Integrating Microsoft Dynamics 365 (D365) with external systems using Azure Logic Apps is a powerful and flexible approach—but it’s also prone to missteps if not planned and implemented correctly. In our experience working with D365 integrations across multiple projects, we’ve seen recurring mistakes that affect performance, maintainability, and security. In this blog, we’ll outline the most common mistakes and provide actionable recommendations to help you avoid them. Core Content  1. Not Using the Dynamics 365 Connector Properly The Mistake: Why It’s Bad: Best Practice:  2. Hardcoding Environment URLs and Credentials The Mistake: Why It’s Bad: Best Practice:  3. Ignoring D365 API Throttling and Limits The Mistake: Why It’s Bad: Best Practice:  4. Not Handling Errors Gracefully The Mistake: Why It’s Bad: Best Practice:  5. Forgetting to Secure the HTTP Trigger The Mistake: Why It’s Bad: Best Practice:  6. Overcomplicating the Workflow The Mistake: Why It’s Bad: Best Practice:  7. Not Testing in Isolated or Sandbox Environments The Mistake: Why It’s Bad: Best Practice: To conclude, Integrating Dynamics 365 with Azure Logic Apps is a powerful solution, but it requires careful planning to avoid common pitfalls. From securing endpoints and using config files to handling throttling and organizing modular workflows, the right practices save you hours of debugging and rework. Are you planning a new D365 + Azure Logic App integration? Review your architecture against these 7 pitfalls. Even one small improvement today could save hours of firefighting tomorrow. I hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

Have you ever needed to pull data out of Dynamics 365 but didn’t know where to begin? Whether you’re building a report, wiring up a Power App, or feeding data into another system, OData is your friend. In just a few clicks, you’ll be able to write simple HTTP requests to retrieve exactly the records you want—no complex code required.  What Is OData and Why It Matters OData (Open Data Protocol) is a standardized way to query RESTful APIs. Microsoft Dynamics 365 exposes its entire data model via OData, so you can:  This means faster development and fewer custom endpoints.  1. Finding Your Web API Endpoint  https://yourorg.crm.dynamics.com/api/data/v9.2 That’s your base URL for every OData call. 2. Exploring Entities via Metadata  Append $metadata to your base URL:  GET https://yourorg.crm.dynamics.com/api/data/v9.2/$metadata  You’ll get an XML file listing all entities (contacts, accounts, leads, etc.), their fields, data types, and navigation properties. Tip: press Ctrl + F to search for your entity by name.  3. Core OData Query Options  a. $select – Return Only What You Need  GET https://yourorg.crm.dynamics.com/api/data/v9.2/contacts?$select=fullname,emailaddress1,jobtitle This limits the payload to just those three fields, making responses smaller and faster.  b. $filter – Narrow Down Your Results  GET https://yourorg.crm.dynamics.com/api/data/v9.2//contacts?$filter=firstname eq ‘Ankit’ Operators: eq (equals) ne (not equals) gt / lt (greater than / less than) Combine with and / or :  GET https://yourorg.crm.dynamics.com/api/data/v9.2//contacts?$filter=statecode eq 0 and jobtitle eq ‘Consultant’ c. $orderby – Sort Your Data GET https://yourorg.crm.dynamics.com/api/data/v9.2/contacts?$orderby=createdon desc  Newest records appear first.  d. $top – Limit Record Count GET https://yourorg.crm.dynamics.com/api/data/v9.2/contacts?$top=5  Great for previews or testing.  e. $expand – Fetch Related Records  Example: Get each contact’s full name and its parent account name in one request:  GET https://yourorg.crm.dynamics.com/api/data/v9.2/contacts?   $select=fullname,parentcustomerid   &$expand=parentcustomerid_account($select=name) parentcustomerid is the lookup field  parentcustomerid_account is the navigation property  Nested $select limits expanded fields  Another example: Expand opportunities with customer account info:  GET https://yourorg.crm.dynamics.com/api/data/v9.2/opportunities?$expand=customerid_account($select=name,accountnumber) Finding Expandable Names In your $metadata, look for lines like:  <NavigationProperty Name=”parentcustomerid_account” Type=”Microsoft.Dynamics.CRM.account” />  Use that Name value in your $expand.  Putting It All Together Suppose you want all active contacts at “Contoso” and their account names:  GET https://yourorg.crm.dynamics.com/api/data/v9.2/contacts?$filter=statecode eq 0 &$expand=parentcustomerid_account($filter=name eq ‘Contoso’; $select=name)&$select=fullname,emailaddress1  Conclusion:  OData might sound technical at first, but once you get the hang of it, it becomes one of the most powerful tools in your Dynamics 365 toolbox. Whether you’re building integrations, reports, or simple automations, OData gives you the flexibility to query exactly what you need—without relying on custom development.  Start small. Open your environment, locate the Web API URL, and try your first $select or $filter query. Once you’re confident, move on to advanced options like $expand and $orderby.  Call to Action:  Need help designing smarter OData-based solutions or integrating with Power Platform tools? Reach out to our team today and we’ll help you build something great. 

In today’s globalised world, firms frequently operate in numerous areas and languages. To efficiently manage worldwide operations, software with multilingual capabilities is required. Microsoft Dynamics 365 Business Central (BC) includes a powerful translation system that enables enterprises to customise language choices, thereby increasing user experience and operational efficiencies. This article looks at how translations function in Business Central and how they may be used to support global business operations. Why Are Translations Important in Business Central? Businesses that expand into new areas face a variety of languages, currencies, and regulatory regimes. Ensuring that employees can interact with Business Central in their native language improves the software’s usability and productivity. Business Central allows users to configure numerous languages across various modules, allowing workers to work smoothly in their favourite language. It also allows translations for custom fields, reports, and data entry, assuring consistency and correctness in both internal and external interactions. How Translation Works in Business Central Business Central supports several languages, including English, French, German, and Spanish. Here’s an outline on how to activate and use translations successfully. 1. Configuring Language Settings The first step in enabling multilingual support is to configure the Language Settings in Business Central. Users can choose their favourite language or use the organization’s default language settings. This guarantees that when a user logs in, the interface, menus, and forms appear in their preferred language. To configure a language in Business Central: 2. Standard Text Translations Business Central provides built-in translations for standard interface elements and commonly used terms such as “Sales Orders,” “Invoices,” and “Purchase Orders.” These translations are included in the base application by Microsoft. For example, changing the language from English to French automatically updates the captions. However, some standard texts may not be translated by default. To install additional language support: Once installed, the system updates with the new language settings, ensuring a localized user experience. 3. Translating Custom Fields Many businesses customize Business Central by adding custom fields, tables, and industry-specific terminology. While these enhancements improve operational efficiency, they may not be automatically translated in the base system. To resolve this, Business Central provides the CaptionML property, which allows developers to define multilingual captions for custom elements. Example: English: Displays field names and labels in English. French: The same fields are shown with French translations. By implementing the CaptionML property, businesses ensure a seamless multilingual experience even for customized elements. To conclude, Microsoft Dynamics 365 Business Central makes it simple for multinational companies to handle multilingual customers. Companies can improve usability and efficiency across regions by changing language settings, adding extra translations, and ensuring that custom fields are translated using CaptionML. Embracing Business Central’s translation skills enables firms to operate efficiently in a global market while providing a consistent and localized experience to all users. We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfonts.com.

Introduction: This guide will walk you through creating and accessing Azure Blob Storage and integrating it with Azure Data Factory to automate data pipelines. From setting up a storage account and managing containers to configuring pipelines and transferring data to an Azure SQL Database, this step-by-step tutorial ensures you gain a comprehensive understanding of the process. Steps: 3. Click on + Create to initiate the creation of a new storage account. 4. Fill in the required fields like subscription, resource group, and region. Review all the settings before proceeding. 5. Create a Storage Account 6. Once the storage account is created, go to the resource by clicking on Go to Resource. 7. In the storage account, navigate to the Containers section and click + Container to create a new container for storing your files. 8. Click on the container you just created to access its contents. 9. Upload the desired JSON file into the container by clicking on Upload and selecting the file from your local system. 10. Ensure that the uploaded file is now listed in the container. 11. Go back to the Azure Portal and search for Azure Data Factory to open the ADF service. 12. From the ADF home screen, go to Author > Datasets. Click + New Dataset to create a new dataset for your Blob Storage. 13. Select the Azure Blob Storage dataset type, as you are working with data stored in Blob Storage. 14. Choose the data format that matches the file you uploaded, such as JSON, and click Continue. 15. Enter the necessary details for your dataset, including the file path and format settings. Select the appropriate Authentication type and specify the Storage account where the Blob Storage resides. Click Create to finalize the dataset creation. 16. Verify the settings and click OK to confirm the dataset configuration. 17. Navigate to the Pipelines section and click + New Pipeline to create a pipeline that will define your data flow. 18. Pipeline gets created successfully as shown below. 19. In the pipeline, select the dataset type as Azure SQL Database and click Continue to set up the SQL Database dataset. 20. Provide the necessary Linked Service details for your SQL database and click Create. 21. After configuring both the source and target datasets, and the pipeline, publish all the elements to save your work. 22. Once the pipeline is running successfully, you can verify its functionality by querying the destination database to ensure data is being transferred properly. a. Go to the SQL Database and select the relevant database. b. Select the database on which we have perform a query. c. Log in with your credentials. d. Write a simple test query to verify data has been transferred from Blob Storage to the SQL Database. Execute the query and confirm that the expected output is returned. Conclusion: Integrating Azure Blob Storage with Azure Data Factory is a powerful way to manage and automate data workflows in the cloud. This guide walks you through creating a storage account, configuring containers, uploading data, and designing a pipeline to process and transfer data to Azure SQL Database. By following these steps, you can efficiently handle large-scale data integration and ensure seamless communication between your data sources and destinations. Azure Data Factory not only simplifies the process of orchestrating data pipelines but also provides robust options for monitoring and optimizing workflows. Whether you are managing JSON files, processing transactional data, or setting up complex ETL processes, Azure’s ecosystem offers a reliable and scalable solution. Start exploring these tools today to unlock new possibilities in data-driven operations! We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfonts.com.