Copilot for Excel: Changing How We Manage Financial Data

1. Automatic Data Insights and Analysis
One of Copilot’s standout features in Excel is its ability to automatically extract insights from complex data.

• Summarise Large Datasets
  It identifies key trends and patterns, helping analysts spot risks or opportunities without manually reviewing the data.
• Automate Complex Calculations and Models
  With a simple instruction like “Analyse this year’s sales data and find areas for growth” Copilot delivers actionable insights in seconds.

For example, investment firms managing large portfolios can use Copilot to quickly run scenario analyses using high-level instructions. This is especially useful in risk management, where understanding portfolio volatility under different market conditions is important.

• Predict Sales Trends
• Identify Future Cash Flow Challenges
• Provide “What-If” Analyses under different market scenarios

Users no longer need to depend solely on manual models or limited built-in functions.

For instance, a financial adviser can quickly forecast a client’s portfolio performance over several years by having Copilot analyse market data and past performance. Copilot automates complex forecasting tasks, increasing accuracy by up to 25%.

Imagine a financial analyst who needs to present a quarterly performance report. With Copilot, they can simply ask: “Create a bar chart showing revenue growth for the last three quarters and highlight any anomalies.” Copilot will instantly generate the chart, ready to present.

Copilot in Word and PowerPoint: Making Reports and Presentations Simple

1. Creating First Drafts of Reports
With Copilot in Word, starting a report doesn’t mean starting from scratch. Financial professionals can give instructions like “Write a financial summary based on this data…” and Copilot will produce a comprehensive report with charts, tables, and appropriate financial terms.

For example, compliance officers can use Copilot to draft quarterly risk assessments based on recent performance data and regulatory requirements, saving significant time and effort.

3. Building Engaging Presentations
Creating PowerPoint presentations can be time-consuming, especially when they need detailed financial explanations and multiple data points. Copilot helps by automatically generating slides based on inputs from Excel or Word. It can create presentations on financial forecasts, revenue growth models, or investment analyses with the appropriate visuals included.

Real-World Example: Investment Portfolio Analysis

• Instant Data Summaries:
  The analyst inputs data into Excel, and Copilot summarises trends, risks, and performance highlights.
• Quick Forecasting:
  Copilot predicts potential outcomes for the next quarter based on market trends.
• Effortless Presentation Creation:
  The analyst asks Copilot in PowerPoint to generate a presentation using the data and forecasts, creating slides with key insights and recommendations in minutes.

This streamlined process allows analysts to focus on more valuable tasks, like advising clients or improving investment strategies, instead of spending time compiling reports manually.

Enhancing Efficiency and Productivity

• Save Time:
  Copilot’s quick data analysis allows teams to focus on strategic decisions.
• Improve Accuracy:
  Advanced AI features reduce human error, leading to more reliable financial models and forecasts.
• Enhance Collaboration:
  With Copilot working across Microsoft 365 apps, teams can collaborate more effectively on projects, reports, and presentations.

Embracing the Future with Microsoft Copilot

Microsoft Copilot offers financial services a powerful tool to improve efficiency and accuracy. By embracing AI technology, financial institutions can enhance their operations and better serve their clients.

We invite you to explore the transformative potential of Microsoft Copilot today. Take the first step towards revolutionizing your financial services by integrating Copilot into your workflow. Empower your team with the tools they need to achieve greater success and deliver unparalleled value to your clients.

If you’re interested in exploring the transformative potential of Microsoft Copilot for your financial services, contact us today! We’ll help you integrate this powerful AI tool into your workflow and unlock new levels of success.

• Microsoft 365 Copilot Overview. Microsoft. Available at: microsoft.com/en-us/microsoft-365/business/ai-powered-productivity
• Financial Services Industry Benefits of Copilot Integration. Microsoft. Available at: microsoft.com/en-us/microsoft-365/enterprise/financial-services
• AI in Financial Forecasting: A Forrester Report. Forrester. Available at: www.forrester.com/report/AI-in-Forecasting

This is where data engineering becomes indispensable. By systematically organising, processing, and refining raw data, data engineering unlocks its potential, converting it into valuable insights that can inform strategic actions. This process involves a blend of technical expertise, advanced tools, and innovative methodologies designed to handle the complexities of modern data ecosystems. The result is a clearer, more actionable understanding of the information, empowering organisations to make informed decisions that lead to tangible improvements in performance and outcomes.

Data engineering serves as the foundation upon which successful data-driven strategies are built. It’s the backbone that supports the collection, transformation, and delivery of data to the right people at the right time. In this blog, we’ll explore data engineering as a discipline, delve into the innovative concepts of Virtual Data Engineering (VDE) and Virtual Database Administration Services (VDAS), and highlight how these services, provided by expert companies, can revolutionise the way organisations leverage their data assets to meet their goals.

What is Data Engineering?

The field of data engineering encompasses a wide range of activities, including:

• Data Ingestion: Capturing data from various sources, such as databases, APIs, IoT devices, and social media platforms, and bringing it into the organisation’s data ecosystem.
• Data Transformation: Cleaning, enriching, and transforming raw data into formats suitable for analysis. This often involves processes like data wrangling, normalisation, and aggregation.
• Data Storage: Designing and managing data storage solutions, such as data warehouses, data lakes, and cloud storage, to ensure data is stored securely and efficiently.
• Data Orchestration: Automating data workflows and ensuring data is delivered to the right systems and users at the right time.
• Data Governance: Implementing policies and practices to ensure data quality, security, and compliance with regulatory requirements.
• Data Monitoring: Continuously monitoring data pipelines and infrastructure to detect and resolve issues, ensuring data availability and reliability.

The role of data engineers is critical in building the infrastructure that enables data-driven decision-making. Without effective data engineering, organisations would struggle to manage their data assets, leading to missed opportunities, inefficiencies, and a lack of competitive edge.

The Evolving Landscape of Data Engineering

Virtual Data Engineering (VDE) as a Service

What is Virtual Data Engineering?

By engaging a company offering VDE services, organisations can access the expertise and resources needed to design, deploy, and manage data pipelines without worrying about the technical details. This service is particularly valuable for organisations looking to leverage data-driven strategies but lacking the internal expertise or infrastructure to do so effectively.

Benefits of Virtual Data Engineering as a Service

• Scalability: With VDE services, expert companies provide scalable data engineering solutions that can grow with the organisation’s needs. Virtual environments can be easily expanded or contracted based on data volumes, processing requirements, and business demands.
• Cost Efficiency: Engaging a VDE service allows organisations to reduce costs associated with maintaining physical hardware and infrastructure. Companies providing these services often offer flexible pricing models, enabling organisations to optimise their data engineering investments.
• Agility: VDE services provide the agility needed to quickly adapt to changing business requirements. Expert companies can deploy new data pipelines or modify existing ones with minimal disruption, ensuring that organisations remain responsive to market changes.
• Simplified Management: By outsourcing data engineering tasks to a VDE service provider, organisations can simplify the management of complex data environments. This reduces the risk of errors and frees up internal resources to focus on core business activities.
• Faster Time to Market: VDE services enable organisations to accelerate the development and deployment of data-driven solutions. This can give businesses a competitive edge by allowing them to respond more rapidly to market opportunities.
• Improved Collaboration: Expert companies providing VDE services often include collaboration tools that facilitate effective communication between data engineers, data scientists, and business users. This ensures that data engineering efforts are aligned with business goals.

Use Cases for Virtual Data Engineering as a Service

• Big Data Analytics: Organisations dealing with large volumes of data can engage VDE services to manage data pipelines for big data analytics, leading to faster and more accurate insights.
• Data Integration: VDE services are ideal for integrating data from disparate sources, such as on-premises systems, cloud platforms, and third-party APIs, enabling organisations to create a unified data environment.
• Real-Time Data Processing: For organisations that need to process data in real-time, VDE services offer the scalability and performance needed to handle high-velocity data streams.
• Data Migration: Expert companies can simplify the migration of data from legacy systems to modern platforms by providing VDE services, ensuring a smooth and efficient transition.

Virtual Database Administration Services (VDAS)

What is Virtual Database Administration Services?

These services typically include a range of features, such as automated provisioning, scaling, backup, and disaster recovery. VDAS is designed to simplify database management and enable organisations to focus on using data to drive their business goals rather than worrying about the underlying infrastructure.

Benefits of Virtual Database Administration Services

• Elastic Scalability: With VDAS, expert companies provide elastic database management services that scale with the organisation’s needs. This elasticity ensures that database resources are always optimally allocated, even during peak demand periods.
• Cost Savings: By outsourcing database administration to a VDAS provider, organisations can reduce costs associated with physical hardware, maintenance, and database administration. The service often operates on a pay-as-you-go model, allowing businesses to pay only for the resources they use.
• High Availability: VDAS providers design their services with redundancy and failover mechanisms to ensure high availability. This means that databases remain accessible and operational, even in the event of hardware failure or other disruptions.
• Automated Management: VDAS includes automation features that handle routine tasks such as backups, patching, and scaling. This reduces the burden on internal teams and allows organisations to focus on higher-value activities.
• Simplified Disaster Recovery: Expert companies offering VDAS ensure that databases are replicated and backed up across multiple locations, simplifying disaster recovery and ensuring business continuity.
• Global Reach: For organisations with a global presence, VDAS providers offer the ability to deploy databases in multiple regions, ensuring low-latency access for users around the world.

Use Cases for Virtual Database Administration Services

• Cloud-Native Applications: Organisations building cloud-native applications can leverage VDAS to host their databases in the cloud, taking advantage of the scalability and flexibility that virtualisation offers.
• Data Warehousing: VDAS is well-suited for data warehousing, where large volumes of data need to be stored, processed, and queried efficiently. The elastic scalability ensures that data warehouses can grow with the organisation’s needs.
• Multi-Tenant Environments: For SaaS providers and other businesses that serve multiple customers, VDAS offers a way to manage separate databases for each tenant while maintaining centralised control and management.
• Disaster Recovery: Organisations that require robust disaster recovery solutions can use VDAS to replicate their databases across multiple regions, ensuring that data is always available in the event of a disaster.

Conclusion: Embracing the Future of Data Engineering

Virtual Data Engineering and Virtual Database Administration Services, provided by expert companies, represent the next evolution in these fields, offering organisations the tools they need to manage their data assets more effectively. By embracing these innovations, businesses can unlock new opportunities, drive innovation, and stay ahead of the competition in a rapidly changing world.

The future of data engineering and database administration is virtual, and the benefits are clear. Organisations that engage expert companies for Virtual Data Engineering and Virtual Database Administration Services will be well-positioned to navigate the challenges of the digital age and thrive in an increasingly data-driven economy.

Why Choose Oreta for Virtual Data Engineering and DBA Services?

• Expertise: Oreta has a team of qualified and certified data engineers and DBAs who have extensive experience and knowledge in data engineering and AI technologies and solutions.
• Flexibility: Oreta offers a flexible approach to its commercial construct, allowing you to choose the service model that suits your needs and budget.
• Quality: Oreta follows a rigorous quality assurance process to ensure that its data engineering and DBA services meet the highest standards of excellence and customer satisfaction.
• Security: Oreta adheres to strict security policies and procedures to protect your data and systems from any threats or breaches.
• Support: Oreta provides ongoing support and maintenance for its data engineering and VDAS services, ensuring that your data infrastructure and pipelines are always running smoothly and efficiently.

If you are looking for a reliable and cost-effective way to streamline your data engineering processes and unlock the power of your data, look no further than Oreta. Contact us today to find out how we can help you with our VDE and VDAS services.

How Azure OpenAI can revolutionise your businesses operations

The examples of practical use of Azure Open AI

Welcome to the second part of our three-part series on Azure OpenAI services where we are continuing to explore how Microsoft’s Azure AI platform is revolutionsing business operations with cutting-edge artificial intelligence. In this we will examine some practical use cases of Azure OpenAI and see how its advanced features can revolutionise your business operations and enhance its performance.

In the first post (Link to Part 1) we learned that Azure OpenAI is a cloud platform that offers powerful artificial intelligence (AI) models and tools through a partnership between Microsoft and OpenAI. As a result, Azure OpenAI helps businesses to use the newest advances in natural language processing, computer vision, and generative models to address challenging problems and generate new possibilities.

Azure OpenAI can help businesses not only to improve their efficiency, productivity but, also, and create new value and opportunities. Let us look into some examples of how Azure OpenAI can be applied to different business scenarios across variety of industries:

Enhancing Customer Service and Support

Streamlining Content Creation and Marketing

Enhancing Financial Analysis and Reporting

Automating Supply Chain and Logistics

Revolutionising Healthcare Services

In the healthcare sector, Azure OpenAI can support diagnostics, treatment recommendations, and patient engagement. A hospital has an option to integrate Azure OpenAI into its electronic health record (EHR) system. The AI models assist doctors by analysing patient data, suggesting potential diagnoses, and recommending treatment options based on the latest medical research. Additionally, AI-powered chatbots engage with patients to remind them of appointments, provide medication information, and answer general health queries. This enhances patient care, reduces the workload on healthcare professionals, and improves overall efficiency.

Enhancing Human Resources and Recruitment

Innovating Product Design and Development

Improving Legal Document Review and Compliance

Transforming Education and E-Learning

Enhancing Retail Customer Experience

Conclusion

Azure OpenAI offers a multitude of opportunities for businesses across various industries to revolutionise their operations and processes. By leveraging advanced AI models and tools, companies can enhance efficiency, improve productivity, and create new value. Whether it’s through enhancing customer service, streamlining content creation, optimizing supply chains, or innovating product design, Azure OpenAI has the potential to transform the way businesses operate.

In our forthcoming third part of the series, we will explore in greater detail the technical aspects involved in deploying Azure OpenAI. We will look at an example of how Oreta internal IT operations applied Azure OpenAI services to enable improvements of service ticketing in Connect Wise system. This will provide you with a real working scenario of developing a model that utilises historical service ticketing data to enhance the automation of ticket generation, assignment tickets to the correct support groups, and to expedite their resolution. So, please keep an eye out for the next blog for these exciting insights.

Contact us now if you want to have chat about Azure OpenAi.

Microsoft AI Portfolio

Below is a visual representation of the Microsoft AI portfolio, showcasing various AI services and applications:

Introduction to Azure AI Services

Designed to be both accessible and robust, Azure AI Services allow businesses the flexibility to build, train, and deploy AI models efficiently using the secure and scalable infrastructure of Azure. The platform supports a range of programming languages and frameworks, making it a versatile choice for teams committed to driving innovation and improving decision-making using cutting-edge AI technologies.

Below is a detailed view of Azure AI services and how OpenAI models are integrated:

Azure AI Services Overview

• Azure AI Speech

Azure AI Speech offers tools for converting speech to text, text to speech, and translating speech into different languages. It also includes speaker recognition features, making it a powerful tool for applications requiring voice interaction and transcription services.

• Azure AI Language

Azure AI Language includes features like sentiment analysis, text summarization, key phrase extraction, entity linking, and custom text classification. These capabilities are crucial for building applications that need to understand and analyse textual data.

• Azure AI Vision

Azure AI Vision provides advanced image and video analysis capabilities, including optical character recognition (OCR), facial recognition, and object detection. This service is essential for applications that require processing and understanding visual data.

• Azure AI Search

Azure AI Search (formerly known as Azure Cognitive Search) enables developers to build sophisticated search experiences into their applications. It supports keyword searches, natural language processing, and AI-powered relevance ranking to deliver accurate search results.

• Azure Bot Services

Azure Bot Services provides a comprehensive framework for building, testing, and deploying intelligent bots. It integrates with other Azure AI services, allowing bots to use speech recognition, language understanding, and other AI capabilities to provide interactive and personalized experiences.

• Azure OpenAI

Azure OpenAI Service is a key component of the Azure AI portfolio, providing access to OpenAI’s powerful generative models, such as GPT-4, GPT-3.5, DALL-E, and Whisper. These models excel in understanding and generating human-like text, creating images from text prompts, and transcribing speech. Azure OpenAI integrates these advanced capabilities into the broader Azure AI ecosystem, enhancing its functionality and providing businesses with cutting-edge AI tools.

How Azure OpenAI Differs from OpenAI?

• OpenAI is an independent research organization focused on developing and deploying advanced AI models. Their flagship models include GPT-4, GPT-3.5, DALL-E, and Whisper. These models excel in generating human-like text, creating images from text prompts, and transcribing speech.
• Microsoft and OpenAI Partnership: The partnership between Microsoft and OpenAI brought Azure OpenAI Service into the picture. This collaboration leverages OpenAI’s cutting-edge models and integrates them into the Azure ecosystem, offering additional benefits such as security, compliance, and scalability.
• Azure OpenAI Service provides access to OpenAI’s models within the Azure ecosystem. This service offers the same advanced models as OpenAI but with the added benefits of Azure’s security and enterprise capabilities. By combining OpenAI’s innovative AI models with Azure’s robust infrastructure, businesses can achieve powerful AI solutions with enhanced security, compliance, and seamless integration with other Azure services.
• Key Differences with Azure OpenAI:
  • Security and Compliance: Azure OpenAI integrates with Azure’s robust security infrastructure, ensuring data protection, access control, and compliance with industry standards.
  • Integration with Azure Services: Azure OpenAI seamlessly integrates with other Azure services like Virtual Networks (VNETs) and Private Endpoints, providing a cohesive and scalable solution.
  • Data Handling: Data submitted to Azure OpenAI remains within Microsoft Azure and is not passed to OpenAI for model predictions, ensuring Azure has sole control and governance of the data, providing enhanced data privacy and security.

While there’s no strict guidance on when to use a particular service, Azure AI service can be used for widely known use-cases that require minimal tuning. Azure OpenAI Service may be more beneficial for use-cases that require highly customized generative models or for exploratory research.

Tools to Manage Azure AI Services

• Azure AI Studio

Azure AI Studio is a unified development environment where you can build, train, and deploy AI models. It offers a user-friendly interface and integrates seamlessly with other Azure services, making it easy to manage AI projects.

• Client Libraries and REST APIs

For developers and data scientists, Azure provides client libraries and REST APIs, offering programmatic access to Azure AI services. These tools provide flexibility and control for customizing AI models and solutions.

• Continuous Integration and Deployment

Azure supports continuous integration and deployment (CI/CD) with tools like Azure DevOps and GitHub Actions. These tools automate the training, testing, and deployment of AI models, ensuring that your applications are always up to date.

Azure OpenAI Use Cases

• Customer Service: AI-powered chatbots and virtual assistants provide instant, personalized responses to customer inquiries, enhancing customer satisfaction and reducing operational costs.
• Content Generation: Automate the creation of high-quality content, ensuring consistency and accuracy, particularly beneficial for marketing and content-driven businesses.
• Predictive Analytics: By analysing historical data, Azure OpenAI helps businesses predict future trends and make proactive decisions, optimizing inventory management and reducing risks.
• Personalized Marketing: Create highly targeted marketing campaigns by analysing customer data and behaviours, improving customer engagement and conversion rates.

Conclusion

Oreta stands at the forefront of harnessing the power of Azure AI services to drive business innovation and operational excellence. Our expertise in integrating these advanced AI tools enables organizations to unlock new levels of productivity, enhance decision-making, and implement cutting-edge solutions tailored to their unique needs. By leveraging Azure AI’s comprehensive suite, including speech, language, vision, search, and bot services, alongside the transformative capabilities of Azure OpenAI, we help businesses stay competitive and future-ready.

Stay tuned for the next instalment in our series, where we will delve deeper into practical use cases of Azure OpenAI and explore how its advanced features can revolutionize your business operations. Don’t miss out on discovering how to elevate your enterprise with the future of intelligent applications. Contact us today to learn how Oreta can help you implement and optimize Azure AI services for your business needs.

Introduction

Microsoft is a major player when it comes to cloud computing, specifically with its two foundational frameworks: the Cloud Adoption Framework (CAF) and the Well-Architected Framework (WAF). The CAF has been instrumental in guiding organisations through their cloud adoption journey, offering a comprehensive array of best practices, documentation, and tools for effective cloud strategy and implementation.

On the other hand, the WAF, while not a recent introduction, has received substantial updates to further enhance cloud architecture approaches. These updates, particularly in late 2023, reflect Microsoft’s commitment to continuous improvement, ensuring that the framework remains relevant and valuable in addressing the evolving needs of cloud architecture.

Explore why CAF and WAF are the commonly discussed and implemented frameworks, gain in depth overview on their significance for businesses navigating the complexities of cloud transformation.

What is CAF and how does it work?

The Microsoft Cloud Adoption Framework (CAF) is not just a blueprint for cloud adoption; it’s an evolving guide that adapts to the ever-changing cloud landscape. This framework is meticulously designed to support cloud architects, IT professionals, and business decision-makers in seamlessly transitioning to the cloud. It aligns business objectives with technical strategies, ensuring successful cloud adoption and optimisation. The CAF encompasses a full lifecycle approach, addressing each stage of cloud adoption with detailed methodologies:

• Strategy: This involves understanding the underlying motivations for cloud adoption and clearly defining the desired business outcomes. It’s about setting a solid foundation for the cloud journey by aligning it with business objectives.
• Plan: Here, the focus is on developing actionable and strategic plans that align with the set business goals. This phase involves detailed planning for the cloud adoption process.
• Ready: This step prepares the cloud environment to accommodate upcoming changes, ensuring it’s optimised and aligned with the planned adoption strategies.
• Migrate: This critical phase involves the migration and modernisation of existing workloads to the cloud. It includes strategies for both moving existing applications and rearchitecting them in a cloud-native environment.
• Innovate: Encouraging the development of new, cloud-native or hybrid solutions, this phase fosters innovation and leverages the full potential of cloud capabilities.
• Secure: Recognising the importance of security, this methodology focuses on enhancing security measures and ensuring robust protection of cloud resources.
• Manage: This entails the management and operational oversight of cloud and hybrid solutions, emphasising efficiency and performance optimisation.
• Govern: It involves the governance of the cloud environment and workloads, ensuring compliance, risk management, and alignment with business policies.

Recent updates to the CAF include a stronger emphasis on sustainability, multi-tenant architectures, and integration with systems like Systems Applications and Products In data Processing (SAP). These updates reflect Microsoft’s commitment to providing a framework that not only guides but also grows with the technological advancements and changing business landscapes.

What is WAF and how does it work?

The Well-Architected Framework (WAF) by Microsoft, while not a brand-new introduction, has recently undergone significant enhancements to further strengthen its role in cloud architecture. Complementing the Cloud Adoption Framework (CAF), WAF focuses intently on the architectural aspect of cloud solutions, guiding the design and management of cloud-hosted applications to ensure they are robust, secure, cost-efficient, and high-performing. The framework is structured around five key pillars, each representing a core element of architectural excellence:

• Reliability: This pillar emphasises the creation of systems that are not only resilient but also capable of swift recovery in the face of disruptions. The goal is to ensure uninterrupted service and high availability.
• Security: Focused on safeguarding applications and data, this pillar involves implementing comprehensive security measures that protect against threats while maintaining compliance and privacy standards.
• Cost Optimisation: Balancing cost against performance and capacity, this area aims to optimise resource utilisation and expenditure, ensuring that cloud investments are both effective and economical.
• Operational Excellence: This involves enhancing operational procedures to ensure smooth, efficient, and reliable business processes. It encompasses automation, monitoring, and continuous process improvement.
• Performance Efficiency: Concentrated on maximising system performance, this pillar stresses the importance of leveraging cloud capabilities to achieve scalable and responsive solutions.

The recent updates to WAF, announced in late 2023, have enriched the framework with more precise guidelines and instructional content across these pillars. These enhancements include updated design principles, checklists, trade-offs, and recommendation guides, all rooted in extensive real-world experience and customer engagements. The framework now offers more detailed guidance for workload teams, shaping discussions and decisions within these teams and setting continuous standards for all workloads.

How does CAF work with WAF?

Adopting these frameworks is not just about leveraging technology; it’s about a transformation in delivering IT services and reorienting business strategies. CAF ensures that this transformation is well-grounded in business strategy, while WAF guarantees that the technology implementation is optimal and well-architected. By integrating these frameworks, Oreta helps organisations to “stand on the shoulders of giants” by leveraging Microsoft’s vast experience to avoid common pitfalls and accelerate cloud journeys.

At Oreta, we understand the nuances and complementary nature of Microsoft’s CAF and WAF. By leveraging these frameworks, we guide organisations through each phase of their cloud journey, ensuring that every step is aligned with business objectives and grounded in architectural excellence. Our expertise ensures that your cloud transformation is not just a technological upgrade but a strategic evolution of your business.

Embark on your cloud journey with Oreta’s expertise in Microsoft’s CAF and WAF. Contact us to explore how we can tailor these frameworks to your organisation’s unique cloud transformation needs.

Introduction

In this blog post, we will explore the guideline for selecting the ideal cloud provider to suit your business needs. Whether you’re grappling with cloud solutions, software development, cybersecurity, or any other technological facet, join us as we uncover the secrets to effectively discerning the ideal service provider that aligns with your organisation’s unique needs and propels your business towards sustained success.

When choosing the right cloud provider, you should consider the below factors:

Deep Expertise
Scalability Support
Customer Service
Managed Services
Migration Support and Security

Deep Expertise

According to a Gartner report, almost all legacy applications migrated to public cloud infrastructure as a service (IaaS) will need optimisation to become more cost-effective by 2024. This underscores the critical role of a cloud provider’s expertise in maximising the benefits of cloud solutions.

A cloud provider’s deep expertise is essential for maximising cloud potential while minimising risks and complexities because it allows for:

• Strategic Alignment: Deep expertise aids in selecting a cloud solution that aligns with your business goals, driving efficiency and innovation.
• Risk Mitigation: A knowledgeable provider can navigate the complexities of cloud implementation, minimising risks such as operational disruptions and security vulnerabilities.
• Optimal Resource Utilisation: Expert providers can help identify the cloud services that deliver the most value for your unique needs, ensuring effective resource usage.
• Futureproofing: An expert provider stays updated with latest trends, helping your business adapt and leverage these advancements, safeguarding your technology investment.
• Vendor Management: Deep expertise simplifies navigation through the complex cloud ecosystem, ensuring seamless integration between different vendors.

Some pivotal questions to ask your cloud provider about their expertise should include:

• Can you describe your experience with cloud solutions similar to our needs?
• What is your process for understanding our business needs and aligning them with the right cloud solution?
• How do you ensure the solutions you provide are future-proof?
• Can you explain how you mitigate risks during cloud migration and implementation?
• What strategies do you employ for optimal resource utilisation in the cloud?
• Can you share your experience managing multiple vendors in the cloud ecosystem?

Scalability Support

RightScale’s 2020 State of the Cloud Report shows that 31% of businesses see cloud cost optimisation as a significant challenge when scaling cloud services, emphasising the necessity of professional scalability support.

The quality of scalability support is crucial when selecting a cloud service provider for the following reasons:

• Future Growth: Scalability support ensures the IT infrastructure grows with the business, accommodating increased traffic, data, and complex applications without performance loss.
• Cost Efficiency: The elasticity of cloud solutions, allowing resources to scale based on demand, ensures businesses pay only for what they use, optimising IT spending.
• Performance Maintenance: Scalability support guarantees consistent service to customers, even as the business scales.
• Innovation Support: Scalability enables quick testing and implementation of new ideas without heavy upfront investment, propelling innovation.

Some pivotal questions to ask your cloud provider about their scalability support should include:

• How will your cloud solutions adapt to our growing needs, such as increased traffic or data volume?
• What is your strategy for adding resources to accommodate our business growth?
• How do you maintain high performance levels as the demands on our cloud resources increase?
• How does scaling up or down reflect on our billing and overall cloud expenses?
• Can you provide examples of how you’ve helped other businesses scale their cloud services successfully?

Customer Service

According to the Microsoft 2020 State of Global Customer Service report, 58% of customers say customer service is a very important factor when choosing a brand, signifying the vital role of customer service in client decision-making. As Bill Gates once said, “Your most unhappy customers are your greatest source of learning,” emphasising the importance of responsive and effective customer service in any business.

Effective customer service is crucial when selecting a cloud service provider due to the following reasons:

• Immediate Assistance: In today’s fast-paced digital world, quick resolution of issues is paramount. Good customer service ensures swift and effective responses, minimising potential downtime.
• Product Understanding: A customer service team with deep product knowledge can guide businesses to better utilise their cloud services, boosting operational efficiency.
• Relationship Building: Exceptional customer service fosters a strong business relationship, promoting trust and long-term commitment.
• Issue Prevention: Proactive customer service can identify and rectify potential issues before they escalate, improving overall system reliability.

Some pivotal questions to ask your cloud provider about their customer service should include:

• What is your support response times, and do you provide 24/7 assistance?
• How does your team handle issue escalation and resolution?
• Can you provide specific examples of how your customer service team has gone above and beyond to support a client?
• How do you gather and incorporate customer feedback into your services and support?

Managed Services – Cloud Operations

According to a report from MarketsandMarkets, the managed services market is expected to grow from USD 223.0 billion in 2020 to USD 329.1 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 8.1% during the forecast period. This data highlights the increasing demand and value businesses place on managed services in the realm of cloud computing.

The inclusion of managed services is vital when choosing a cloud service provider for the following reasons:

• Operational Efficiency: Managed services allow businesses to concentrate on their core tasks by outsourcing IT management, thus improving productivity.
• Cost Savings: Managed services can lead to significant cost savings by reducing the need for in-house IT teams and infrastructure.
• Risk Reduction: With expert handling of IT aspects, managed services help mitigate the risk of data loss, downtime, and cyber threats.
• Access to Expertise: Managed services bring specialised knowledge and skills, which can lead to better IT decision-making and innovation.

Some pivotal questions to ask your cloud provider about their managed services should include:

• What managed services do you offer, and how do they enhance the base cloud services?
• How do your managed services improve operational efficiency and security?
• Can you provide examples of how your managed services have added value to other businesses?
• How does your managed services model reflect on our overall cloud expenses?

Migration / Integration Support and Security

According to a 2020 report by Fortinet, 74% of organisations have moved some applications into the cloud and then moved them back on-premises, indicating the complexities of the migration process. Moreover, a Gartner study found that through 2025, at least 99% of cloud security failures would be the customer’s fault, emphasising the need for expert migration, integration, and security support.

Migration, integration support and security are critical when selecting a cloud service provider for the following reasons:

• Smooth Transition: Expert support ensures a seamless migration, minimising disruption to business operations.
• Optimised Performance: Proper integration allows businesses to leverage their cloud services fully, enhancing performance and efficiency.
• Data Protection: Robust security measures protect sensitive business data from unauthorised access and cyber threats.
• Risk Reduction: Expert planning and execution of the migration process mitigate risks of data loss or system downtime. Similarly, stringent security measures help prevent potential cyber threats.

Some pivotal questions to ask your cloud provider about their mitigation support and security should include:

• What is your process for migrating systems to the cloud, and how do you ensure minimal disruption to our operations?
• How do you ensure seamless integration between the cloud services and our existing systems?
• What security measures do you have in place to protect our data and applications in the cloud?
• Can you provide examples of migrations, integrations, and security measures you’ve successfully implemented for other businesses?

Conclusion

Additionally, outstanding customer service fosters trust and minimizes downtime. Managed services enhance operational efficiency, cut costs, and mitigate risks. Comprehensive support for migration, integration, and security ensures a smooth transition and data protection. By asking pivotal questions, you can partner with the right provider for a successful digital future.

At Oreta, we stand as the premier cloud service provider for businesses in Australia. With our deep expertise, proven track record, and strong partnerships with major cloud platforms, we deliver exceptional solutions tailored to our clients’ unique needs. Our focus on managed security services, compliance assistance, scalability support, transparent pricing, and outstanding customer service is what sets us apart. We ensure seamless migration and integration processes, enabling businesses to unlock the full potential of the cloud. Trust Oreta as your strategic cloud partner and experience the power of cloud technology to drive your business forward.

Contact us now for a no obligation chat.