Advantages of D365 and Cloud Offering

Introductions Tim Harris VP Strategy & Solutions tim@arbelatech.com Twitter: @DaxTalk Arbela Technologies www.ArbelaTech.com Twitter: @ArbelaTech

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Azure

http://azureplatform.azurewebsites.net/en-us/

Evolution of AX / D365

Evolution of the Technology Dynamics Platform Dynamics 365 for Operations Dynamics AX Dynamics CRM Operations Sales Service Field Service Project Service Marketing PowerApps Dynamics AX Dynamics CRM Scalability up and out with 32 Cores + 96GB Memory Unlimited auto-scaling with no additional cost, Geo-Replication & Sync, On-Prem WMS, MES, Retail, Built in DR, Backup, Performance Management Scale Scalability limited to 8GB + 4 Cores per AOS – Have to Scale Out .NET Connector Integrations + Early AIF Versions AIF & DIXF integration DIXF, SOAP, JSON, Microsoft Flow Common Data Service, Integration Services, Azure ML Integration Reporting Web Connectivity via SharePoint EP, Native Reporting Engine, Some SSRS Move to SSRS Reporting, SSAS Cubes for BI SSRS, Entity Store, Integrated Power BI Native Mobile Development, PowerApps for rapid mobile development Mobile No Native Mobile Companion Apps for Expense, Approvals, Shop Floor

Evolution of the Functional Dynamics Platform Dynamics AX 2009 Dynamics AX 2012 Dynamics 365 for… Dynamics AX Dynamics CRM Operations Sales Service Field Service Project Service Marketing PowerApps Dynamics AX Dynamics CRM Built in Workflow Engine with Workflow templates Built it Workflow Engine with Workflow Templates Workflow Difficult .NET based external solution No real modelling Organizational Hierarchy for modeling and versioning org changes & policies Organizational Hierarchy for modeling and versioning org changes & policies Org Modelling Finance Core Financial Engine Expanded Dimension Functionality, Collections Management, eBanking Integration Expanded Dimension Functionality, Collections Management, eBanking Integration, Financial Checklists Robust Security, Role – Duty – Privilege - SoD Compliance Basic Security Robust Security, Role – Duty – Privilege - SoD

Deployment Scenarios

Microsoft Ecosystem

The Microsoft Ecosystem

Common Data Service The three pillars of the Common Data Service are: Be the focal point for your data: bring your data together into one place. Be a great place to build and manage apps: help app creators and developers of all skill levels to easily create apps with the data in the Common Data Service. It just works with the rest of Microsoft: provide out-of-the-box integrations with technologies across Microsoft including Flow, Power BI, and Office. What CDS isn’t yet: Master Data Management (MDM) – though it is being worked on.

Common Data Service between D365 Applications Connect D365 For Sales and D365 For Operations using Common Data Service. D365 Cust | D365 for Ops Accounts  Customers Contacts  Contacts Products  Products Quotes  Quotes Sales Orders  Sales Orders Invoices  Invoices D365 for Customer Engagement Accounts  Customer Contacts Products  Products Quotes Sales Orders  SO Invoices  Invoice Common Data Service D365 for Operations & Finance

The Microsoft Graph

Extensibility Build custom LOB apps & automation PowerApps MSFT Flow Dynamics 365 CUSTOM CONNECTOR CONNECTORS GATEWAYS Cloud services On-premise data 3rd party apps Common Data Model TAKE AWAY Organizations often time require rapid building of purpose-built custom LOB apps. These may require data from many sources whether these are from cloud services, on-premise data, or business applications such as Dynamics 365. PowerApps and Flow provide integration via Connectors and Gateways that make it possible for organizations to get data out of services they are already using. Options: Connector for Dynamics 365 (AX/CRM) is a purpose built connector to get data out of Dynamics 365 apps. Connectors for cloud services is a custom built connector organization can build to get data out of services. On-Premises Data Gateways make it possible to get data out of in-house LOB solutions/apps. New: Office 365 integration using SharePoint Modern lists Customer Stories:

Advanced Analytics

Approach to BI & Analytics Projects – ADI Analytics

Approach to BI & Analytics Projects Target Personas Define the Questions Define the Business Model Define Facts Define Dimensions DEFINE PHASE Define the roles for a business area, within a targeted domain. Define the critical questions to answer that drive all further work Define the facts and definitions (dimensions) that surround those facts. List always in business semantics Define facts with tables and fields from targeted data source. Define dimensions with tables and fields from targeted data source. Create Semantic Layer Create Presentation Layer Validate Against Questions Deploy to Users Training & Support CREATE PHASE Create semantic layer that maps from your sources to the data warehouse for enabling presentation layer. Create presentation layer for targeted persona’s that answer defined questions Validate story from presentation layer against targeted personas and questions. Refine as needed. Deploy presentation layer deliverables that relate to targeted personas and business questions. Post deployment training for end users and technical staff. On-going support for expanding insights.

Advanced Analytics EXAMPLE SOLUTIONS Sales and marketing Finance and risk Customer and channel Operations and workforce Sales forecasting Fraud detection User segmentation Agent allocation Demand forecasting Credit risk management Personalized offers Warehouse efficiency Sales lead scoring Product recommendation Smart buildings Fraud detection is just one scenario where we’re seeing very broad use of Advanced Analytics. The above is just a snapshot, but it gives you an idea of the other areas where Advanced Analytics is helping solve tough business problems. For example sales and marketing is the #1 use of Advanced Analytics today. That’s because most any business of any type can benefit from knowing what customers are going to stay or leave, how to keep the churn risk segment happy and how to make the most of their most valuable customers. We have some more specific examples of that coming up. Marketing mix optimization Predictive maintenance Supply chain optimization

Relationship Insights

Base Cards - Relationship Insights

Email Cards – Relationship Insights

Embedded Interface

Relationship & Email Engagement, Productivity - Insights

IoT

Innovation at work – real world IoT use cases Aircrafts Cows Street sweepers Electric charging stations Auto Fryers Oil equipment Dogs Vending machines Buses Power plant Buildings Internet of Things Factory floor Oil distribution Racing Elevators Trucks While there are a lot of interesting IoT scenarios unfolding in the consumer space, based on our experience in working with customers and partners we see the majority of IoT value being enabled in the commercial space. This is backed by a recently released McKinsey report that states that 70% of the value enabled by IoT will come from B2B scenarios. Whether its Rockwell Automation, from whom you'll hear from later on today, that is helping its oil and gas customers improve efficiency by monitoring supply chain assets, or ThyssenKrupp elevators that is doing predictive maintenance on elevators to prevent unscheduled downtime for their customers, or the Stanford Linear Accelerator Center (SLAC) that is using IoT to continuously monitor various sensors of the linear accelerator to anticipate problems, take action and prevent failure; organization of all types are starting to harness the value of IoT to transform themselves. Of course, as a solution provider you could very well be working with a customer that's creating a consumer product, let's say a car manufacturer. However, the value you'll be providing in this B2B2C scenario is helping that organization build an enterprise grade IoT solution so they can launch their products. Our focus here is simply to enable build enterprise grade internet of their things solutions for your customers. Our goal is to provide you the best platform to do this. Power tools Vaccine dispensers Mining equipment Surveillance Engines Postboxes Smart meters Smart grids Medical devices

Operational Efficiency

Business Intelligence

Business Intelligence