, you learn the voice and lexical nuances of colleagues. The rest of the time? I end up pausing the conversation to check who it was that volunteered to serve as my tester and clarify who is going to be getting back to me next week. In a Teams meeting, though, you can quickly tell who is speaking – and respond with a much friendlier “thanks, Jim, for offering to help”.
When you join a Teams meeting, you’ll see up to four large tiles
with meeting participants. If there are more than five participants (you don’t show
up on your own view!), the remaining people will be represented by smaller
images in the lower right-hand corner of the screen.
When someone is speaking, their tile will be highlighted in
a purply-blue and a brighter highlight circumscribes their image.
The four large tiles represent the most recent speakers, so
you will notice who is in these four tiles change throughout the call. And, yeah,
it’s possible for more than one person to be talking at a time – you’ll have
multiple highlighted tiles.
There is another place to view who is speaking. On the right-hand
column, click to enter the participant pane.
The current speaker will be bolded.
Bonus Features: Sometimes
I’ll start a large call and have trouble getting everyone’s attention to start the call. In the participant pane,
you can click “Mute all” to mute all
participants. N.B. Any participant can do this – so don’t test it in the
middle of a real discussion!
And just like meetings through the PSTN system or other web-meeting
platforms, you’ll get the occasional person typing without hitting mute. Or speaking
to someone who popped into their office. Or experiencing feedback on the connection.
In Teams, it’s easier to identify who
is causing a disruption – they are going to be highlighted as speaking.
Once you’ve identified the source of the noise, click the
not-quite-a-hamburger-button next to their name and select “Mute participant”.
You can create a
document in a Teams file space (from “New”, select the document type); but, if
you want to use a custom template (or if you just didn’t think of it and started the document on your computer),
you can also save an Office 365 document to Microsoft Teams.
For the Teams file space to appear in the save dialogue, you’ll need to be following the SharePoint repository that underpins the file space. From the Files, select “Open in SharePoint”.
In the upper right-hand corner, click “Not following” to
follow the site.
The change may not be reflected immediately on your computer
– if your Teams space does not show up yet, wait an hour or two. Select “Save
as” from the Files ribbon bar.
Click on “Sites – Windstream Communication”. The Teams space you followed will show up in the SharePoint sites list. Click on the team name.
Then select “Documents”
From there, you will see the name of each channel. Select
the appropriate one, then navigate to the location you want to store your
document. Give the document a name and click “Save”
The document will be saved directly to your Teams space.
Applications can generate data in formats that aren’t quite useful – glomming multiple fields
together to make something unusable. And asking people to type information can
yield inconsistent results – is my name Lisa Rushworth, Lisa J Rushworth, or
just Lisa? Excel has several functions that allow you to produce consistent,
usable data (without copy/pasting or deleting things!)
Flash Fill
Flash
Fill will try to figure it out for you. Add an empty column (or more) and manually
type one or two values. On the “Data” ribbon bar, select “Flash Fill” and Excel
will use the data you’ve entered into the row to figure out what should go in
the rest of the row.
The guesses aren’t 100% accurate – especially if your
information is not consistent – but it’s a lot
easier to delete the handful of things that are obviously not zip codes …
Than to work out a formula that extracts the same
information
Text to columns
Text to columns uses the fixed-length file and delimited
file import wizard on a column of data – essentially treating that column as a
file to be imported. In this example, a DateTime value is provided in a way
that Excel only sees it as a string. And, frankly, I am not interested on the
exact hundredth of a second the event occurred. What I really want to do is group these creation dates by day, so all I
need is the date component.
If you want to retain all the data, you’ll need to insert empty
columns to the right – otherwise the data being split out can overwrite existing data. In my case, I only want to keep one of the new columns.
Highlight the column that holds your data. On the “Data”
ribbon, select “Text to columns”
Select if the column should be split based on a fixed width
definition or a delimiter and click ‘Next’
Indicate the proper delimiter – in this case, I need to use ‘Other’
and enter the letter T. A preview of the split data will appear below – make sure
it looks reasonable. Click “Next”.
For each new row, you can
specify a data type. Or leave the type set to “General” and Excel will try to
figure it out.
If you do not need to retain the data, select “Do not import
this column (skip)”. Click “Finish” to split your column.
Voilà – I’ve got a usable date value.
Notice, though, I have lost my original data. If you want to
retain the original data, create a
copy of the column. In this example, I want to know how many e-mail addresses
use each domain, but I want to have the e-mail addresses in a recognizable and
usable format too.
Text to columns will still replace the values from the selected column. But the copy will
contain the original text.
You can even use Text to columns to sort out odd data that doesn’t actually get split into multiple
columns. In this example, negative values have the minus sign after the number …
which isn’t actually a negative
number and isn’t usable in calculations.
Pick a delimiter that doesn’t appear in your data, and you’ll
only have one column. When selecting the data format, click “Advanced”
Make sure the “Trailing minus for negative numbers” checkbox
is checked and click OK.
And we’ve got negative
numbers
Right, Left, Mid, and Search Functions:
You can also use the Search
function in conjunction with Right,
Left,
and Mid
to extract components of column data. In this example, we have first and last
names. Since there are a few middle initials in there, we cannot just split on
the space character.
These formulae aren’t perfect – Mary Ann will have ‘Mary’ as
a first name – but
Working out where to start the text extraction and the number
of characters to extract can get complex. I’ll usually include the Substitute
function to simplify things a little – the zip code, in this case, is whatever
is left over after we find the city and state.
Producing columns with the city, state, and zip code from
the ‘Location’ column.
How many times have you clicked a second time expecting to “paint” your format only to realize the format painter is a one-click deal-e-o. Well, it’s not — you just have to know the trick to ‘locking’ it on. Double click the format painter button — now you can paint as many things with the format as you like.
If you want to create a simple bot that uses natural language processing training to allow users to ask questions that aren’t exactly what has been attached to the answer (i.e. I could say “I forgot my password”, “I don’t remember my password”, or “what’s my password” and be directed to the password portal URL without anyone having to come up with every possible iteration of the query),you can create one without actually programming a bot. You’ll need to enter some questions and answers – and it’s best to have a few questions associated with each answer so the bot can ‘learn’ what a real user might ask.
Before we start, understand how the billing works for Microsoft’s cloud services. There are generally free tiers for selections, but they are resource limited. When you first start with the Azure magic cloudy stuff, you get a 200$ credit. A message indicating your remaining credit is shown when you log into the Azure portal. Pay attention to that message – if you think you are using free tiers for everything but see your credit decreasing … you’ll need to investigate. Some features, like usage analytics,cost extra too.
Instead of programming a bot, you can use a pre-built bot and a question/answer knowledgebase maintained at https://www.qnamaker.ai/ Sign in to your company account
Select “Create a knowledge base” to start.
Click the button to “Create a QnA service”
A tab will open to the Azure portal, and you’ll see a wizard to create a QnA Maker resource. Provide a name and select your subscription – you may be walked through creating a new trial subscription. For the management pricing tier and search pricing tier, select the free plans unless you expect high usage or need to store a lot of documents. The selections below are the free tiers.
Disable app insights unless you want to study usage of the q&a – app insights is a paid add-on. Click create to create.
Return to the Azure Portal dashboard and click “Refresh” in the “All resources” section. Eventually, you will see your knowledge base appear.
Return to the QnA Maker tab. In “Step 2”, click the drop-down arrows to select the Azure Directory (you should just see our company), the subscription (again, probably just the one), and the knowledge base we just created.
In “Step 3”, provide a name for your knowledge base. If you have an existing Q&A file, or a URL with Q&A pairs, you can import them here. I will enter question/answer pairs manually later.
Optionally, add ‘chit chat’ – this allows your bot to respond to common things users type like “do you know Siri” or “how are you”. It isn’t needed, but it saves adding answers to “are you there” manually. This imports question sets to your KB, so you can remove any you don’t feel are appropriate for your implementation.
Click “Create your KB”.
And wait a few minutes.
Once the KB has been created, click “Add QnA pair” to begin adding questions. You can also scroll through the imported “chit chat”questions and modify/remove any you don’t like.
Answers use markdown formatting, so you can add hyperlinks, italics, bold, numbered lists.
Once you have added your question/answer pairs, click “Save and train” – training allows the bot to respond with an appropriate answer when the question isn’t exactly one of the questions provided.
Wait again … when you are returned to the q&a pair screen, click “Publish” – this implements your changes in production. You can stage changes, allowing others to review them, by waiting to click Publish.
Read the warning – assuming you actually want your changes to be in production, click “Publish”.
Wait some more, and you have an endpoint!
Copy the ‘stuff’ from the box into a text file somewhere. Find your QnAEndpointHostName, QnAKnowledgebaseId, and QnAAuthKey
Unless you are going to be the *ONLY* person editing your KB (and never go on holiday, never ring up sick), you’ll want to share access with others. Log into https://portal.azure.com and locate your “cognitive service”. Click on its name to edit it.
Click on “Access control (IAM)”
In the “Add a role assignment” section, click “Add”.
Select either “Cognitive Services Contributor” or “Owner” as the role (owners are allowed to manage all settings, including permissions whereas service contributors can only manage data within the knowledge base). Enter an Active Directory group name – you can enter individual people, but then someone will need to manually edit the permissions as people join and leave your group.
If you didn’t select owner, make sure you add some other owners (either a group or a few people)
Now we’re ready to set up a bot …
Microsoft Teams uses Azure bots – so you’ll need to create an Azure bot. From https://portal.azure.com, click on ‘Create a resource’.
Search for “bot” and find the bots you are looking for. Either “Functions Bot’ and “Web App Bot” can be selected – I am using a WebApp bot because that’s what I’ve used for other bots I’ve coded. Functions bots use Azure functions, which are C# scripts, for logic processing; WebApp bots use WebAPIApp Service for logic processing (C# or NodeJS). If you’re not planning on tweaking anything … doesn’t much matter. Click “Create” to create the bot.
Give your bot a name – this needs to be unique. In the pricing tier, click on “View full pricing details” to see the options. Again, I am selecting the free tier. Don’t forget to hit ‘select’, or your selection will not be updated.
When you get to the bot template section, you can pick either C# or NodeJS – again, if you don’t plan on tweaking anything … doesn’t much matter. I am using C# because I know C#. Select the SDK v3, then find the “Question and Answer” bot template. Again, don’t forget to click “Select” or your selection won’t be saved.
Create a new storage location, disable application insights (it’s a for-fee add-on), and click “Create”.
Wait for it …. You’ll see a blue bar running under the bell icon in the upper right-hand corner of the site.
Soon, you’ll see a success message in the upper right-hand corner.
Refresh the resources on the dashboard and select the “WebApp Bot”. Under ‘App Service Settings’, go into “Application Settings”. Here’s where you enter the QnA information we saved after your knowledge base was published. Click in the “Value” column to paste in the values for QnAAuthKey, QnAEndpointHostname, and QnAKnowledgebaseId. Don’t have them? No big – go back to QnA Maker, open your KB, and select the “Settings” tab. There it is again!
Click “Save” to commit your changes.
Return to the Dashboard and select your “Web App Bot”
In the left-hand navigation column, select “Channels”. Click on the Teams logo.
The “Calling” tab will enable IVR or real-time media interaction with your bot – I have never done this, it may not be possible with our product set. “Publish” is to publish your Bot in the Microsoft store – not something I want to do with a bot designed to answer employee-specific questions, but I could see creating a Enterprise Customer Q&A bot that enterprise customers can add to their Teams spaces … in which case, making the bot available in the Microsoft Store would be convenient. Click “Save” to create a Teams channel for communication with your bot.
Read the publication terms and privacy statement. If you agree, check the box and click “Agree”.
In the Channel section, click the “Microsoft Teams” hyperlink.
This will open a new browser tab. Click “Cancel” so you can copy the URL.
Once you’ve copied the URL, click “Open in Teams web app” to interact with your bot using the Teams web client (or ‘launch it now’ for Teams desktop client)
It’s alive! Ask some questions and verify that your answers are being delivered. Check for formatting problems or bad hyperlinks.
Anyone you have set as “Cognitive Service Maintainer” or“Owner” should be able to use QnA Maker to maintain the question and answer set. Log in to https://www.qnamaker.ai, select the “My knowledge bases” tab, and click on the knowledge base name. Modify/add question/answer pairs, then click “Save and train”, then “Publish”.
I am a member of multiple Teams, and I can remember that Keith posted something about creating a Q&A a few days ago … but I don’t remember where he posted that message. I cannot reply to it until I find it. Search can help — chat conversations are searchable. But did he type QnA, Q&A, Q and A …
Instead of clicking through all of the channels in all of my Teams spaces trying to find a single post or working my way through the various ways of phrasing “questions and answers”, I can look at my chat with Keith. Click the “Activity” tab. Now I am looking at things Keith has posted to our shared Teams spaces in the past two weeks.
The Team and channel into which the activity was posted is included before each message. An icon indicates if the activity is a reply to an existing thread or a message starting a new thread.
You can click on any entry in the activity log.
Your Teams client will show you the message in its context – you are in the correct Team and Channel, and the message is briefly highlighted. This makes replying to the message we found in the activity feed quite quick.
What if you’ve never chatted with the person? Start a new chat and type in their name. You don’t have to send a message to them (although I could totally see myself writing “ignore this message – I just needed to get you listed in my recent conversations”), just click away and there will be a draft chat with them. Click on that draft chat, and you’ll have an “Activity” tab.
Before you start, understand how billing works for Microsoft’s cloud services. There are generally free tiers for selections, but they are resource limited. When you first start with the Azure magic cloudy stuff, you get a 200$ credit. A message indicating your remaining credit is shown when you log into the Azure portal. Pay attention to that message – if you think you are using free tiers for everything but see your credit decreasing …you’ll need to investigate. Some features, like usage analytics, cost extra too.
Microsoft Teams uses Azure bots – so you’ll need to create an Azure bot to get started. From https://portal.azure.com, click on ‘Create a resource’. Search for “bot” and find the bots you are looking for. To host your bot on Azure, select either the “Functions Bot’ or “Web App Bot”. Functions bots use Azure functions, which are C# scripts, for logic processing; WebApp bots use WebAPI App Service for logic processing (C# or NodeJS). To host your bot elsewhere, select “Bot Channels Registration”. In this example, we are using a “Web App Bot”.
Give your bot a name– there will be a green check if the name is unique. Pick your language – C# or Node.JS – and then decide if you want an Echo bot (which gives you a starting place if you’re new to developing bots) or a blank slate (basic bot). Don’t forget to click “Select” otherwise you’ll be back to the defaults. You’ll need to create a resource group. Click on “Bot template” and select what you want to use as the basis for your bot. As of 14 Dec 2018, use v3 unless you need something new in v4 – there’s a lot more available there, and the Bot Builder extensions only work with v3 (https://github.com/OfficeDev/BotBuilder-MicrosoftTeams)
You may need to create a service plan
And storage configuration. Once you have completed the bot configuration, click “Create” and Azure will deploy resources for your bot.
You’ll see a deployment process message, and your messages will have a similar notification. Wait a minute or three.
Return to the dashboard & you’ll see your bot services. Go into the bot that you just created.
Select “Build” – you can use the online code editor or use an existing source repository and configure a continuous integration. I will be setting up a continuous integration – don’t click the link under “Publish”, it goes to an old resource. Click to download the source code – it takes a minute to generate a zip file for download.
Once the download link is available, download and extract the file – this will be the base of your project. Put it somewhere – in this example, I’ll be using a GitHub project. Extract the zip file and get the content into your source repository.
Return to your dashboard and open the App Service for your bot. Select the “Deployment Center”.
Select the appropriate source repository. When GitHub is used, you will need to sign in and grant access for Azure to use your GitHub account. Click “Continue” once the repository has been set up.
Select the build provider – Kudu or Azure Pipelines. Which one – that’s a personal preference. Azure Pipelines can deploy code stored in git (at least GitHub, never tried other Git services). Kudu can build code housed in Azure DevOps. Kudu has a debugging console that I find useful, and I’ve successfully linked Kudu up with GitLab to manage the build process elsewhere. Azure Pipelines is integrated with the rest of the Azure DevOps (hosted TFS) stuff, which is an obvious advantage to anyone already using Azure DevOps. It uses WebDeploy to deploy artifacts to your Azure websites (again, an advantage to anyone already doing this elsewhere).
The two build environments can be different – MS doesn’t concurrently update SDK’s in each environment, so there can be version differences. It’s possible to have a build fail in one that works in the other. Settings defined in one platform don’t have any meaning if you switch to the other platform (i.e. you’ll be moving app settings into a Build Definition file if you want to switch from Kudu to Azure Pipelines) so it’s not always super quick to swing over to the other build provider, but it might be an option.
I prefer Kudu, so I’ll be using it here.
Select your repository name from the drop-down, then select the project and branch you want to use for deployment. In my repository, the master branch has functional code and there is a working branch for making and testing changes.
Review the summary and click “Finish”.
In GitHub, you confirm a webhook has been added to your project on push events. From your project’s settings tab, select “Webhooks” and look for a azurewebsites URL that includes your bot name. You can view the results of these webhook calls by clicking “Edit” and scrolling down to “Recent deliveries”.
Add the interactions you want – information needs to be accessible from the Azure network, otherwise your bot won’t be able to get there. You can test your bot from the Azure portal to identify anything that works fine from your local computer but fails from the cloud. From the Web App Bot (*note* we are no longer in the App Service on the Azure portal — you need to select the bot resource), select “Test in Web Chat” and interact with your bot.
Once you have your bot working, you need to add the Teams channel to allow the bot to be used from Teams. Select “Channels” and click on the Teams logo.
There’s not much to set up for a bot – messaging is enabled by default. I don’t want IVR or real-time media functionality … but if you do click on the “Calling” tab. The “Publish” tab is to publish your bot in the Windows store – this might be a consideration, for instance, if you wanted to create a customer service interaction bot that enterprise customers could add to their Teams spaces (i.e. something you want random people to find and use). Since I am answering employee specific questions, I do not want to publish this bot to the Internet. Click “Save” when you have configured the channel as needed (in my case, just click ‘save’ without doing anything).
Review the publication terms and privacy statement. If these are agreeable, click “Agree”.
You’ll be returned to the Channels overview. Click on the hyperlinked “Microsoft Teams” – this will open a new URL that is your bot.
You can copy the URL here – others can use the same URL to use your bot. Either open the link in the Teams app
Or cancel and click “Use the web app instead” at the bottom of the screen.
Wait for it … your bot is alive!
That’s great … how do I interact with company resources? Quick answer is “you don’t” – this bot uses resources available on the Internet. To interact with private sources, the magic cloudy Microsoft network must be able to get there. Personally, I’d host my own bot engine. Expose the bot to the Internet and create a “Bot Channels Registration” instead.
This post contains more niche “for developers” information than most of my Teams info series 😊
You’ve seen third-party services with connectors in Teams – both services with connectors published to Teams and services that can use the “Incoming Webhook” connector to post data. Youcan use the “Incoming Webhook” connector within your code too. If you want to allow others to post information into their Teams spaces, you’ll need a configuration option that allows end-users to supply the webhook URL. If you want to post information into your Teams space, then you can include it directly in your code. If you are doing the former, provide something like the “Creating a Teams Webhook URL” instructions below to your end users. In this example, I am doing the later. The example script is Python code that gathers statistics and posts a summary to my Teams space.
Creating a Teams Webhook URL:
Create a URL for your incoming webhook – from the not-quite-a hamburger menu next to the channel into which you want to publish your data, select “Connectors”, find “Incoming Webhook”, and click “Add” (if you have already configured a webhook in your Teams space, you will see “Configure”instead, and will not have to ‘install’ the webhook)
Read the privacy policy and terms of use, and if they are acceptable click “Install”
Provide a name for your webhook – this name will be displayed on all posts made via this webhook. Scroll down.
You can customize the logo associated with your webhook posts – nice if your application has a well-known logo. Click create to generate the webhook URL.
Copy the URL somewhere, then click ‘Done’.
Using Teams Webhooks Within Code:
OK, now you’ve got something like this in a text document (no, I didn’t post a real webhook to the Internet – the long pseudo-random alphanumeric string is hex, and there aren’t a whole lot of m’s and q’s in hex!):
What do you do with it? You make a POST call to that URL and supply JSON-formatted card content in the data. Microsoft provides a complete card reference, but you’ll need to use the O365Connector Card with the incoming webhook connector.
The card requires “summary” or “text” be included – you’ll get a bad data HTTP response if you fail to set one of these values. Card text can be formatted in markdown or HTML – if you want to use HTML, you need to set markdown to false.
You’ll need a function that POSTs data to a URL:
################################################################################
# This function POSTs to a URL
# Requirements: requests
# Input: strURL -- URL to which data is posted
# strBody -- content to be sent as data
# strContentType -- Content-Type definition
# Output: BOOL -- TRUE on 200 HTTP code, FALSE on other HTTP response
################################################################################
def postDataToURL(strURL, strBody, strContentType):
if strURL is None:
print("POST failed -- no URL provided")
return False
print("Sending POST request to strURL=%s" % strURL)
print("Body: %s" % strBody)
try:
dictHeaders = {'Content-Type': strContentType}
res = requests.post(strURL, headers=dictHeaders,data=strBody)
print(res.text)
if 200 <= res.status_code < 300:
print("Receiver responded with HTTP status=%d" % res.status_code)
return True
else:
print("POST failed -- receiver responded with HTTP status=%d" % res.status_code)
return False
except ValueError as e:
print("POST failed -- Invalid URL: %s" % e)
return False
And you’ll need something to create a card and call the HTTP POST function. Here, I define a function that takes statistics on Windstream’s Microsoft Teams usage, formats a card with the values, and POSTs it to my webhook URL.
################################################################################
# This function posts usage stats to Teams via webhook
# Requirements: json
# Input: strURL -- webhook url
# iPrivateMessages, iTeamMessages, iCalls, iMeetings -- integer usage stats
# strReportDate - datetime date for stats
# Output: BOOL -- TRUE on 200 HTTP code, FALSE on other HTTP response
################################################################################
def postStatsToTeams(strURL,iPrivateMessages,iTeamMessages,iCalls,iMeetings,strReportDate):
try:
strCardContent = '{"title": "Teams Usage Statistics","sections": [{"activityTitle": "Usage report for ' + yesterday.strftime('%Y-%m-%d') + '"}, {"title": "Details","facts": [{"name": "Private messages","value": "' + str(iPrivateMessages) + '"}, {"name": "Team messages","value": "' + str(iTeamMessages) + '"}, {"name": "Calls ","value": "' + str(iCalls) + '"}, {"name": "Meetings","value": "' + str(iMeetings) + '"}]}],"summary": "Teams Usage Statistics","potentialAction": [{"name": "View web report","target": ["https://csgdirsvcs.windstream.com:1977/o365Stats/msTeams.php"],"@context": "http://schema.org","@type": "ViewAction"}]}'
jsonPostData = json.loads(strCardContent)
if postDataToURL(strURL, json.dumps(jsonPostData),'application/json'):
print("POST successful")
return True
else:
print("POST failed")
return False
except Exception as e:
print("ERROR Unexpected error: %s" % e)
return False
Run the program, and you’ll see information in Teams:
A personal recommendation based on my experience with third-party code that uses generic incoming webhooks — have a mechanism to see more than a generic error when the POST fails. It takes a lot of effort to pull apart what is actually being sent, turn it into a curl command to reproduce the event, and read the actual error.Providing a debug facility that includes both the POST body and actual response from the HTTP call saves you a lot of time should your posts fail.
