Data Archives - Flyte

Why Microsoft Dataverse Is a Practical Data Foundation for Scalable Power Platform Deployments

Flyte Team — Thu, 02 Apr 2026 14:30:08 +0000

Many challenges in Power Platform environments are not caused by poorly designed apps, but by limitations in the underlying data layer. As environments mature, the data storage choice made early on can significantly influence how well solutions scale, integrate, and remain maintainable.

For many organisations, SharePoint is the initial data store for Power Platform solutions. This is a reasonable starting point. SharePoint is widely licensed, familiar to users, and well suited to collaboration scenarios. Lists can be created quickly, basic apps can be built rapidly, and simple workflows can automate everyday tasks. In early stages, this approach often delivers visible efficiency improvements with minimal setup effort.

Over time, however, usage patterns tend to evolve.

Individual lists are duplicated to meet slightly different requirements. Columns are renamed or altered. Multiple teams create similar datasets because they need independent control over their processes. Reporting becomes more difficult as data structures diverge, and bringing information together requires additional preparation. These issues often emerge incrementally rather than all at once, making them easy to overlook until a more complex requirement exposes them.

This article outlines where SharePoint-based storage commonly reaches its limits in Power Platform environments, what Microsoft Dataverse provides as a data foundation, and what organisations typically encounter when moving between the two.

When SharePoint Reaches Its Practical Limits

SharePoint performs well as a document management and collaboration platform, and it can support simple lists effectively. Challenges tend to arise when SharePoint lists are used as operational data stores for line-of-business processes.

Common indicators include:

Related data spread across multiple unconnected lists
Business rules implemented separately in each app or flow
Reporting data that requires reconciliation or manual adjustment
Permission structures that are hard to align with organisational roles

These situations usually develop gradually. They become more visible when organisations attempt to consolidate data, apply consistent governance, or expand solutions across departments.

For example, one finance team we worked with maintained several SharePoint lists that had evolved independently over time. Each supported a valid local requirement. The limitation only became clear when leadership requested a consolidated report. Producing that report required extensive data alignment because similar fields had been implemented differently across lists. After moving the data into Dataverse with a unified schema, the same reporting requirement became straightforward and repeatable.

This pattern is a common reason organisations begin exploring Dataverse as their Power Platform environments grow.

What Microsoft Dataverse Provides

Dataverse is Microsoft’s cloud-based data platform that underpins Dynamics 365 and integrates directly with the Power Platform. It provides a managed data layer that is independent of individual apps and is designed to support relational data, security, and governance requirements typical of business systems.

Its value is not limited to data storage. It also provides functionality that is applied consistently wherever the data is used.

Data-level security

Dataverse supports role-based security at the table, row, and column levels. This allows organisations to control access to specific records and fields based on user roles rather than relying on list-level permissions. This is particularly relevant in scenarios where users should access different subsets of the same data without duplicating datasets.

Centralised business rules

Validation rules, required fields, and calculated columns can be defined directly in the data model. These rules are enforced regardless of whether data is entered through a Power App, an automation, or an integration. This reduces the need to reimplement logic in multiple places and helps maintain consistency as solutions expand.

Built-in audit history

Dataverse automatically tracks changes to records, including who changed what and when. This capability supports operational oversight and compliance requirements without requiring additional custom logging solutions.

Together, these features support more predictable behaviour across apps, automations, and reports. Microsoft’s own Total Economic Impact studies have linked Power Platform adoption to significant productivity and cost benefits, particularly where solutions share a common, well-structured data layer rather than operating independently.

Indicators That Dataverse May Be Appropriate

Not every Power Platform environment needs Dataverse immediately. However, organisations often consider it when one or more of the following conditions apply:

Reporting requires manual intervention
If datasets must be cleaned, merged, or adjusted before reports can be relied on, this often points to structural data issues.
Business logic is implemented in multiple places
When changing a rule requires modifying several apps or flows, maintaining consistency becomes increasingly difficult.
Access control is becoming complex
If users cannot be granted appropriate access without being over-privileged, the permission model may no longer be suitable for the data.

When these conditions are present, the cost of maintaining the existing approach can exceed the effort required to introduce a more structured data foundation.

What a Dataverse Migration Typically Involves

A common concern is that migrating from SharePoint or Excel to Dataverse will be disruptive. In practice, the technical migration is usually less challenging than expected. Microsoft provides tools to move data, and the primary effort lies in designing the data model before migration.

That design phase involves reviewing existing datasets, identifying duplication, aligning field definitions, and establishing clear relationships. Many organisations find this process valuable in its own right, as it surfaces inconsistencies that have accumulated over time.

In one professional services organisation, multiple departments had independently built request-tracking solutions using SharePoint. Consolidating this information for reporting required regular manual effort. After defining a shared Dataverse model and migrating the data, teams were able to work from a single dataset, and reporting became automated rather than routine maintenance.

Migration is not only a technical step. It is often the point where a Power Platform environment shifts from a collection of isolated solutions to a more integrated and scalable platform.

Enabling Broader Platform Capabilities

Once data is centralised in Dataverse, other platform features become easier to implement consistently. Power BI reports can rely on a single source of truth. Power Automate flows can operate across datasets without complex transformations. Copilot and Power Pages can interact with live business data while respecting configured security boundaries.

These capabilities are difficult to achieve reliably when data is fragmented across independent lists and files.

Using the Platform More Effectively

Organisations that see the greatest long-term value from the Power Platform are often those that focus on data foundations as well as app development. In many cases, Dataverse is already available through existing Microsoft licensing.

The decision is therefore less about acquiring new tools and more about using the platform’s capabilities in a way that supports growth and governance over time.

A well-structured data layer does not eliminate the need for good app design, but it significantly reduces the effort required to maintain, extend, and report on solutions as adoption increases. Flyte supports organisations at different stages of this evolution, from early assessment through to migration and optimisation, depending on current needs.

Next Steps for Power Platform Growth

As Power Platform adoption increases, data design decisions made early on begin to have a measurable impact on cost, delivery speed, and confidence in reporting. Organisations often reach a point where incremental fixes no longer address underlying data issues, and a more structured approach is required.

A sensible next step is to review how data is currently stored, how many systems or lists hold similar information, and where duplication or manual work has become routine. For many organisations, starting with a single process or dataset and assessing whether Dataverse is a better fit provides clarity without requiring wholesale change. This kind of assessment typically focuses on data structure, security requirements, reporting needs, and long-term maintainability rather than rebuilding for its own sake.

Flyte works with organisations to carry out these evaluations, map existing SharePoint and Power Platform solutions to scalable data models, and implement Dataverse where it meaningfully reduces complexity and risk. The aim is not to replace working solutions unnecessarily, but to ensure the platform you are relying on today can continue to support the business as demands increase. Get in touch to see how Flyte can support Power Platform growth within your Organisation.

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Ethical and Safe AI Development with Microsoft Azure AI Foundry

Flyte Team — Thu, 28 Aug 2025 13:18:57 +0000

In the swiftly advancing realm of artificial intelligence (AI), ensuring ethical and safe development practices is paramount. Microsoft Azure AI Foundry stands at the forefront of this mission, offering a robust platform for creating AI solutions that prioritise ethical considerations and safety. This blog post delves into the principles and practices that guide ethical and safe AI development using Microsoft Azure AI Foundry.

Ethical AI development is crucial for building trust and ensuring that AI technologies benefit society as a whole. It involves creating AI systems that are fair, transparent, and accountable. Ethical AI aims to prevent biases, protect privacy, and ensure that AI systems are used responsibly.

Microsoft Azure AI Foundry: A Commitment to Ethics and Safety

Microsoft Azure AI Foundry is designed with a strong commitment to ethical and safe AI development. Here are some key aspects that highlight this commitment:

1. Fairness and Bias Mitigation

Bias Detection and Mitigation Tools: Azure AI Foundry provides tools to detect and mitigate biases in AI models. These tools help developers identify and address potential biases in data and algorithms, ensuring fair outcomes.

Inclusive Datasets: The platform encourages the use of diverse and representative datasets to train AI models, reducing the risk of biased results.

2. Transparency and Explainability

Documentation and Reporting: Comprehensive documentation and reporting tools are available to ensure transparency in AI development processes.

3. Privacy and Security

Data Privacy: Azure AI Foundry prioritises data privacy by implementing robust security measures and compliance with data protection regulations. This ensures that sensitive information is handled responsibly.

Secure Development Practices: The platform promotes secure coding practices and provides tools to identify and mitigate security vulnerabilities in AI applications.

4. Accountability and Governance

Ethical Guidelines: Microsoft provides ethical guidelines and best practices for AI development, helping developers align their projects with ethical standards.

Governance Frameworks: Azure AI Foundry supports governance frameworks that enable organisations to monitor and manage AI systems effectively, ensuring accountability throughout the AI lifecycle.

Real-World Applications

The principles of ethical and safe AI development are not just theoretical; they have practical applications across various industries. Here are a few examples:

Healthcare: AI models developed using Azure AI Foundry can assist in diagnosing diseases while ensuring patient data privacy and reducing biases in medical research.

Finance: Financial institutions can leverage AI to detect fraud and manage risks, with transparency and fairness built into the models.

Education: AI-powered educational tools can provide personalised learning experiences, ensuring that all students receive fair and unbiased support.

Conclusion

Ethical and safe AI development is essential for building a future where AI technologies are trusted and beneficial to all. Microsoft Azure AI Foundry provides a comprehensive platform that empowers developers to create AI solutions with ethics and safety at their core. By prioritising fairness, transparency, privacy, and accountability, Azure AI Foundry is leading the way in responsible AI development.

As we continue to innovate and explore the possibilities of AI, it is our collective responsibility to ensure that these technologies are developed and deployed ethically and safely. With Microsoft Azure AI Foundry, we have the tools and frameworks to make this vision a reality.

Leverage AI innovations for ethical growth

At Flyte, we understand that successful AI integration for UK businesses goes hand-in-hand with responsible practice. As Microsoft 365 and Power Platform specialists, we see first-hand the transformative power of AI tools like Azure AI Foundry and Microsoft Copilot. Our approach is rooted in helping you leverage these innovations not just for efficiency, but for ethical growth.

We assist UK businesses in:

Strategic AI Implementation: Guiding you in identifying appropriate AI use cases that align with your ethical framework.
Data Governance & Security: Ensuring your data strategies support responsible AI development, adhering to GDPR and other UK data protection standards.
Custom Solution Development: Building AI-powered applications and workflows with fairness, transparency, and accountability designed into their core.
Training & Best Practices: Empowering your teams with the knowledge and tools to develop and deploy AI responsibly.

The future of UK business will be significantly shaped by AI. By embracing responsible AI principles today, businesses can not only mitigate risks but also forge a path of sustainable innovation, build enduring trust with their stakeholders, and contribute positively to society. This isn’t just good ethics; it’s good business.

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Unleash Your Potential: How the Microsoft Power Platform is Redefining UK Engineering

Flyte Team — Fri, 15 Aug 2025 14:27:51 +0000

At Flyte, we believe in a simple truth: technology should empower people, not hinder them. For the UK’s forward-thinking engineering firms, the path to greater efficiency and innovation is no longer a complex coding challenge. It’s a creative process powered by the Microsoft Power Platform. Our experienced development team work with Engineering firms to design and implement these effective solutions, transforming business challenges into opportunities for growth.

Microsoft Power Platform – a modern workplace framework

The Power Platform is not just a set of tools; it’s a modern workplace framework for unlocking the potential within your organisation:

PowerApps: Build Smarter, Faster. We help you move beyond generic, off-the-shelf software. PowerApps allows us to rapidly build bespoke applications tailored to your exact needs. Whether it’s a mobile app for on-site quality checks or a system to manage supplier relationships, we help you create intuitive solutions that digitise processes and ensure data integrity from the moment it’s captured.

Power Automate: Streamline Every Process. Time is a valuable resource. With Power Automate, we identify and automate the tedious, repetitive tasks that drain your team’s energy. From automating invoice approvals to streamlining project sign-offs, our solutions free up your most skilled people to focus on the high-value work that truly drives your business forward.

Power BI: Actionable Insights at a Glance. You have a mountain of data; we help you turn it into a powerful asset. Power BI allows us to consolidate data from various sources and create interactive dashboards that provide real-time insights. Imagine a single dashboard where you can track project profitability, monitor resource utilisation, and predict key outcomes—all in one place. That’s the power of effective data visualisation.

Why UK Engineering Firms Trust the Power Platform

The move towards low-code innovation is gaining significant momentum in the UK engineering sector. Major firms like WGM Engineering (Case Study), Balfour Beatty (source) and AECOM (source) are already leading the charge, proving the platform’s ability to deliver tangible results. This is part of a broader trend; a Microsoft report highlights the potential for a £78 billion boost to the UK economy from SME AI adoption (source).

Here’s why we believe the Power Platform is the right choice for your business:

Accelerated Innovation: Forget lengthy, expensive development cycles. The platform’s low-code nature means we can design and deploy solutions in weeks, not months. A Forrester study on low-code development found projects can be completed up to 20 times faster than with traditional methods (source).

Increased Productivity & Efficiency: Our solutions don’t just automate tasks; they optimise workflows. This strategic efficiency allows your team to achieve more with less, improving overall productivity and ultimately boosting your bottom line.

Seamless Integration: We build solutions that integrate flawlessly with your existing Microsoft ecosystem, including Teams and SharePoint. This eliminates data silos, promotes better collaboration, and creates a single, unified source of truth for your entire team.

Cost-Effective Solutions: By leveraging your existing Microsoft licences and reducing the need for traditional, custom-built software, the Power Platform offers a highly cost-effective route to digital transformation.

The Microsoft Power Platform is a strategic asset for any UK engineering firm aiming to thrive in today’s competitive landscape. It’s about more than just technology; it’s about empowering your people and optimising your operations for the future.

Ready to see how Flyte can transform your business? Contact us to work on your next project.

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Copilot vs ChatGPT: Which is Better for Your UK Business?

Flyte Team — Fri, 01 Aug 2025 14:01:17 +0000

The AI arms race is well and truly underway- and for UK businesses, the question isn’t whether to adopt AI, but which tools to adopt. Two names dominate the conversation: Microsoft Copilot and ChatGPT by OpenAI.

Both are powerful, both promise to supercharge productivity, and both are evolving rapidly. But which one is right for your business? The answer depends on your goals, workflows, and how ready your teams are to embrace AI.

At Flyte, we help UK businesses harness cloud and AI technologies safely and effectively. In this post, we’ll break down the key differences between Copilot and ChatGPT- so you can make an informed decision.

What Is Microsoft Copilot?

Copilot is Microsoft’s AI assistant integrated into the Microsoft 365 ecosystem- Word, Excel, PowerPoint, Outlook, Teams, and more. It’s designed to work inside the tools your teams already use.

Key features:

Generate content in Word or slides in PowerPoint.
Analyse and visualise data in Excel.
Draft emails and summaries in Outlook and Teams.
Pull data from your internal files and documents using Microsoft Graph.

Ideal for:

Businesses deeply invested in Microsoft 365 looking to boost team productivity without changing platforms.

What Is ChatGPT?

ChatGPT is a conversational AI developed by OpenAI. It’s platform-agnostic, meaning it doesn’t require any specific software suite. Instead, it offers a powerful chat interface- and with ChatGPT Plus or Pro plans, access to the GPT-4.5 or GPT-4o model for even more advanced reasoning.

Key features:

Natural language Q&A and idea generation.
Code assistance and data analysis via the Code Interpreter.
Custom GPTs that can be trained on your business knowledge base.
Integration via API or browser extensions for bespoke workflows.

Ideal for:

Innovative teams or developers looking to build AI-enhanced workflows, create content, or automate complex tasks.

Copilot vs ChatGPT: Key Differences

Feature	Microsoft Copilot	ChatGPT
Integration	Deeply integrated with Microsoft 365	Platform-independent
Ease of Use	Familiar UI, low learning curve	Conversational, requires exploration
Customisation	Limited, based on Microsoft data ecosystem	High (Custom GPTs, API, plugins)
Data Access	Internal data via Microsoft Graph	External data via uploads or integrations
Security & Compliance	Enterprise-grade (in Microsoft environment)	High, but depends on implementation
Pricing	Added cost on top of Microsoft 365	Free tier, Plus and Pro plans available

Which Should Your Business Choose?

Choose Microsoft Copilot if:

You’re already embedded in the Microsoft ecosystem.
Your goal is to enhance day-to-day productivity with minimal disruption.
You need enterprise-ready compliance and security out of the box.

Choose ChatGPT if:

You’re experimenting with AI-driven innovation, coding, or automation.
You want to train custom assistants or integrate with non-Microsoft systems.
You’re seeking flexibility and cutting-edge reasoning power.

Or- Why Not Both?

The truth is, these tools aren’t mutually exclusive. Many UK businesses are deploying Copilot for office productivity and ChatGPT for innovation, development, and AI workflows. The key is to manage access, governance, and training so teams know when and how to use each effectively.

At Flyte, we work with UK businesses to implement secure, scalable AI solutions—whether that means configuring Microsoft Copilot, training a custom GPT, or deploying hybrid workflows that bring out the best in both.

Ready to Embrace AI?

If you’re unsure how to get started or want help comparing the ROI of Copilot vs ChatGPT in your organisation– let’s talk.

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5 Benefits of Carrying Out a Data Discovery

Flyte — Tue, 02 May 2023 09:04:20 +0000

Data is one of the most valuable resources that any organisation has, as when utilised correctly, it can be used to greatly improve organisational performance. However, managing high volumes of data is a time-consuming task that many organisations simply do not have the resources or knowledge to correctly handle. In fact, 95% of organisations cite that the need to manage unstructured data is a problem. This can result in missed opportunities, data gaps, and failure to comply with data regulations.

To ensure they are getting the most out of their data, many organisations undergo a data discovery. Data discovery is the process of carrying out a deep dive into your organisation’s data to gain valuable insights. This can be carried out as a standalone task, or as the first step in a digital transformation project. The data discovery process involves working closely with key stakeholders to identify existing challenges and set objectives, before carrying out an audit of your existing technology and systems. Once the audit has been completed, a report summarising findings and presenting recommendations and a roadmap will be provided.

Key benefits of carrying out a data discovery include:

Improved understanding of data – when you are manually managing large amounts of data it can be difficult to understand exactly what data you have, or what data you need. During the data discovery process, your current technology and systems will be audited, with key findings presented to your team in a simplified report, providing you with valuable insights
Identify opportunities and weaknesses – as well as presenting findings, recommendations will also be provided on how your organisation can improve performance. This will include any opportunities that your team can take advantage of, and any weaknesses that your team should be aware of. Alongside the recommendations, a recommended roadmap will be shared that outlines the steps that should be taken to carry out the changes successfully
Compliance with data regulations – there are many laws in place regarding the storage and use of data, including the Data Protection Act and GDPR. When you have one employee or a small team manually managing your data it can be impossible to ensure that you are fully compliant. Failure to comply with these laws can result in serious consequences, including fines, legal action, and a bad reputation. Carrying out a data discovery will allow any potential breaches to be identified, with a plan to rectify them
Improved decision making – unless you are a trained data analyst, understanding and analysing large volumes of data can be difficult. When carrying out a data discovery, valuable insights can be gained from the data, regarding areas including customer behaviour or employee performance. These insights can then be used to improve the decision-making process, as well-informed, data-backed decisions are more likely to create positive, effective results
Increased productivity and efficiency – during a data discovery, recommendations are provided, that if followed, increase productivity and efficiency within your organisation. A clear roadmap will be provided that will clearly outline the steps that must be taken to achieve this

The Cloud Cover IT Digital Transformation team has extensive experience of carrying out successful data discoveries. To learn more about our data discovery process, or to book a meeting, click here.

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4 Companies That Have Successfully Implemented a Data-Empowered Marketing Strategy

Flyte — Thu, 20 Oct 2022 08:52:27 +0000

The age of Digital Transformation is over. The last great shift was about “going digital”. The next great shift is about “getting smart”.

AI, machine learning, and smart automation will drive 70% of GDP growth over the next decade. In this new “Machine Economy“, data will continue to increase in both volume and value, and many data teams are already struggling to keep up. But where do marketing teams fit into all of this?

Well, this exploding amount of data can actually bode well for marketers.

By leveraging important, meaningful data, marketing teams can get to know their audience better, personalise customers’ experience, and ultimately, meet the goals that are going to increase ROI. There is no doubt that data can be used to put together an effective brand strategy that fuels the overall growth of the brand.

That all sounds great, right? But where is the proof that these data-empowered strategies work?

EasyJet

To celebrate its 20^th birthday, the travel company took personalisation to a whole new level. In one campaign, EasyJet used the travel history of each of its customers to create a personalised experience. They used historical customer data to do this, for example, looking at when they first travelled with the airline to make predictions about where they were likely to go next. They used highly personalised emails in the campaign, and curated copy based on 28 data sources. The result? The open rates from this campaign were 100% more than their typical newsletters, along with a 25% higher CTR. Impressive, right?

Sephora

The beauty giant is all about personalisation – their website is set up to show the customer what they want. From product discovery tools to customised loyalty rewards, it’s no wonder Sephora is so successful. Their homepage displays recommended products to each customer, and the entire selection uses data based on their past purchases and browsing activity. In addition, they have a section on the homepage that shows its newly released products in the “new for you” feed of recommendations, personalising the experience even further. These are just a few of the data-empowered marketing strategies that have led to its success.

Under Armour

Under Armour is another brand that uses data at the core of its marketing campaigns. They take data from the their own app and fitness community to tap into customers’ behaviours and create their marketing strategies accordingly. Their online fitness community has over 200 million users, with an insane amount of data available – Under Armour gathers insights from users who have purchased health-tracking devices, as well as their activity in fitness apps, such as MyFitnessPal. So, when it comes to curating campaigns, the brand can, yet again, personalise the user experience – they use the data available to determine how often they should message the customer, at what times, and what products they should offer. Meaning that customer engagement is higher, as is the ROI.

Netflix

And finally, of course, we have Netflix. The streaming service uses data processing software, as well as traditional BI tools, and open-source solutions, to gather and store information about their consumers. This helps the brand focus on what to promote to specific viewers – most notably the “Recommended for You” section. As a result, the service sees a high engagement rate with “Netflix Original” series and films – the service actually renews 93% of its original series! This directly contributes to increased revenue, viewership, and of course engagement.

What are you waiting for?

When used correctly, marketing analytics are an extremely useful resource that helps maximise your ROI, improves the performance of your campaigns AND results in happier customers. Of course, implementing this is easier said than done. Knowing what data to pull together, investigating what it’s telling you, and then drawing out actionable insights from it takes time and a lot of effort, if you do it manually.

Here at Cloud Cover IT, we can help make this process more efficient and productive by implementing TimeXtender. TimeXtender is a data estate builder that fully automates the data management process. That means no more time wasted manually collating high volumes of data from different sources and creating overly complicated reports. Instead, you can focus on using your newfound understanding of your customers to build meaningful campaigns that generate results.

If you’d like to learn more about TimeXtender, please email sales@cloudcoverit.co.uk .

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