Wednesday, October 18, 2017

Quick tip: Format JSON documents in Notepad++

Notepad++ does not have built-in support for formatting JSON documents, but you can use JSONViewer for this. It can be installed directly using the "Plugin Manager" in Notepad++. Just got to "Plugins > Plugin Manager > Show Plugin Manager > Available tab"

Wednesday, October 11, 2017

Use Chrome user profiles to simulate different Dynamics 365 identities


Great tip that I saw on Twitter from @jukkan and @georgedude – you don’t need to use private browsing in Google Chrome to login to Dynamics 365 with a separate identity, you can use Chrome user profiles instead.

Click the person icon
 in the top right corner to configure your chrome profiles.



Check out Share Chrome with others or add a profile for more details.

Tuesday, October 10, 2017

Easy way to get the Dynamics CRM Realm ID for server-based SharePoint integration

Server-based SharePoint integration in Dynamics CRM actually uses the same techniques as high-trust SharePoint app (For more background read Security in SharePoint Apps – Part 1) that you can develop yourself. SharePoint apps (or add-ins) use Appprincipals (a separate identity for an app) to act on your behalf when interacting with SharePoint. SharePoint knows that it can trust the request from the AppPrincipal when it is correctly registered. So one of the steps in Configure server-based authentication with Microsoft Dynamics 365 (on-premises) and SharePoint on-premises  requires you to register the AppPrincipal. To be able to use Register-SPAppPrincipal, you will need the CRMRealmId.

But there is an easier way to get to the crmrealmid than described in the walkthrough (if you forgot to note it down as suggested by the article) – you can simply go to the Settings>Customizations>Developer Resources and use the instance reference ID.


Wednesday, September 27, 2017

Rise of the machines : machine learning and artificial intelligence in Dynamics 365 Part 1

A couple of months ago, I wrote a blog post Microsoft Azure Machine Learning – the power to predict which provided  a high level view  of Microsoft’s service offering around machine learning and artificial intelligence in the cloud. In the next series of posts I will delve a little deeper into a number of scenarios where we can leverage Microsoft AI offering (machine learning and Cognitive services)  together with Dynamics 365/CRM.

If you look at most legacy CRM solutions, they are nothing more than digital contact lists and notebooks where you can look up contact information, check personal details or see when someone on your team has last contacted a customer. They contain a huge amount of data, but without built-in machine learning or predictive analytics, defining priorities on which prospects to contact first for a potential deal is like searching for a needle in a haystack. The added value of a modern CRM system is, that it should guide and support your sales team so that they can focus on what they are meant to do – sell. By automating tedious tasks such as sending follow up emails and reminders, you will free up more time to focus on selling. If you are not sure of the current state of your CRM solution, just take a look at what your mobile phone experience.



Microsoft is betting big on AI (See One year later, Microsoft AI and Research grows to 8K people in massive bet on artificial intelligence) and Dynamics 365 is a platform which can benefit greatly from these investments. Although, the first built-in functionality is still quite rudimentary and some of it is still in preview – the potential seems enormous (also see How machine learning will change Dynamics 365 from Ben Hosking )



Figure 2 Dynamics 365 Customer Insights, relationship analytics and relationship assistant.  

The table below lists functionality/features within the Dynamics 365/CRM platform which uses machine learning and artificial intelligence.

Functionality Availability Remarks
Sentiment analysis within Microsoft Social Engagement Understand the public perception using sentiment analysis GA Native sentiment detection is be available in the 17 Core languages (English, Danish, Dutch, Finnish, French, German, Greek, Italian, Norwegian, Polish, Portuguese (Portugal), Russian, Spanish, Swedish, Turkish, Japanese, Chinese traditional) and Arabic
Social selling assistantThe Social Selling Assistant recommends personal actions for you to  leverage social networks (e.g. which posts to share etc …)GA
Use Azure text analytics with Dynamics 365 (Preview) Suggest similar cases US region only – Preview The rules you create can use either Cognitive Services Text Analytics or some features let you use
the built-in similarities matching engine in Microsoft Dynamics 365. Notice that you can only create one similar records suggestions rule for each entity type.
Use Azure text analytics with Dynamics 365 (Preview) Automatically suggest knowledge base articles US region only – Preview Uses Azure Cognitive Services Text analytics services
Use Azure text analytics with Dynamics 365 (Preview) Topic analysis – identifies topics/categories for
cases to allow to better manage and resolve
cases
Currently not available
anymore
Azure Cognitive Services Topic Detection API was removed,
so this functionality is not available anymore. Expected to be updated to use the new Topic API.
Use Azure text analytics with Dynamics 365 (Preview)Using Document suggestions , Dynamics 365 can presents a list of suggested documents to the user while
the user works on an opportunity/quote etc …
GAThe Document Suggestions feature doesn't require a connection to the Azure Text Analytics service. If you choose not to use Azure Text Analytics, Document Suggestions will use the built-in keyword matching logic available in Microsoft Dynamics 365
Product recommendations (Preview) Dynamics 365 uses the Cognitive Services recommendation service to build an advanced recommendation model for automatic cross-sell product recommendations that are based on historical transaction data. US Region only – Preview
will end February 2018
and feature will be removed
Lead scoring and contact and account data augmentation

through Versium Predict
Versium predict can use CRM data to generate predictive models to score leads, to augment data on contacts or accounts, and to acquire lists of new prospective consumers or businesses from Versium's database. Microsoft has an OEM arrangement with Versium Predict which allows Dynamics 365 customers to install and use Versium Predict.
Relationship assistantProvide guidance and assistance on activities that you should perform based on interactions with customersUS Region only – previewRelationship assistant is part of the bigger relationship insights functionality which includes e-mail engagement and auto capture.
Dynamics 365 Customer InsightsAzure-based SAAS service which enables organizations to bring together transactional, web and social customer data to visualize it in a Customer 360°. DCI also allows you apply advanced data transformation algorithms (KPI calculation and machine learning) on this data to generate role-specific insights.
(*) There currently are a number of changes ongoing where some of the functionality which was powered by Azure Text Analytics and Product Recommendation APIs, will need to use the newer Azure Cognitive Services APIs.


In the next blog posts I will delve a little deeper into some of the available built-in functionality as well as look at how you can extend Dynamics 365 to integrate with Azure Cognitive Services, Azure Machine Learning, etc ...

Interesting links:

Tuesday, September 19, 2017

Improve Dynamics 365 and submit your ideas

Microsoft recently setup a new channel to submit your ideas to improve Dynamics 365 – go check it out on https://ideas.dynamics.com/ . Some development teams at Microsoft, definitely take the feedback formulated through this new channel to heart.  During one of the Dynamics 365 Spring 2017  Preview executive briefing sessions one of the presenters told us  “If you look at the new “Social pane” section you will notice that out of the top 10 ideas, 6 are currently addressed in the new Activity timelines in Dynamics 365”.  But also one of the things that we bumped into when doing a project with Dynamics CRM Online Portals – the fact that Plugin exception information needs to be surfaced in Dynamics CRM Online Portals was recently picked up the Portal team (thanks

So go ahead and submit your own ideas for improvement and don’t forget to vote for these ideas:

Thursday, September 14, 2017

Dynamics 365 monthly reading September 2017

Technical topics (Configuration, customization and extensibility)
Topics for Dynamics 365 business analysts, power users and end users

Topics about Dynamics 365 Spring release (aka 9.0 release)
The Dynamics 365 Spring release (version number 9.x) is the next upcoming release of Dynamics 365. For the moment we only got news about the updates for the next version of Dynamics CRM/365 online so no news yet for on-premise deployments.
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Friday, August 25, 2017

Dynamics 365, Azure webjobs, Azure Service Bus queues and deadletters

When you need to integrate Dynamics 365 (online) with other applications/services in on premise or in the cloud there are a number of challenges. One of the most commonly used integration patterns is messaging since it allows for loose coupling and it provides a reliable way of integration since both applications don’t necessarily have the same responsiveness or uptime. One of the key extensibility points from an integration perspective that you can leverage is the fact that you can connect Microsoft Dynamics 365 (both on premise and online) with the Azure Service  (See Azure integration with Dynamics 365). In an asynchronous messaging pattern, you will however still need a message processing component.  Since you are already leveraging cloud components, it might make sense to also use Azure for this message processing component.


There a number of Azure components you might take a look at:
  • Azure cloud services: use an Azure worker role for message processing (for some background on this read Should I use cloud services or something else?)
  • Azure app services: use  Azure web jobs for message processing.
  • Azure virtual machine hosting the processing components
  • Azure functions  - similar to Azure web jobs since it was built on the same code base as webjobs and has a similar API.
  • Azure logic apps
If you look at the two first options (worker roles and web jobs), you will notice that they offer similar functionality payload – ability to run code repeatedly. However, there are some differences between the two - primarily in terms of environment customization. Web Jobs are good for running small tasks (not very computation heavy) and useful in scenarios where you do not have the need to depend on host OS features. Worker Roles can be used to run computation heavy workloads and their host OS can be modified a bit (by installing dependency components in OS through startup tasks). Worker roles are costly (similar to running a dedicated VM) while web jobs do not carry any additional cost. In case you need extreme customization on OS environment, then you would simply run a windows service inside custom OS image in Azure VM.  So basically you are looking at a trade off between control (and full flexibility) and agility combined with ease of management.



Now, if you look specifically at Azure webjobs, you will see that they can be triggered by a schedule, messages in Azure storage queue or blobs added to Azure storage and http call by calling the Kudu Webjobs API. But given the fact that Dynamics 365/RM already provides integration  with Azure Service Bus, this is the one that you will typically use – for a good walkthrough take a look at  How to use Azure Service Bus with the WebJobs SDK .

One of the things to keep in mind though, is that when an Azure webjob encounters an error in processing a message, it will retry processing it a specified number of times.  The number of retries is configured through the JobHostConfiguration.Queues.MaxDequeueCount property – see Azure webjobs and JobHostConfiguration for more details. This mechanism has been been built to avoid that a queue-based application gets stuck in a loop receiving and aborting the same message it can not process – this is also referred to as poison message handling.  So if this count is exceeded, the message will be move to the deadletter queue (when it is configured).

But the Azure service bus queues also have a property called MaxDeliveryCount (See QueueDescription class) which is by default set to 10 – so if this setting is lower than the setting in the JobHostConfiguration, your message might be moved to the deadletter queue (DLQ) earlier – see Overview of service bus dead-letter queues for more details.
If you open the deadletter queue with Azure Service Bus Explorer you will notice that these messages have additional properties called DeadLetterReason and DeadLetterDescription – these might be helpful in determining what causes the messages to end up in the DLQ. You can also move a message to the dead letter queue yourself by calling the BrokeredMessage.DeadLetter method.

Lessons learned:  If you are building an integration using Azure Service Bus queue, don't forget to think about how to handle messages which are deadlettered.


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