Step 1: Pre-Outline Brief Target Audience: Purpose:To clarify when to use session storage vs local storage in Power Apps Portals, using a real-world use case: syncing customer dropdown selection across pages in a portal. Pain Points Solved: Step 2: Core Content Scenario Overview I was working on a customer dropdown inside a Power Apps Portal (Dashboard). When a customer was selected, I wanted: This brought up the key question: “Should I use session storage or local storage?“ Understanding Session Storage vs Local Storage Before diving into the solution, let’s break down the difference: 🔹 Session Storage 🔹 Local Storage Key difference: Problem Statement When building multi-page Power Apps Portals, we often need to carry user selections (like Account/Customer IDs) across pages. But which one should we use? Initial Approach and Issue I first used localStorage for the customer selection. While it worked across pages, it had one drawback: This confused users because they expected a “fresh start” after logging back in. Working Solution: Using Session Storage The best solution was to use sessionStorage: Power Apps Portal Code Example 1. Store customer selection in sessionStorage (Dashboard page): 2. Apply selection on another page (e.g., Contracts page): 3. Clear selection on Sign Out (SignIn page): Benefits of This Approach In Power Apps Portals, deciding between sessionStorage and localStorage depends on user expectations: In my customer dropdown scenario, sessionStorage was the clear winner, as it ensured selections synced across pages but reset cleanly at logout. Sometimes, it’s not about picking one — but knowing when to use both to balance persistence with user experience. Need help implementing storage logic in your Power Pages? Reach out to CloudFronts Technologies as I’ve already implemented this use case for syncing dropdowns between Dashboard and childpages in a Portal website. You can contact us directly at transform@cloudfronts.com.

One limitation while working with MS forms is the 1 GB limit on file submission through the forms. Many of you guys are must be using Forms to get files from users or clients outside your organizations and those files can be over 1GB.  In this blog I will show you how you let users submit files over 1 GB through MS Forms and store this response into a SharePoint list. So let’s being..  Approach:   MS Form stores all the files onto your one drive, One drive also offers a feature called “Request Files” using which you can create a shareable link to a one drive folder in which anyone with the link can upload files and it has no limit over the size of the file.   So instead of using the forms upload file feature we will be using shareable link from the Request File feature on the form using which users will be able to submit documents of any size. Let’s see how to do this.  Create Shareable link to a one drive folder using Request File Feature.  Copy this link and save it we will be using this link in our MS form.  Create MS Form.  You can add the link as you want on the form you can also add it in your sections sub title (Both these are just examples or ideas of how you can show users this link.)  Stored attachments in one drive.  We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

SQL Server Reporting Services (SSRS) remains a cornerstone technology in the Microsoft BI stack, and mastering its expression language is crucial for creating dynamic, professional reports. While Power BI has gained significant attention in recent years, SSRS continues to excel in pixel-perfect reporting, complex tabular reports, and scenarios requiring precise formatting control. In this comprehensive guide, we’ll explore practical SSRS expressions focusing on two critical areas: date handling and conditional formatting. These examples will help you create more dynamic and user-friendly reports that adapt to your data and business requirements. Key takeaways: Understanding SSRS Expression Basics SSRS expressions use Visual Basic .NET syntax and are enclosed in equal signs: =Expression. They can access: Date Handling Expressions 1. Dynamic Date Ranges in Headers Scenario: Display “Report for Q1 2024” or “Monthly Report – March 2024” based on parameter selection. =Switch(     Parameters!DateRange.Value = “Q1”, “Report for Q1 ” & Year(Parameters!StartDate.Value),     Parameters!DateRange.Value = “Q2”, “Report for Q2 ” & Year(Parameters!StartDate.Value),     Parameters!DateRange.Value = “Monthly”, “Monthly Report – ” & MonthName(Month(Parameters!StartDate.Value)) & ” ” & Year(Parameters!StartDate.Value),     True, “Custom Report – ” & Format(Parameters!StartDate.Value, “MMM yyyy”) & ” to ” & Format(Parameters!EndDate.Value, “MMM yyyy”) ) 2. Age Calculations Scenario: Calculate precise age from birth date, handling leap years correctly. =DateDiff(“yyyy”, Fields!BirthDate.Value, Now()) –  IIf(Format(Fields!BirthDate.Value, “MMdd”) > Format(Now(), “MMdd”), 1, 0) 3. Business Days Calculation Scenario: Calculate working days between two dates, excluding weekends. =DateDiff(“d”, Fields!StartDate.Value, Fields!EndDate.Value) –  DateDiff(“ww”, Fields!StartDate.Value, Fields!EndDate.Value) * 2 –  IIf(Weekday(Fields!StartDate.Value) = 1, 1, 0) –  IIf(Weekday(Fields!EndDate.Value) = 7, 1, 0) 4. Fiscal Year Determination Scenario: Convert calendar dates to fiscal year (assuming fiscal year starts in April). =IIf(Month(Fields!TransactionDate.Value) >= 4,      Year(Fields!TransactionDate.Value),      Year(Fields!TransactionDate.Value) – 1) 5. Relative Date Formatting Scenario: Display dates as “Today”, “Yesterday”, “3 days ago”, or actual date if older. =Switch(     DateDiff(“d”, Fields!OrderDate.Value, Now()) = 0, “Today”,     DateDiff(“d”, Fields!OrderDate.Value, Now()) = 1, “Yesterday”,     DateDiff(“d”, Fields!OrderDate.Value, Now()) <= 7, DateDiff(“d”, Fields!OrderDate.Value, Now()) & ” days ago”,     DateDiff(“d”, Fields!OrderDate.Value, Now()) <= 30, DateDiff(“d”, Fields!OrderDate.Value, Now()) & ” days ago”,     True, Format(Fields!OrderDate.Value, “MMM dd, yyyy”) ) 6. Quarter-to-Date Calculations Scenario: Show if a date falls within the current quarter-to-date period. =IIf(Fields!SalesDate.Value >= DateSerial(Year(Now()), ((DatePart(“q”, Now()) – 1) * 3) + 1, 1)      And Fields!SalesDate.Value <= Now(), “QTD”, “Prior Period”) Conditional Formatting Expressions 1. Performance-Based Color Coding Scenario: Color-code sales performance against targets with multiple thresholds. Background Color Expression: =Switch(     Fields!ActualSales.Value / Fields!TargetSales.Value >= 1.1, “DarkGreen”,     Fields!ActualSales.Value / Fields!TargetSales.Value >= 1.0, “Green”,     Fields!ActualSales.Value / Fields!TargetSales.Value >= 0.9, “Orange”,     Fields!ActualSales.Value / Fields!TargetSales.Value >= 0.8, “Red”,     True, “DarkRed” ) Font Color Expression: =IIf(Fields!ActualSales.Value / Fields!TargetSales.Value >= 0.9, “White”, “Black”) 2. Alternating Row Colors with Grouping Scenario: Maintain alternating row colors even with grouped data. =IIf(RunningValue(Fields!ProductID.Value, CountDistinct, “DataSet1”) Mod 2 = 0, “WhiteSmoke”, “White”) 3. Conditional Visibility Based on User Roles Scenario: Hide sensitive columns based on user permissions. =IIf(User!UserID Like “*admin*” Or User!UserID Like “*manager*”, False, True) 4. Traffic Light Indicators Scenario: Display traffic light symbols based on status values. Color Expression: =Switch(     Fields!Status.Value = “Complete”, “Green”,     Fields!Status.Value = “In Progress”, “Orange”,     Fields!Status.Value = “Not Started”, “Red”,     True, “Gray” ) 5. Dynamic Font Sizing Scenario: Adjust font size based on the importance or value of data. =Switch(     Fields!Priority.Value = “Critical”, “14pt”,     Fields!Priority.Value = “High”, “12pt”,     Fields!Priority.Value = “Medium”, “10pt”,     True, “8pt” ) To conclude, SSRS expressions provide powerful capabilities for creating dynamic, responsive reports that adapt to your data and business requirements. The examples covered in this guide demonstrate how to handle common scenarios involving dates and conditional formatting, but they represent just the beginning of what’s possible with SSRS. As you continue developing your SSRS expertise, remember that these expression capabilities complement other BI tools in your arsenal. While Power BI excels in self-service analytics and modern visualizations, SSRS remains unmatched for precise formatting, complex tabular reports, and integration with traditional SQL Server environments. Whether you’re creating executive dashboards, regulatory reports, or operational documents, mastering SSRS expressions will significantly enhance your ability to deliver professional, dynamic reporting solutions that meet your organization’s specific needs. We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

Power BI is one of the most popular tools for business intelligence and reporting. But out-of-the-box reports often fall short when it comes to addressing real-world business needs. To truly maximize its potential, Power BI can be customized with advanced features like conditional formatting, multi-page designs, and Row-Level Security (RLS). In this blog, we’ll walk through a practical example of customizing a Power BI report for territory-based account analysis. Even if you’re a beginner, this guide will help you understand the steps and how you can apply them in your own reports. Problem Statement The business needed to analyze accounts by sales territory. The default Power BI report had limitations: – All territories looked the same on the map, making it difficult to differentiate them. – Managers had no easy way to drill into account-level details. – Sensitive account data was visible to everyone, creating compliance risks. Clearly, a more structured and secure approach was needed. Solution Approach Using DAX, we created a measure to assign each territory a unique color. This helped managers quickly distinguish regions on the map. 2. Multi-Page Report Design We structured the report across three pages: – Page 2 – Drill-Through Account Details: Clicking on a territory brings you here to view specific accounts. – Page 3 – Tabular Data View: A table version of Page 2 for exporting and validating data. 3. Row-Level Security (RLS) RLS was applied so each Territory Manager only sees data for their assigned region. This not only secures data but also builds trust among users. Key Learnings – Beginners can start small: apply conditional formatting to bring clarity to visuals. – Multi-page design makes reports more user-friendly than cluttering everything on one screen. – RLS is essential for real-world deployments, ensuring only the right people see the right data. To conclude, by customizing Power BI with conditional formatting, multi-page design, and Row-Level Security, even a beginner can create professional-grade reports. These enhancements transform Power BI into a secure, role-based tool that aligns with how businesses actually operate. We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com.

In conversations with Business Central customers, one recurring theme stands out: permissions remain the single biggest operational pain point. For too long, organizations have taken the path of least resistance: The outcome? A fragile balance where security is compromised, efficiency is slowed, and compliance becomes an afterthought. But permissions should not be a roadblock. They should be a strategic enabler. Moving Beyond “Access” to “Enablement” Business Central has quietly matured its security model. The challenge is not capability, but mindset. Organizations must move from access as convenience to permissions as governance. Here are three levers that shift permissions from problem to advantage: Why This Matters for Leaders Strong permissions are not an IT housekeeping task—they are a strategic safeguard: The Leadership Imperative To conclude, Business Central leaders must stop viewing permissions as a technical nuisance. In an era of increasing scrutiny on data security and compliance, permission architecture is leadership architecture. The organizations that invest in this today will not only reduce risk but also unlock smoother onboarding, faster adoption, and a culture of accountability. If you need further assistance or have specific questions about your ERP setup, feel free to reach out for personalized guidance. We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudfronts.com. It’s time to replace the culture of SUPER users with a culture of super governance.

In today’s global manufacturing landscape, businesses need more than just strong products to stay competitive. They need digital operations that connect customers, distributors, and internal teams in different regions. One powerful way to achieve this is by integrating e-commerce platforms with enterprise resource planning (ERP) systems. This is the story of a 140-year-old global leader in materials testing machine manufacturing that transformed its order-taking process through a Shopify–Dynamics 365 Finance & Operations integration. The Challenge With offices in five countries and sales across the UK, Europe, China, India and multiple U.S. territories, this manufacturer had a truly global footprint. Yet, order-taking remained manual and inefficient: In short: their legacy setup couldn’t keep up with modern customer expectations or their own ambitions for global growth. The Solution Over the course of a decade long partnership, we helped the company modernize and digitize its business processes. The centerpiece was a seamless integration between Shopify and Dynamics 365 Finance & Operations (F&O), built natively within F&O (no recurring middleware costs). Key integrations included: This solution ensured that high data volumes and complex processing demands could be handled efficiently within F&O. The Results The change has reshaped how the company works: Lessons for Other Global Manufacturers This journey highlights critical lessons for manufacturers, distributors, and global businesses alike: The Road Ahead After integrating Shopify with Dynamics 365 F&O, the company has launched a dedicated distributor website where approved distributors can place orders directly on behalf of customers. This portal creates a new revenue stream, strengthens the distribution network, and ensures orders flow into F&O with the same automation, inventory sync, and reporting as direct sales. By extending digital integration to distributors, the company is simplifying order-taking while expanding its business model for global growth. Ending thoughts The journey of this global manufacturer shows that true digital transformation isn’t about adding more tools, it’s about connecting the right ones. By integrating Shopify with Dynamics 365 F&O, they moved from fragmented, manual processes to a scalable, automated ecosystem that empowers customers, distributors, and internal teams alike. For any organization operating across regions, the lesson is clear: e-commerce and ERP should not live in silos. When they work together, they create a foundation that not only accelerates order taking but also unlocks new revenue streams, sharper insights, and stronger global relationships. In a world where speed, accuracy, and customer experience define competitiveness, the question isn’t whether you can afford to integrate, it’s whether you can afford not to. If you need further assistance or have specific questions about your ERP setup, feel free to reach out for personalized guidance.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.

Managing budgets is a key part of financial discipline and managing budgets is more than just tracking numbers. Companies need to make sure departments, projects, and cost centers spend within limits. Dynamics 365 Finance helps by providing a built-in Budget Control feature that keeps spending under check right where daily transactions happen. In Dynamics 365 Finance, Budget Control helps to enforce spending limits in real time, directly within transactions. Budget control is a tool in D365 Finance that checks transactions against available budgets. If a transaction exceeds the budget, the system can either: This way, overspending is caught before it happens. Steps to know how It works How Budget Control Works in Dynamics 365 Finance When setting up budget control (see screenshot below), finance teams define: This ensures that every purchase, expense, or journal is validated against budgets before the company commits to spending. Example: If Marketing has a $100,000 budget and a new purchase order exceeds it, the system can block it or route it to a manager. Why is Budget Control Important? Budget control in D365 Finance is a simple but powerful way to enforce financial discipline. It connects budgeting with daily operations, helping companies stay on track. If you are looking to set up or optimize Budget Control in your organization, our team can help you design the right approach, implement best practices, and ensure a smooth rollout. Reach out to CloudFronts Technologies at transform@cloudfronts.com to explore how we can support your Dynamics 365 Finance Budgeting journey.

In any growing business, finance isn’t just about ticking compliance boxes anymore. It’s about staying in control, spotting trends early, and making confident decisions fast. That’s exactly where financial dimensions in Dynamics 365 Finance come into play. Over the last few months, we’ve seen multiple requirements from businesses asking for smarter use of dimensions. And it makes sense, dimensions are no longer just an optional “nice-to-have.” They’re becoming the backbone of modern financial management, enabling organizations to track performance in ways that directly support decision-making. Think of them as a smarter way to organize your numbers. They give finance teams the flexibility they need to adapt on the fly, and they give leadership the kind of clear, real-time visibility that helps drive better business calls  What Are Financial Dimensions? At the core, financial dimensions are labels you attach to transactions. These labels tell you: So instead of tracking expenses only by account (e.g., Travel Expenses), you can track: All this without creating hundreds of extra GL accounts. Why Should Management Care? Here’s how financial dimensions support strategic and operational goals: 1. Multi-Dimensional Reporting Want to review profitability by region, department, or project? Dimensions let you filter and analyze financial data from multiple angles—without waiting on custom reports. This supports faster decision-making, better forecasts, and more agile operations.  “How much did we spend on marketing in South India last quarter?” You’ll have the answer in seconds. 2. Budgetary Control and Cost Monitoring Dimensions allow finance teams to set up budget controls per department or project. This ensures: Spot overruns before they become problems not after. 3. Cleaner Chart of Accounts Without dimensions, you’d need separate accounts like: This becomes unmanageable. With dimensions, you keep one account (611000 – Travel) and layer in detail using dimensions, keeping your chart lean and reporting rich. 4. Easier Scaling and Restructuring Adding a new business unit, product line, or region? No need to overhaul your chart of accounts. Just add new dimension values. Dimensions give you the structure you need today and the flexibility you’ll need tomorrow. A Practical Example Let’s say you want to understand the true cost of a customer support center in Pune. You can filter all expense accounts with: Immediately, you’ll see: All grouped by those two dimensions without modifying your account structure. Final Word Financial dimensions are not just about slicing data they’re about driving alignment between finance and operations. They: If you’re already using Dynamics 365 or considering it, investing time in defining the right dimensions upfront will pay dividends for years. Planning a D365 Finance rollout or re-implementation? Let’s talk about how to design a dimension strategy that fits your business model. You can reach out to us at transform@cloudfronts.com. 

Why SmartPitch? – The Idea and Pain Point  The idea for SmartPitch came directly from observing the day-to-day struggles of sales and pre-sales teams. Every Marketing Qualified Lead (MQL) to Sales Qualified Lead (SQL) conversion required hours of manual work: searching through documents stored in SharePoint, combing through case studies, aligning them with solution areas, and finally packaging them into a client-ready pitch deck.  The reality was that documents across systems—SharePoint, Dynamics 365, PDFs, PPTs—remained underutilized because there was no intelligent way to bring them together.   Sales teams often relied on tribal knowledge or reused existing decks with limited personalization.  We asked: What if a sales assistant could automatically pull the right case studies, map them to solution areas, and draft an elevator pitch on demand, in minutes?  That became the SmartPitch vision: an AI-powered agent that:  As a result of this product, it has helped us reduce pitch creation time by 70%.   2. The First Prototype – Custom Copilot Studio  Our first step was to build SmartPitch using Custom Copilot Studio. It gave us a low-code way to experiment with conversational flows, integrate with Azure AI Search, and provide sales teams with a chat interface.  1. Knowledge Sources Integration  2. Data Flow  3. Conversational Flow Design  4. Integration and Security  5. Technical Stack  6. Business Process Enablement  7. Early Prototypes  With Custom Copilot, we were able to:  We successfully demoed these early prototypes in Zurich and New York. They showed that the idea worked but they also revealed serious limitations.  3. Challenges in Custom Copilot  Despite proving the concept, Custom Copilot Studio had critical shortcomings:  Lacked support for model fine-tuning or advanced RAG customization.  However, incorporating complex external APIs or custom workflows was difficult.  This limitation meant SmartPitch, in its Copilot form, couldn’t scale to meet enterprise standards.  4. Rebuilding in Azure AI Foundry – Smarter, Extensible, Connected  The next phase was Azure AI Foundry, Microsoft’s enterprise AI development platform. Unlike Copilot Studio, AI Foundry gave us:  Extending SmartPitch with Logic Apps  One of the biggest upgrades was the ability to integrate Azure Logic Apps as external tools for the agent. This allowed SmartPitch to:  This modular approach meant we could add new functionality simply by publishing a new Logic App. No redeployment of SmartPitch was required.  Automating Document Vectorization  We also solved one of the biggest bottlenecks—document ingestion and retrieval—by building a pipeline for automatic document vectorization from SharePoint:  This allowed SmartPitch to search across text, images, tables, and PDFs, providing relevant answers instead of keyword matches.  But There Were Limitations  Even with these improvements, we hit roadblocks:  At this point, we realized the true bottleneck wasn’t the agent itself, it was the quality of the data powering it.  5. Bad Data, Governance, and the Medallion Architecture  SmartPitch’s performance was only as good as the data it retrieved from. And much of the enterprise data was dirty: duplicate case studies, outdated documents, inconsistent file formats.  This led to irrelevant or misleading responses in pitches.  To address this, we turned to Databricks’ Unity Catalog and Medallion Architecture:  You can read our post on building a clean data foundation with Medallion Architecture [Link]   Now, every result SmartPitch surfaced could be trusted, audited, and tied to a governed source.  6. SmartPitch in Mosaic AI – The Final Evolution  The last stage was migrating SmartPitch into Databricks Mosaic AI, part of the Lakehouse AI platform. This was where SmartPitch matured into an enterprise-grade solution.  What We Gained in Mosaic AI:  In Mosaic AI, SmartPitch wasn’t just a chatbot it became a data-native enterprise sales assistant:  From these, we came to know the following differences between agent development in AI Foundry & DataBricks Mosaic AI –    Attribute / Aspect  Azure AI Foundry  Mosaic AI  Focus  Developer and Data Scientist  Data Engineers, Analysts, and Data Scientists  Core Use Case  Create and manage your own AI agent  Build, experiment, and deploy data-driven AI models with analytics + AI workflows  Interface  Code-first (SDKs, REST APIs, Notebooks)  No-code/low-code UI + Notebooks + APIs  Data Access  Azure Blob, Data Lake, vector DBs  Native integration with Databricks Lakehouse, Delta Lake, Unity Catalog, vector DBs  MCP Server  Only custom MCP servers supported; built-in option complex  Native MCP support with Databricks ecosystem; simpler setup  Models  90 models available  Access to open-source + foundation models (MPT, Llama, Mixtral, etc.) + partner models  Model Customization  Full model fine-tuning, prompt engineering, RAG  Fine-tuning, instruction tuning, RAG, model orchestration  Publish to Channels  Complex (Azure Bot SDK + Bot Framework + App Service)  Direct integration with Databricks workflows, APIs, dashboards, and third-party apps  Agent Update  Real-time updates in Microsoft Teams  Updates deployed via Databricks workflows; versioning and rollback supported  Key Capabilities  Prompt flow orchestration, RAG, model choice, vector search, CICD pipelines, Azure ML & responsible AI integration  Data + AI unification (native to Lakehouse), RAG with Lakehouse data, multi-model orchestration, fine-tuning, end-to-end ML pipelines, secure governance via Unity Catalog, real-time deployment  Key Components  Workspace & agent orchestration, 90+ models, OpenAI pay-as-you-go or self-hosted, security via Azure identity  Mosaic AI Agent Framework, Model Serving, Fine-Tuning, Vector Search, RAG Studio, Evaluation & Monitoring, Unity Catalog Integration  Cost / License  Vector DB: external, Model Serving: token-based pricing (GPT-3.5, GPT-4), Fine-tuning: case-by-case, Total agent cost variable (~$5k–$7k+/month)  Vector Search: $605–$760/month for 5M vectors, Model Serving: $90–$120 per million tokens, Fine-Tuning Llama 3.3: $146–$7,150, Managed Compute built into DBU usage, End-to-end AI Agent ~$5k–$7k+/month  Use Cases / Capabilities  Agents intelligent, can interact/modify responses; single AI search per agent; infrastructure setup required; custom MCP server registration  Agents intelligent, interact/modify responses; AI search via APIs (Google/Bing); in-built MCP server; complex infrastructure; slower responses as results batch sent together  Development Approach  Low-code, faster agent creation, SDK-based, easier experimentation  Manual coding using MLflow library, more customization, API integration, higher chance of errors, slower build  Models Comparison  90 models, Azure OpenAI (GPT-3.5, GPT-4), multi-modal  ~10 base models, OSS & partner models (Llama, Claude, Gemma), many models don’t support tool usage  Knowledge Source  One knowledge source of each type (adding new replaces previous)  No limitation; supports data cleaning via Medallion Architecture; SQL-only access inside agent; Spark/PySQL not supported in agent  Memory / Context Window  8K–128K tokens (up to 1M for GPT-4.1)  Moderate, not specified  Modalities  Text, code, vision, audio (some models)  Likely text-only  Special Enhancements  Turbo efficiency, reasoning, tool calling, multimodal  Varies per model (Llama, Claude, Gemma architectures)  Availability  Deployed via Azure AI Foundry  Through Databricks platform  Limitations  Only one knowledge source of each type, infrastructure complexity for MCP server  No multi-modal Spark/PySQL access, slower batch responses, limited model count, high manual development  7. Lessons Learned:  … Continue reading Inside SmartPitch: How CloudFronts Built an Enterprise-Grade AI Sales Agent Using Microsoft and Databricks Technologies  →

In any enterprise application like Dynamics 365 Project Operations, setting up a secure and structured environment is the foundation of a successful implementation. Before diving into projects, resource planning, or billing, it’s critical to configure the environment, establish legal entities, assign the right user roles, and implement appropriate security controls. This article explains how to configure these foundational elements in D365 PO. 1. Legal Entity Configuration A Legal Entity in D365 represents an organization that can enter into legal contracts and is used to segregate financial, operational, and statutory data. Steps to Configure: Why It Matters: Each project in D365 PO must be linked to a legal entity for:  2. User Setup D365 users are authenticated via Azure Active Directory (Azure AD). Once synced, users must be provisioned in the application. How to Set Up: 3. Security Roles & Duties Security in D365 PO is role-based, meaning users get access based on the role(s) assigned to them. Each security role contains duties, which contain privileges. Common Roles in D365 PO: Role Name Purpose Project Manager Manage project planning, time entry approvals Project Accountant Responsible for costing, billing, revenue Resource Manager Manage bookings and capacity Salesperson Handle opportunities and quotes Time/Expense User Submit time and expenses System Administrator Full access, environment config  Assigning Roles:  4. Security Settings & Access Controls Security ensures users can access only what they are authorized to. Key Configurations: Advanced Features: 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.