In this lively debate you will hear from Calligo’s Practice Leads as they discuss their key takeaways from 2023 and their data predictions for 2024 and beyond.
Topics discussed include:
Regulation of AI including the EU AI act
AI hallucinations & AI bias
Data governance and data fines
Dashboard fatigue
Data ROI
In the rapidly evolving landscape of IT infrastructure, businesses are constantly faced with the critical decision of choosing between on-premises and cloud solutions. The allure of cloud computing, with its promises of scalability, flexibility, and cost efficiency, often leads organizations to assess the financial implications of their choices meticulously. In this blog post, we’ll delve into the complexities of assessing on-premises vs. cloud costs, exploring hidden expenses, the concept of shared responsibility, and the role of a trusted partner like Calligo in navigating this intricate terrain.
Comparing On-Premises and Cloud Costs
On-Premises Costs:
1. Capital Expenditure:
On-premises solutions often entail significant upfront costs for hardware, software licenses, and infrastructure setup. This capital expenditure can strain budgets and limit financial flexibility.
2. Maintenance and Upgrades:
Regular maintenance, updates, and hardware upgrades contribute to ongoing operational costs for on-premises solutions. Predicting and managing these costs can be challenging over the long term.
3. Staffing and Training:
Employing skilled personnel for system administration, maintenance, and troubleshooting adds to the on-premises cost equation. Training employees to manage evolving technologies further increases operational expenses.
Cloud Costs:
1. Pay-as-You-Go Model:
Cloud services operate on a pay-as-you-go model, allowing businesses to pay only for the resources they use. This flexibility can be advantageous for managing costs efficiently, especially during periods of fluctuating demand.
2. Operational Expenditure:
Cloud solutions transform IT costs from capital expenditure to operational expenditure, providing businesses with more predictable and manageable ongoing expenses.
3. Scalability and Efficiency:
Cloud scalability enables organizations to adapt quickly to changing workloads, optimizing costs by automatically adjusting resource allocation.
Hidden Costs in the Cloud:
While the cloud offers a transparent pay-as-you-go model, hidden costs may emerge without careful consideration:
1. Data Transfer and Bandwidth:
Cloud providers may charge for data transfer between regions and the internet, making it essential to factor in bandwidth costs.
2. Storage Costs:
The cost of storing data in the cloud can accumulate, especially with large datasets. Assess storage needs and choose cost-effective storage options.
3. Egress Charges:
Cloud providers may impose fees for data leaving their network. Understanding egress charges is crucial, especially for data-intensive applications.
Shared Responsibility Model:
As organizations transition to the cloud, it’s essential to understand the shared responsibility model:
1. Cloud Provider Responsibilities
Cloud providers manage the security and compliance of the cloud infrastructure, including data center security, hardware maintenance, and network infrastructure.
2. Customer Responsibilities:
Customers are responsible for securing their data within the cloud, managing access controls, implementing encryption, and ensuring compliance with industry regulations.
Responsibility Transfer to the Cloud Provider:
With the cloud, certain responsibilities are transferred to the provider:
1. Security and Compliance:
Cloud providers invest in robust security measures and adhere to compliance standards, alleviating some security concerns for customers.
2. Hardware Maintenance:
The burden of hardware maintenance, updates, and upgrades shifts to the cloud provider, reducing the operational workload for customers.
Areas of Responsibility Retained by the Customer:
Despite the advantages of responsibility transfer, customers retain crucial responsibilities:
1. Data Security:
Ensuring the security of data within the cloud, including encryption, access controls, and compliance, remains the customer’s responsibility.
2. Application Security:
Customers are responsible for securing applications deployed in the cloud, addressing vulnerabilities, and implementing best practices for secure coding.
Leveraging Calligo for Informed Decision-Making:
Calligo, as a leading player in cloud services, plays a pivotal role in helping organizations assess on-premises vs. cloud costs:
1. Comprehensive Cost Analysis:
Calligo conducts a thorough analysis of on-premises and potential cloud costs, considering factors like data transfer, storage, and potential hidden expenses. This ensures organizations make informed financial decisions.
2. Expertise in Compliance and Security:
Calligo’s expertise in compliance and security positions them as a valuable partner. They assist in navigating shared responsibility, ensuring that customers meet compliance standards while benefiting from the security measures provided by the cloud.
3. Tailored Solutions:
Calligo recognizes that each organization is unique. By offering tailored solutions, they ensure that the migration strategy aligns with business objectives, optimizing costs while addressing specific needs and challenges.
4. Managed Services for Ongoing Optimization:
Beyond migration, Calligo provides managed services for ongoing optimization. This includes continuous monitoring, updates, and adjustments to ensure that cloud resources are utilized efficiently, maximizing cost-effectiveness.
Conclusion:
Assessing on-premises vs. cloud costs is a multifaceted endeavor that goes beyond comparing price tags. It requires a deep understanding of the shared responsibility model, consideration of hidden costs, and strategic decision-making. With the expertise of Calligo, organizations can embark on their cloud journey confidently, navigating the complexities of cost analysis, compliance, and security to unlock the full potential of the cloud while optimizing financial investments. Embrace the future of IT infrastructure with a trusted partner by your side, ensuring that every step taken is a step toward efficiency, scalability, and success.
For more comprehensive insights into cloud strategy, visit https://cal.essence-design.co.uk
Artificial Intelligence (AI) and machine learning have revolutionized numerous industries, offering automation and efficiency. However, achieving the optimal balance between human input and machine automation in AI model development is crucial but often overlooked. In our recent Beyond Data podcast, hosts Tessa Jones and Peter Matson were joined for a compelling discussion with the co-founder of Trubrics, Joel Hodgson, where the importance of AI explainability, trust, user feedback, and ongoing monitoring were explored.
Joel highlighted the challenge of model adoption, a common issue in the data science landscape. Organizations invest significant time and resources in developing AI models, only to face skepticism and underutilization from non-technical stakeholders. This hesitation often arises from a lack of trust and understanding. Education and transparency are vital tools to address this challenge.
Another significant hurdle is the gap in effective communication between business professionals and data scientists. Bridging this divide is essential to incorporate valuable domain knowledge into the model development process. The solution lies in creating feedback loops that enable collaboration between domain experts, business users, and data scientists throughout the model’s lifecycle. These feedback loops are crucial for gathering user insights, improving model performance, and building trust.
Trubrics’ approach of “machine learning monitoring from the users’ point of view” shifts the focus from traditional machine learning metrics to user perception. Evaluating AI models based on their impact and utility to users, rather than just accuracy, is essential. Users’ experiences, trust, and satisfaction play a pivotal role in determining the effectiveness of AI models. Monitoring should identify issues impacting the user experience and ensure AI models align with user expectations.
Trust emerged as a cornerstone in AI adoption. Trust is not limited to data scientists but extends to end-users, employees, and the entire organization. It involves transparent communication, feedback loops, and alignment between different groups. Over time, as individuals become more familiar with AI in the business world, this trust can be built and weaved into organizations’ culture, just as our trust in everyday technology has.
Monitoring AI models’ performance is essential. Technical monitoring involves tracking various model characteristics, while business-facing monitoring assesses alignment with expectations and business impact. These two facets of monitoring are crucial in ensuring AI models continue to meet user needs and business objectives and therefore must be aligned when identifying the reasoning and desired outcomes from such models.
Measuring and evaluating the Return on Investment (ROI) for AI models presents considerable challenges, especially when examining their performance over extended periods. Striking a balance between the continual expenses associated with model maintenance and the value it delivers requires a nuanced approach. Organizations need to account for both the initial and ongoing financial ROI assessment, recognizing that it can become less clear-cut.
According to a recent research report conducted by Calligo, in collaboration with the Global CIO Institute, “36% of business leaders measure the success of an ML project in financial terms, while 11% either have no way to gauge success or go by gut feeling“. This suggests that determining the ROI for ML and AI initiatives isn’t solely tied to financial gains; it also involves a significant degree of uncertainty when the desired ROI isn’t well-defined at the project’s outset.
In conclusion, AI explainability and the balance between human input and machine automation are crucial in AI model development. Education, transparency, effective communication, user-centric monitoring, and trust-building are essential elements in this endeavor. As AI continues to shape our world, achieving these elements will be pivotal to ensure responsible and ethical AI development and its successful integration into our lives. Organizations like Trubrics are at the forefront of this mission, working towards making AI a valuable and trusted tool in our increasingly automated world.
Listen on Spotify or watch below
When it comes to how truly intelligent Artificial Intelligence (AI) is, it’s a polarizing debate. Either AI will solve the world’s woes or robots will rule us all – Matrix-style. But it’s all a little more complicated than Hollywood makes it seem…
Watch podcast episode 2 here
For a deep dive, do listen to our Beyond the Data podcast hosted by Sophie Chase-Borthwick (Calligo’s Global Data & Governance Lead) and Tessa Jones (VP of Data Science Research & Development).
Meanwhile, in this blog we look at tea-making and social care robots to illustrate an otherwise very nuanced and arguably never-ending narrative on the ‘intelligence’ part of the AI equation.
It’s important first to consider the different types of AI:
Let’s unpick the gray area of ‘general AI’, by looking at what robots are capable of – and whether this makes them truly intelligent, yet…
A robot making a cup of tea isn’t something a lot of us think twice about and wouldn’t be the first example of proving intelligence in a typical setting. However, scientists are doing just this, typically by:
1. Coding in the tasks a robot has to complete first (boil kettle, get cup, put the teabag in and so on).
2. Using experience-based learning to demonstrate how to make a cup of tea. When the robot doesn’t do it well or something is not done correctly, then the robot is given more examples of how to do that task.
To successfully have the robot make a cup of tea, scientists are having to build in and prescribe a lot of the parameters and tasks a robot has to complete. However, if the environment changes (for example a robot has to make a cup of tea in a different room) it would likely struggle because it isn’t familiar with the environment and the parameters.
Intelligence can’t just be about managing to do a task correctly; it’s being able to use inference to adapt in a new environment and navigate unfamiliar parameters to complete a task.
However, this adaptation and re-learning is a lot slower for robots than it is for humans. As Tessa Jones highlights, it’s referred to as Moravec’s paradox and essentially means it’s easy to train robots to do things that humans find hard, like chess and logic-driven tasks. However, it’s hard to train robots to do things humans find easy, like walking and image recognition.
In the podcast Sophie Chase-Borthwick observes: “Playing a game of chess is very rule-based [and easy to code into a robot] whereas making a decent cup of tea is definitely an art”.
When looking at robots comprehending tasks much like a human, what could be more human than caring for one another? Japan is leading the exploration of the use of social robotics for assisted care. However, rather than the robot just serving a functional task, Japanese scientists are building one step further…
“There’s a concept coming out of Japan – a concept called ‘kokoro’”, says Tessa. “For robots to actually be effective and useful, there needs to be a heart-to-heart connection between the human and the robot”. There’s typically three kinds of kokoro you can achieve:
1. How the robot affects the human. If the human is feeling sick, whether the robot can interact in a way that lifts their spirits – for example Paro, a soft baby seal robot designed for use in hospitals and nursing homes as a therapeutic tool.
2. Whether the robot understands a human’s emotions. The robot can conceptualize when the human is feeling sad or angry. But getting this right is very difficult, as it’s hard to detect between anger and happiness based on imagery and voice. Microsoft has even recently stopped a lot of its programs around emotion detection as it opens the door to racial biases, and different facial and voice features.
3. When the robot itself feels and has its own ‘kokoro’. Currently, this remains confined to science fiction as it maps to ‘super intelligence.’
However, it’s worth considering the spectrum of human diversity. For example, neurodiverse people don’t always recognise what some emotions are but they are still intelligent. So recognising emotions and responding to them on its own isn’t a demonstration of intelligence.
As Sophie poignantly puts it: “Are we re-defining intelligence to suit the machines – and in doing so, carving out some humans?”.
Calligo’s Chief Information Security Officer, Mark Herridge, has written this blog to discuss why organizations need to adopt a “Zero Trust” approach when it comes to their data security and what steps they need to take to protect their data.
We all know working practices have changed as a result of COVID-19, lockdowns and a lingering – in some cases, permanent – reluctance to commute into major hubs.
Similarly, much has been reported on the rise of opportunistic COVID-19 security threats, ranging from social engineering tactics such as targeted phishing attacks that seek to prey on users’ ongoing worries about the pandemic to companies straining to quickly enable remote workers.
For the blissfully unaware, ransomware is a type of cyberattack whereby the attacker encrypts the files on a victim’s machine or across the network and then demands a ransom before they will be decrypted and access is restored, or so they hope. Sometimes the hacker will even threaten to sell or disclose the stolen data unless a ransom is paid.
The speed that COVID-19 spread around the globe and the lockdown that followed has caught many companies off guard, and there’s a good chance that you may even be reading this in a hastily-assembled home office, in your kitchen or a spare bedroom.
For some, the ability to keep data secure has been torpedoed by unexpected, sudden volumes of employees working from home, relying on domestic networks and personal devices. Similarly, there has been widespread confusion over how to balance employees’ privacy and confidentiality with the broader obligation of staff protection and even civil responsibility.
Navigating these times is difficult but there is some comfort in knowing that even during this emergency situation, the normal rules still apply.
Our Data Privacy team has released new guidance on the Data Security and Data Privacy concerns of the ‘new normal’, in order to help businesses follow data privacy rules and security best practice, while protecting the health and preserving the productivity of their staff.
Updated: December 2019
Planning for a business’s future can be an exciting time for business owners and office managers alike—what could be more inspiring than the possibility of growth, widespread positive impact, and success?
Unfortunately, there’s a darker side to planning for the future, too. While imagining and planning for the perfect scenarios above is important, the reality is that disaster can and does happen. Without preparing for both the good times and the bad times, a business and its offices can’t succeed.
That’s where business continuity planning comes in.
What Is Business Continuity Planning?
When unexpected disaster strikes, business owners and managers must have a safety plan in place to ensure that their business operations can continue after major events like natural disasters, cyberattacks, or other accidental damages to a company, its physical location, and its infrastructure.
Business continuity planning is the development and practice of a plan which businesses can implement in the event of a serious setback caused by one of the disasters above. These plans include aspects of both prevention and recovery, with the primary goal being to maintain business operations while protecting personnel, data, and assets.
Why Do You Need a Business Continuity Plan?
One could say that the benefits of having a BCP are endless, but they’re more than just benefits—they’re proof that a BCP plan is absolutely necessary.
So, what is this proof of a BCP’s importance?
Organisations with business continuity plans:
Inspire reliability, trust, and confidence in their clients
Build a good reputation (and preserve it during dire circumstances)
Instil the idea of resilience and strength throughout the company’s operations
Are up to the industry standard
Can thrive in any situation
Nobody ever wants their business continuity plan to have to be activated, because it means something disastrous has happened. But they’re a necessity in modern business and having confidence in your continuity planning is achievable.
What is the difference between data backups and a business continuity plan?
Simply having your data backed up and secure is a good start – but it is only a start. Planning for a catastrophic systems failure or a cyber attack, means knowing that:
You can restore data safely and rapidly
Your team will be able to get back using both software and hardware with confidence, soon after a systems failure
Customer service will be maintained
You won’t lose time, money or customer confidence
Take the following as an example. In January 2017, Cockrell Hill Police Department (Texas, US) came under ransomware attack. A single infected server led to the loss of eight years of evidence including video recordings. So far, so bad.
Then, their back-up procedure activated very soon after the ransomware attack replacing their backed up files with a backup of files that had been encrypted by the ransomware and were therefore inaccessible.
Their previously uncorrupted data backup was wiped out by the very system they’d been relying on to preserve it.
Cockrell Hill had a business back up, but they needed a business continuity plan.
Creating an effective business continuity plan
In designing a business continuity plan, it’s important to ask the following questions:
Are the backed-up files easily accessible?
Is the backup device safe, secure and accessible?
Can our operating systems be reinstalled from the backups or just the filesystem?
How long will reinstallation of our operating systems take?
How long will critical file restoration take?
And how long for complete data restoration?
How much time will pass before the business is able to be running at full capacity again?
And how much time must we allow to catch up on anything we had to postpone during the catastrophe?
A Quick Guide to Business Continuity Planning
Get organised from the beginning and start the process of business continuity planning by choosing which members of the company will work together to develop and maintain a plan. Delegate responsibly, and diversify the team in order to gather insight from multiple business branches.
However, ensure that the primary person responsible for organising and maintaining the BCP is someone high on the pyramid. In other words, a senior official like a business owner or an office manager should take point on leading the planning efforts.
Once a team has been established, take action to ensure that all company employees and contributors are aware of the team members and their responsibilities. This creates accountability while keeping the entire office in the loop.
Before mobilising your BCP team to begin outlining a plan, take some time to begin by performing a business impact analysis. A BIA includes gathering data about the worst-case scenario. In other words, a BIA will yield detailed information about possible company losses (both monetary and intangible) and the negative effects caused by major disruptions.
The BCP team can use the company’s mission statement and information about the company’s legal obligations to rank the minimal, critical services required of the business and then determine which of these services would be unable to function after a variety of emergency scenarios.
With the results of the BIA in mind, the team’s next task is to outline practical, actionable procedures to follow in the event of an emergency so that business functionality is maintained.
This process will include assessment of any current procedures in place, then filling in necessary gaps using information from the BIA. This might include readiness procedures to prepare for natural disasters or the process of archiving and backing up databases to recover from a cyberattack.
Once a BCP has been developed and reviewed by the planning team, make the rest of the organisation aware by hosting training sessions, designing exercises to make the plan tangible to employees, and reviewing the procedure in detail. Ensure that all employees understand why a BCP is necessary as well as how to implement this BCP in an emergency.
Importantly, help each employee to understand the individual role they can play in the implementation of the BCP. Let them know what’s at stake and how their participation will propel the business forward in a time of crisis.
A business may have one of the most thorough and effective BCPs out there, but this means little if the plan is not reviewed and updated on a regular basis. Include as a part of the plan regular checkpoints throughout the year during which members of the BCP team evaluate the plan and implement company-wide initiatives such as practice drills.
This step has become particularly important in recent years as technology evolves and malicious cyberattacks have risen in number.
Remember, threats are changing all the time, and the BCP must be updated and familiar to the entirety of the business in order to be effective.
Effective business continuity planning saves time, money and reputation
Rebuilding your system requires so much more than simply restoring data – there’s the time required to review what went wrong and make sure you’re not leaving yourself open to risk again. You have to account for the time and energy required to inform your team and your customers and rebuild their confidence after an event like this, whether it’s fire, flood our outside attack.
All in all, having a robust plan will save you not just time and money, but reputation too. In fact, it could save your entire business, because according to a study by accounting firm Touche Ross 90% of businesses without a disaster recovery plan will fail following a disaster. Considering 30% of businesses don’t have a plan in place, this figure is startling.
There is probably no business technology topic with more column inches dedicated to it than cloud computing.
Topics range from the virtues and drawbacks of private, public or hybrid, to the complexity of migration, or cloud’s suitability for certain industries, businesses or use cases. Not to mention the excitement over more futuristic topics such as the quantum computing race.