At its core, Business Central still does what a good accounting system should do: manage finances, control data and provide reliable reporting. But it no longer stops there. Built as a cloud‑based platform, it supports much more than accounting alone – spanning supply chain management, purchasing, inventory, warehousing and operational processes – and gives businesses better visibility over how work flows through the organisation.

One of the key differentiators of Business Central is its twice yearly release cycle, complemented by regular monthly updates. Rather than disruptive upgrade projects every few years, organisations receive continuous improvements – new functionality, performance enhancements, and security updates – as part of their ongoing service. This means businesses are always working with a modern solution. More recently, AI capabilities such as Microsoft Copilot have been embedded directly within Business Central, offering contextual summaries and assistance that support everyday decision‑making.

50,000+ organisations worldwide now run Microsoft Dynamics 365 Business Central, supporting millions of users across finance and operational teams globally. One of its defining strengths is how closely it integrates with Microsoft tools such as Outlook and Teams for day-to-day communication, Excel for analysis, and Power BI for real-time reporting.

Automation plays a key role, particularly when combined with specialist add‑on applications available through Microsoft AppSource, which offers 5,000+ certified extensions for Business Central (Shopify, Paypal, Continia…). Tools such as Continia, which is built entirely inside Business Central, help automate areas like invoice processing, approvals and expense management. It can reduce your manual processes by 90%, fewer errors and more time spent on work that genuinely adds value – a welcome change for anyone who has ever chased an approval on a Friday afternoon.

No two organisations operate in the same way. Jersey businesses span a wide range of sectors – from financial services, charity sector, legal firms to retailers – each with their own pressures and priorities. A modern ERP system needs to adapt to those differences, rather than force every organisation into the same mould.

At Prosperity 24/7, our focus is on understanding how each business works in practice. Not simply on deploying software but on how decisions are made, and where better visibility and control can add real business value. Configuration, automation and extensions are tailored accordingly, ensuring the system supports day-to-day operations while remaining flexible for future growth.

In a world where businesses are expected to move faster, comply with increasing regulation and gain insight from ever growing volumes of data, having a modern ERP platform at the centre is no longer optional. At Prosperity 24/7, a diverse Business Solutions team with varied backgrounds continues to upskill and collaborate, ensuring technology is applied in a way that genuinely supports evolving Jersey business needs.

This article was first published in the Jersey Evening Post

The post From accounting system to intelligent platform: how modern ERP is reshaping business operations appeared first on Prosperity 247.

Artificial intelligence, or AI, is the ability of machines to do things that normally require human intelligence, such as understanding language, recognising images, making decisions, and learning from data. AI is not a single “thing” at all, but a collection of methods and tools that can be applied to the various problems and domains that we have. They have been around for a while now and you will already be familiar with, and using them:

• Machine learning: Predictive models based on data and statistics – used for predicting the weather.
• Anomaly detection: Systems that detect unusual patterns or events, enabling pre-emptive action – found in security and monitoring systems.
• Computer vision: Applications that interpret visual input from cameras, images, or videos – often used in KYC processes and in speed cameras.
• Conversational AI: AI agents, (or bots), that can engage in dialogs with human users – ChatGPT anyone (or that ghastly paperclip from ye olde Office applications)?

It’s in this last area that we have seen AI recently get pushed into the limelight in the past few months. With conversational based apps that feel like we are talking to an intelligent creature and getting unique outputs.

“a highly detail picture of a futuristic circuit board with a brain in the middle of it. hyperealistic, 4k render, HDR, god rays, ray tracing.”

What is all the fuss about?

ChatGPT took the world by storm with its scarily impressive abilities to not only understand language but to also create and produce things such as stories, poems and computer code. Being able to create (often) new things from a set of natural language instructions is what we know as generative AI and it couldn’t be done without the use of Large Language Models (LLMs).

LLMs are capable of understanding and generating human-like text by processing vast amounts of data. They are a key component of generative AI.

It was this that got so many people using the technology – the ability to be able to create seemingly new creations from simply describing them. Suddenly everyone could feel like a video artist, a poet, a musician or a highly skilled visual artist, and it truly does feel like magic.

Wherever you sit on the ethical concerns and conversations to be had around this technology there is no denying, it can do some very impressive stuff and is improving at doing so at an alarming rate.

Go try some applications out if you haven’t already – a few I have used and been impressed by are: ChatGPT, Sudo, Microsoft Copilot and DALL-E*.

*(I have used DALL-E to generate the images in this article with the prompts underneath. If you use the same prompts, you will get a totally new picture based upon the same idea! Am I graphic designer now? Is DALL-E?)

“a monkey looking at a fire fairy”

What does this mean to me?

At the very least you are going to be continually using products and services that utilise AI to provide you with a better experience, and you may not even notice. At best you will arm yourself with the correct AI tools to improve your life, work, productivity and creativity.

It is in the best interests of professionals and businesses (and all people really!) to capitalise on the benefits that can be had from using AI and integrating AI tools, features and services into existing processes and solutions.

Let me to take you through some of the ways AI has helped me to help give a broader picture.

• Music Production – there are some great applications of AI in the audio plugin world. From smart compressors and EQs(equalisers) to sound separation tools that allow you to, for example, isolate a vocal from a full track or reduce the background noise on an audio sample.
• Writing – generative AI can be super useful in generating, writing, critiquing and summarising content. It has helped with a few ideas for this piece (although I prefer to largely write my own material to retain my voice). I go to it for various things such as E-mails, Power Point slides, articles and documentation. It’s great at coming up with a plan to cover pretty much any subject you can throw at it, which can then be used as inspiration for what you are working on.
• Googling – or should I say “Generative AI’ing”. I’ll often just ask Copilot (more on that later) for queries I have. Rather than me going to a search engine, looking at a few of the most likely relevant results, skim reading each, gaining an understanding of the material and coming up with a summarised idea of it in my head… I just let Copilot do that for me, in a few seconds.
• For example, “Tell me the top 5 things people do in New York with a total budget of $1000 in October. Don’t include anything that includes big heights.”
• Coding – many a times have I asked Copilot (Microsoft’s generative AI tool) to write me a quick bit of JavaScript or to talk me through more complicated C# coding solutions. Not only is it a great at teaching these things but also coming up with code solutions. Of course, anything it produces is highly scrutinised, as it does gets things wrong on occasion!
• Enhancing Client Offerings – being able to access many AI services and tools means I can now offer things to my clients that were previously outside my skillset.

You want automatic translations of any document stored in a particular folder into 5 different languages? No problem!

You want to automatically create an expense to be reviewed in your platform of choice when an employee e-mails in a receipt? I got you!

You have a large datastore and want to index it so you can query it with natural language (“tell me all documents that were created between 2011 and 2014 that mention the company “Stellar Optics” in a negative way”)? Hold my beer.

“make me a realistic picture of an alligator in a puddle. The puddle should be in the middle of a floating land mass that is contained with a spherical dome. In the background it is sunset made of intense oranges and reds with the silhouette of flying birds.”

How do I get such magic?

AI Apps are springing up at a crazy rate – it’s the latest gold rush. One of my primary concerns when using the technology is how is my use of it being used to train it and other AI applications. On a professional level this question is even more pronounced as there are legal data requirements to consider. This is why I prefer staying within the confines of Microsoft infrastructure.

Everything you do with AI within your Microsoft tenant is private to you. All the data used and submitted to any aspect of AI remains yours and is not used to train any other models or applications. This means I can play around with AI, ask it questions about my data, get it to check over my code and to generate me content without having to worry about all the data involved in doing all that.

Microsoft offers some great products and services for consuming and using AI features and solutions, most of them are not free (but considering the security and governance they offer it’s usually a small price to pay!). Each could be its own article, but I will try to briefly go over them.

M365 Copilot – an AI agent that you can find in all your Office applications and an ever-growing number of other M365 applications.  The best thing about this use of AI is it has access to all the data that you have access to (e.g. is security aware) within your tenant. So, you can ask it to summarise your week and it will include information from files you have worked on, meetings you have had, e-mails you have received etc. You can even ask it to find an hour in an afternoon sometime next week where you and specified other colleagues are all available and it will quickly give you some options! Of course, it can also generate content in any app (Word, Excel, PowerPoint etc), you just need to be able to describe what you want, it’s amazing.

Copilot Studio – a quick way to produce chatbots and agents to handle specific tasks like helping people with the information contained in your website or a particular set or documents such as your HR policies. It can even handle complex interaction with external systems, the sky is (not even) the limit.

Azure Cognitive Services – a suite of services that developers can use to build AI solutions without having to deal with the underlying algorithms and models. Cognitive Services provide pre-built and pre-trained functionalities for common AI tasks. It includes some very handy services:

• Open AI Services – build your own copilot and generative AI applications with cutting-edge language and vision models.
• Search – be able to quiz and index your own data that is hosted outside of Office.
• Content Safety – automatically detect offensive or inappropriate content in images and text.
• Translator – translate any text, speech or audio into another language.
• Speech – use a pre-trained AI voice (or train your own!) to talk to users or generate audio using provided text or generated content.
• Vision – read text, analyse images, and detect faces with optical character recognition (OCR) and machine learning.
• Language – build conversational interfaces, summarize documents, and analyse text using prebuilt AI-powered features.
• Document Intelligence – apply advanced machine learning to extract text, key-value pairs, tables, and structures from documents.

How are organisations using AI?

Artificial intelligence is a game-changing technology that can help transform your businesses and gain a competitive edge. There are many ways this could manifest within your own company, one of the most common ways is by saving you time.

Easy AI wins for a business usually come by identifying processes and operations that can be improved by implementing one of the AI offerings mentioned above.  It is thinking about all the things AI can do (see, hear, understand language, identify things, summarise, etc.), and how quick it can do it, to figure out how you could piece these things together to help within your own organisational context.

You could allow employees to submit invoices and receipts for expenses via e-mail or a chat channel. Text could be extracted from the receipt and categorised, this data could then be written to your software that deals with expenses to be approved. No one had to key in any information.

How about you have your Teams meetings recorded, then have the audio analysed to get a transcript of what was said whilst recognising who the speaker as to create a set of minutes, which you could then have translated to several other languages along with generating a summary of the meeting. Then, to help with inclusivity, automatically take those summaries and minutes and convert them into audio for those who have visual impairments (and do this for every language).

Companies also have a lot of siloed data – maybe because it’s on-premise, or a lonely SQL server somewhere in the cloud, or a third party holds the data and you can only get to it via an API. There are various ways you can ingest and interact with that data and by using LLMs you can ask questions about it as if you were asking a person. Maybe you’d like to know “how many documents are there that reference our product HJ334 that were created between the 1^st April and 24^th June and that also contain website links to the product”. Or even “given our financial data what would be a realistic forecast for our IT department next year, explain your answer”.

Anything else?!?

Oh so much more! But I’ve already gone on longer than I wanted in this “small overview” of the subject.

AI is here – it’s not going anywhere. So best figure out how best to use it. Give me a shout or give us call at Prosperity 24/7 if you want to have a quick chat about how we can help you on that journey by being your guide and partner.

I’ll leave you with one last picture and leave you to interpret it.

“could you please make me a picture of what the world will look like in 10 years time given the advancement of AI and likely human actions. Be brutally honest.”

The post AI: Is it all just hype? appeared first on Prosperity 247.

Learn how the upcoming 2024 wave 1 release of Business Central will enable you to track and report greenhouse gas emissions with ease and accuracy with new sustainability ledgers and chart of sustainability accounts.

To extend this powerful functionality, Continia will introduce Continia Sustainability, which brings AI and automation to the collection of your ESG data directly from your supply chain and employee expense claims.

Discussion topics:

• What is the impact of sustainability reporting?
• What is best practice and how will it affect me?
• Why use Business Central, Copilot and Fabric for reporting.

Details:

Venue:  Space, Prosperity 24/7
Date: Thursday 14th March 2024
Time:  08:30 to 11:00
Refreshments will be provided.

The post Great Minds Series: Make real progress to Net Zero with Microsoft Dynamics Business Central appeared first on Prosperity 247.

When learning about Fabric, a few things grabbed my interest. My previous article goes into some initial lessons learned from migrating a traditional SQL Server data warehouse into Fabric warehouse. Shameless plug here.

This article explores what capacities are and how they drive the Fabric experience. To save you suffering from TL;DR, my key take outs are:

• A capacity is the way compute power and billing are represented in Microsoft Fabric – there are three different types, they work the same.
• Budgeting and controlling spend is straight forward as you can know the maximum a Fabric capacity will cost for any given month.
• Bursting and smoothing helps you to manage your workload.
• The capacity tries to keep background or scheduled jobs running.
• The Fabric Capacity Metrics app in Power BI shows very detailed information on capacity usage.
• In the event of an extreme overage, or a one-off big process, capacity can be increased on the fly, with no downtime, to allow for more throughput.

If that’s piqued your interest, then read on.

What are “capacities”?

Fabric capacities are the way that the compute power and billing is represented in Microsoft Fabric and Power BI Premium, aiming to give a simple and flexible foundation to the licensing model. They are measured in Capacity Unit Seconds (CUS) which represents how much throughput and processing power you have during a given period.

There are three types of capacity within Fabric:

Power BI premium capacities

These aren’t new and continue to be bought via Office 365. Since October 2023, premium capacities will stop being measured in v-cores (Voltage to the CPU Core) and instead measured in capacity units (CUs). This is a measurement change only, performance and costing hasn’t changed. The entry cost here is a Power BI P1 workspace which is about £4000 a month.

Fabric capacities

These are the new kid on the block, and they are purchased through Azure. They can be bought in the same sizes as power BI premium capacities but more interesting to us is that they can be bought in much smaller sizes. This allows a lower cost of entry to enterprise grade data analytics tools. The entry cost for an F2 is capped to £220 a month (more on this later).

The trial capacity

This doesn’t need to be purchased and allows us to test out the fabric experience with 64 CUs of throughput. This is a useful tool to get to test and play with Fabric tools. It can also be used as a method to run a real workload, which will help you understand what level of capacity is required before purchase (though 64 CUs is a lot).

The cost of Fabric capacities

A very welcome piece of Fabric news for budgeting and controlling spend is that you can know the maximum a Fabric capacity will cost for any given month. It has a single cost regardless of workload or tool (whereas estimating Azure Synapse Workspace costs requires at least a master’s degree!)
Other useful points to note on capacity cost are:

• Capacity is universal compute and all workloads within Fabric use this.
• Capacity usage is billed per minute of runtime, so you only pay for what you use.
• There is a fixed upper cost to the capacity if you ran it 24/7 for the entire month.

Pushing the boundaries

The other thing that I thought was: can I break it? Is this true?

I value knowing what happens when you push against the boundary of a platform. I believe that this level of understanding adds to our confidence when making recommendations to clients.

How will Fabric react? Are there overage andfair usage charges? Will Microsoft stop my workloads from running??

To answer this, I did the only reasonable thing: I set out to utterly exceed a realistic scenario:

• Purchased a F2 capacity SKU (the smallest available).
• Created 2190 parquet files containing roughly 9.5 billion rows of data.
• Created a Warehouse table of the same schema as the parquet files.
• Created pipeline job that would copy all the data from the files into the Warehouse table.

What happened?

The pipeline ran successfully, all the data loaded, as we expected, in 30 minutes.

How did it happen?

That is because capacities feature ‘bursting’. Microsoft will give you more capacity than purchased to get the work done. Additionally, Microsoft will ensure that any started jobs will finish. Any throttling will only happen on new/future queries and jobs.

But there’s no free dinner in the cloud. To pay back for this bursting, Microsoft have built a feature called ‘smoothing’. This is the process where burst of capacity is smoothed across the rest of the day whilst your capacity is in low or idle usage. I’ve come to think of it as borrowing compute power from future you. Instead of slowing down the job, Fabric lets you exceed it and pay it back as if the job took longer.

Bursting and smoothing are completely transparent to end users. It is fully managed by the workspace. I have had a couple of other experiences with this, and it works well. It is normal to have ETL jobs that run in the morning/out of hours. Knowing they can go a bit over capacity and still get the data in on time is reassuring.

Overage and throttling.

In short peaks of bursting (10 minutes) there is no throttling imposed. The table from Microsoft below shows how throttling gets stricter as the overage increases.

Source for the table above is Microsoft Docs: Understand your Fabric capacity throttling – Microsoft Fabric | Microsoft Learn.

The takeaway here is that the capacity tries to keep background or scheduled jobs running.

I went well into the “all requests are rejected” territory… So, my workspace was toast for a while.

How do I know how much capacity I am using

Microsoft have released a Fabric Capacity Metrics app in Power BI that shows very detailed information on capacity usage.

1. The capacity available on the current SKU.
2. How much capacity is being utilised and by what. Evidence that we are bursting over capacity and that is being smoothed over the next day.
3. Changes to the utilisation based on SKU change to F4 to reduce how much time smoothing/throttling take.

The metrics app also shows details on overages.

1. By going over capacity the workspace starts adding to the cumulative overage
2. As capacity continues to be used overage increases.
3. Capacity resized to F4 (doubling the size from F2) to get out of throttle purgatory quicker. Increased CUs means the cumulative overage can be paid quicker.
4. Once the capacity is in idle burndown starts. This could have been done quicker on a larger capacity.
5. Once burndown complete resize the capacity to F2.

The takeaway here is that in the event of an extreme overage, or a one-off big process, capacity can be increased to allow for more throughput. The change in resize is quick and reflects in fabric in minutes.

Note: Power BI capacities can have auto scaling enabled will automatically take care of this capacity resizing if it is enabled.

Overall, the experience with Fabric continues to impress clients and myself. Performance of the platform over analytical workloads is blazing fast and the costing around it transparent, reasonable, and flexible.

This article would not be possible without this great blog from Chris Novak. Chris gets extra points for a great gif explaining bursting/smoothing. If you want to know more, and how the new Fabric capacities compare to Power BI Premium capacity, check it out.

The post Powering Microsoft Fabric appeared first on Prosperity 247.

My recent travels with Microsoft Fabric (referred to as Fabric from here in) Microsoft’s new all-in-one analytics solution for the AI era, has been an interesting journey. Like most nerdy techies I love a new shiny tool in the toolbox, but I have been around long enough that I have a (un)healthy dose of cynicism.

Setting the scene

My current project is migrating a large data warehouse from on-premises SQL into a Fabric Warehouse. The workload is large enough (over 2.5TB) that running this in SQL Server is a challenging proposition. Moving this into an analytical toolset/platform should see a reduction in cost and an increase in performance.

The Microsoft documentation points to this being a smooth process as Fabric warehouses leverage the TSQL language for a ‘lift and shift’ approach. Broadly speaking this has been the case, resulting in a straightforward and relatively quick migration:

• SSIS packages translated into Data Factory Pipelines and Data Flow Gen 2.
• SQL tables and stored procedures kept as is (minor changes to data types and temp tables).
• Migration of data via CSV/Parquet exports.
• Approximately 2.5 terabytes of data. Mostly in one fact table.

The project’s objectives are:

• Migrate the warehouse to Fabric with little or no impact to downstream reports/processes.
• Reduce operational costs by taking advantage of cloud storage/compute.
• Improve performance and reliability of ETL and warehouse.

Why Warehouse over Lakehouse?

The first question we asked was: which approach is best for this project, Warehouse or Lakehouse. We chose Warehouse because it uses TSQL as the primary language for working with the Warehouse,  making it easier for the in-house team to adopt and maintain the final solution.

Ultimately, the decision is about what language the team developing/maintaining the solution has proficiency or comfort with:

• If you have data engineers with TSQL experience? Lean towards Warehouse.
• If you have data analysts/scientists with Spark experience? Lean towards Lakehouse.

The choice shouldn’t get in the way though, as all Fabric tools can read from Warehouse/Lakehouse thanks to using the same underlying storage format (Delta Lake Parquet). So, your data scientists can use Spark on a Warehouse. Bonus feature here is that it doesn’t take any effort to get these tools to work together, they ‘just do’.

Is this expensive?

Cost has been the biggest draw for me to Fabric. We have been using Azure Synapse Workspace and while it’s a fantastic tool, it has always seemed too expensive for smaller clients.

Fabric is costed via capacity like Power BI; however, it comes in some very small SKUs which is going to let us bring the same enterprise ready tools to our smaller clients. The smallest SKU costs £200 per month and that is if it is running 24/7.

Things to get used to

At the core, Fabric Warehouse has a different engine to SQL Server which give us ‘normal’ SQL developers a learning curve (at least at the time of writing):

• No temp tables, indexes, computed columns,
• Primary/foreign keys not enforced.
• Some data type differences, no Unicode support.

Knowing that the storage is Delta Lake Parquet, and processing is happening in parallel these limitations do make sense and haven’t hindered us.

The other challenge was getting files into OneLake to then be processed by the pipelines. OneLake is based on Azure Data Lake Storage Gen 2 which means anything that it can talk to ADLS Gen 2 which can talk to OneLake. In practicality, there are some subtle URL differences that mean most tools can’t yet handle OneLake. Lower-level tools (AzCopy.exe, Azure Storage SDK) have no issue though so we are still able to upload files. In time, Power Automate, Logic Apps, SSIS, etc will catch up.

Takeaways so far

Our experience has shown that SSIS and SQL workloads can migrate smoothly to Fabric and enabled some efficiencies due to additional features.

Creation of tables, views, and stored procedures in Warehouse was straightforward due to using similar definition of from SQL Server.

Knowledge sharing with the in-house BI team has been smooth due to using familiar TSQL language. This isn’t finished yet, but so far so good.

Fabric has a very cohesive/integrated working environment. The interface can be switched into different personas depending on what the end user is doing: data engineering, data science, reporting, etc.

The Fabric Workspace can be seen through different ‘personas’ to tailor the experience.

Fabric has higher performance compared to source SQL Server. Showing a performance increase of 20% to 45%.

Fabric has only recently come out of preview. Our research and work so far has shown it is ready for prime time. It is built upon pre-existing foundations (Azure Synapse Workspace and Power BI) with enough new features, and exciting future roadmap, that we are happy to recommend it for current and future customers. Conversely, Azure Synapse Workspace seems to be the poor cousin in this by comparison.

Migration of data has also been smooth with Fabric providing multiple options to meet your requirements. We chose export/import through files to ensure timing and load on the production warehouse was kept to the minimum.

• Pull in with Data Factory or Data Flows.
• Push in with SSIS.
• Push in with Synapse Link for SQL.
• Export/import processes via CSV/Excel/Parquet files.

There is very good support for programmatic access to export/import/upload of data into Fabric. We didn’t use this extensively but did perform research to understand the ‘art of the possible’.

Fabric has recently released ‘No Copy Table Clone’ which is going to be an amazing for testing. Allowing a table to be cloned near instantaneously and updates to be made to it without affecting the original. Testing the impact of changes on large, multi-million row, tables just became a lot easier/safer.

The post Weaving data analytics with Microsoft Fabric appeared first on Prosperity 247.

Many of the problems encountered by businesses are a result of a long line of investment in separate pieces of software over a number of years which are now hindering more than helping.

Employees are bogged down by manual and inefficient processes which leads to errors. Employee satisfaction is lower and turnover higher. The business experiences increased costs and reduced productivity as a result. So how do organisations overcome this?

This is where ERP comes in.  Enterprise Resource Planning or ERP solutions allows businesses to adapt faster, work smarter and perform better. It helps businesses overcome these challenges and make their vision a reality by connecting the dots and improving effectiveness.  These solutions can give businesses a complete view of their activity and performance, acting as a central hub for a variety of departments to access, collaborate and share information.

By connecting areas like finance, HR, sales, marketing, customer service and operations in a single solution, organisations can adapt more easily to disruption, rapid change and transformational business growth.

Prosperity 24/7’s specialist ERP team works closely with Microsoft to deliver their ERP solution, Microsoft Dynamics 365 Business Central to our clients.

Voted the Best ERP system in 2023 by Forbes Advisor, Microsoft Dynamics 365 Business Central is a cloud-based solution that uniquely offers the breadth and security of the Microsoft cloud, while continuing to offer different modules and extensions, so organisations can start with what they need today and adapt as they grow.

Not only is it a comprehensive business wide solution that sits at the heart of the business but it integrates with the familiar office environment of Microsoft 365.

Its advanced automation capabilities, robust reporting and analytics, and cloud-based delivery model make it an ideal solution for streamlining and optimising business processes, to help drive growth and profitability.

By implementing Business Central, our clients can confidently optimise business processes and unlock the insights needed to adapt faster, work smarter, and perform better.

Find out more about Microsoft Dynamics 365 Business Central.

Source: ¹ IDC ² Microsoft annual work trend index ³ Gartner AFP

The post Why do you need ERP at the heart of your business? appeared first on Prosperity 247.

Hosted by Prosperity 24/7’s Head of Data and Integration, Fabio Hepworth and Head of ERP, Phil Berrill, this Round Table event is open to IT professionals and business leaders. Attendees will hear from industry experts who will demonstrate the full potential of Dynamics 365 and the Power Platform. They will learn how to leverage Co-pilot AI, a cutting-edge feature that brings intelligent automation to your business processes. Our experts will show you how this powerful tool can streamline operations, boost productivity, and drive growth.

We’ll share valuable insights gained from years of experience working with Dynamics 365 and Power Platform, discuss best practices that can help you make the most out of these powerful tools and avoid common mistakes that can hinder your success.

We will showcase the end-to-end data journey. From a customer purchasing a product (Power Pages), to the information being visible to the sales team (Dynamics 365 Sales), the invoice flowing through to Finance for payment (Business Central) and data being ready for analysis and reporting (Microsoft Fabric).

Discussion topics:

1. Power Pages & Azure B2C: Securely empowering your customers to view and interact with their data.
2. Dynamics 365 & Power Apps: Modern customer engagement applications to streamline and automate your business processes.
3. Business Central: Integrated cloud-based ERP solution to manage financial, supply chain, and operations.
4. Microsoft Fabric & Power BI: Curate and democratise your data using the latest tools in Data Engineering and Data Science.

Location:  ‘Space’ Prosperity 24/7’s Headquarters, Quayside, St Helier Waterfront

Dates:  There is a choice of sessions on the following days:

• Tuesday 12th September from 12:30 to 14:00
• Wednesday 13th September from 09:00 to 10:30

Refreshments will be provided.

Unleash the potential of co-pilot AI in your business

Learn how to leverage Co-pilot AI, a cutting-edge feature that brings intelligent automation to your business processes. Our experts will show you how this powerful tool can streamline operations, boost productivity, and drive growth.

Learn from best practices and avoid common pitfalls

At our showcase, we’ll share valuable insights gained from years of experience working with Dynamics 365 and Power Platform. Discover best practices that can help you make the most out of these powerful tools and avoid common mistakes that can hinder your success.

Book Here

The post Great Minds Series: Discover the Power of Microsoft Dynamics: 12/13 September appeared first on Prosperity 247.

With a shared vision of enabling organisations to thrive and prosper in an ever-evolving business landscape, Prosperity 24/7 will continue to work alongside the IoD internationally, driving further operational improvements across the organisation using Microsoft’s Power Platform.

For the IoD, the platform offers operational automation as well as enhanced, integrated and automated sales functionality for opportunity management, leveraging AI-driven, relationship insights, to optimise the performance not only for the sales and membership team but provide a greatly improved experience for members.

With the core systems replacement complete, the 120 year old organisation now has a platform that can drive innovation forward and implement further innovation to help Members. Digital transformation will not only streamline its operations, but also enhance the IoD’s ability to support and lead the UK’s business community in the modern era.

Jon Geldart, IoD Director General, commented on the project,

Our journey of digital transformation is an essential component of the long-term success of the IoD. We will have the ability to do amazing things – swiftly and effectively – and a strong foundation to build on as we continue to drive innovation.

We have had an incredible journey, helping the IoD to rationalise, re-imagine and ultimately, empower their phenomenal colleagues across the UK and beyond with new ways of working, to ultimately enhance the Members’ experience.” said Chris Clark, CEO of Prosperity 24/7. By leveraging our cutting-edge technology solutions, the IoD will be able to drive organisational efficiency, elevate member engagement, and stay ahead in an increasingly competitive environment.

The post Prosperity 24/7 empowers the Institute of Directors through digital transformation appeared first on Prosperity 247.