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Ignite the digitalisation turbo with low-code

Author: Stefan Brotzler, Director Enterprise Sales DACH at Mendix

Whether developing industry-specific applications or automating internal processes, low-code can be used in a wide range of applications. Initial best practices generally show very quickly that low-code can be used not only to develop individual applications or create connectors and other building blocks for digital business transformation. Low-code can also be used to tackle the most complex business requirements, such as the modernisation of legacy systems or the creation of new digital business models. This is because the technology offers a wide range of benefits that companies can use to give their digitalisation efforts the overdue boost they need to remain competitive.

IT backlogs are a thing of the past

The digitalisation train is picking up speed year after year. To ensure that companies are not left behind, digital solutions need to be provided faster and on a larger scale. But with IT projects that sometimes take years to complete, this is a major challenge. With visual modelling using drag-and-drop, prefabricated components, automation options, one-click deployment and assistance bots, speed is the foundation of any low-code platform. This is because low-code allows intuitive application creation even without programming skills. In fact, low-code can reduce development time by up to 90 per cent. This can turn years into months or even weeks.

Collaboration to combat the shortage of IT specialists

The inherent value of low-code is that it brings professional developers and other non-technical teams together in a collaborative environment using a visual language. This is beneficial for two reasons. Firstly, IT resources can be utilised in a more targeted manner when working in so-called “fusion teams” made up of developers and technically minded people from the specialist departments. Secondly, the quality of the solutions developed increases. This is because close collaboration and direct coordination close communication gaps from the outset and applications are created precisely in line with specific requirements. If these change ad hoc, for example, it can be ensured that this is immediately taken into account in the development process and that the final version covers the current requirements. The participation of the various stakeholders, including the end users, contributes to significantly accelerated development. The IT department therefore has more time to devote to complex tasks that require their specific expertise. They are no longer the bottleneck for technological progress in the company because their capacities are expanded by experts from other departments.

To anticipate persistent prejudices against so-called “citizen developers”: Low-code development does not promote shadow IT or the amateurish creation of applications. For example, because IT remains responsible for business-critical modules and applications. It is therefore possible to define the provision, combination and reuse options in advance using rules so that the other team members only use certain components as a “black box”. The available modules and interfaces can then be used on a modular basis, whether for the creation of new applications or the customisation of existing ones. Role-based access rights and control mechanisms that give IT an insight into the entire development lifecycle at all times also ensure that governance is satisfied. Shadow IT tends to spread uncontrollably if IT is unable to fulfil requests promptly and specialist departments end up creating applications and implementing solutions on their own that are not compatible with the rest of the IT landscape or even harbour security risks.

Composability meets agility

Many companies are already familiar with the term “composable enterprise” or “composable business”. These terms were coined by the analyst firm Gartner. This refers to an organisation that has a modular structure in order to be better prepared for increasingly dynamic market conditions in the future and to be able to react to changing customer requirements with agility. “Composability” is therefore relevant for the entire organisation, not just IT. However, low-code can pave the way for this, as it is already characterised by the reusability of modular components. The modular principle not only simplifies and shortens development, but also enables the flexible adaptation and scaling of applications, processes or complete application landscapes. This lays the foundation for organisations that operate in volatile business environments and need to increase their resilience. Low-code acts as a catalyst for building a composable business.

Low-code platforms, such as those from Mendix, also offer tried-and-tested modules that are available in the Marketplace. The community of experienced partners and ISVs (Independent Software Vendors) provide a large selection of customisable out-of-the-box solutions.

Nothing works without artificial intelligence

Nobody can ignore artificial intelligence and generative AI (GenAI) anymore, that much is clear. However, many questions arise for interested companies: Which regulations need to be observed? What added value can AI create in which areas? How do employees need to be trained?

AI is already an important component of holistic low-code platforms, from which companies can benefit directly in order to develop intelligent applications. This is referred to as “AI-enabled” development. This means that the productivity of developers is improved, for example through the use of bots that act as co-developers. On the other hand, there is talk of “AI-enhanced” applications that use AI functionalities to optimise user productivity. These AI functions can be AI services from third-party providers such as AWS or OpenAI, but also self-trained ML models.

Driving innovation with low-code

Low-code is used in the most complex use cases as a key driver of digital transformation and has therefore developed into a core technology that is used in many industries – in manufacturing as well as in retail, the public sector and the financial world.

Low-code does not exclude development with high-code, but can go hand in hand with it – for future-proof applications with a high level of user-friendliness and optimised added value. The shortcomings of outdated core systems and monoliths can also be overcome – in order to realise a modern IT infrastructure that fulfils all business requirements and remains scalable for the requirements of tomorrow.

Low-code democratises and significantly accelerates development. This not only allows IT budgets to be deployed in a more targeted manner and costs to be saved, but also enables entire ecosystems to be digitalised and sustainably transformed. When IT teams no longer spend their resources solely on keeping up with day-to-day tasks and employees can work more efficiently thanks to automated workflows because repetitive tasks are eliminated, there is also time for innovation.

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Driving business success in today’s data-driven world through data governance

Source: Finance derivative

Andrew Abraham, Global Managing Director, Data Quality, Experian

It’s a well-known fact that we are living through a period of digital transformation, where new technology is revolutionising how we live, learn, and work. However, what this has also led to is a significant increase in data. This data holds immense value, yet many businesses across all sectors struggle to manage it effectively. They often face challenges such as fragmented data silos or lack the expertise and resources to leverage their datasets to the fullest.

As a result, data governance has become an essential topic for executives and industry leaders. In a data-driven world, its importance cannot be overstated. Combine that with governments and regulatory bodies rightly stepping up oversight of the digital world to protect citizens’ private and personal data. This has resulted in businesses also having to comply e with several statutes more accurately and frequently.

We recently conducted some research to gauge businesses’ attitudes toward data governance in today’s economy. The findings are not surprising: 83% of those surveyed acknowledged that data governance should no longer be an afterthought and could give them a strategic advantage. This is especially true for gaining a competitive edge, improving service delivery, and ensuring robust compliance and security measures.

However, the research also showed that businesses face inherent obstacles, including difficulties in integration and scalability and poor data quality, when it comes to managing data effectively and responsibly throughout its lifecycle.

So, what are the three fundamental steps to ensure effective data governance?

Regularly reviewing Data Governance approaches and policies

Understanding your whole data estate, having clarity about who owns the data, and implementing rules to govern its use means being able to assess whether you can operate efficiently and identify where to drive operational improvements. To do that effectively, you need the right data governance framework. Implementing a robust data governance framework will allow businesses to ensure their data is fit for purpose, improves accuracy, and mitigates the detrimental impact of data silos.

The research also found that data governance approaches are typically reviewed annually (46%), with another 47% reviewing it more frequently. Whilst the specific timeframe differs for each business, they should review policies more frequently than annually. Interestingly, 6% of companies surveyed in our research have it under continual review.

Assembling the right team

A strong team is crucial for effective cross-departmental data governance.  

The research identified that almost three-quarters of organisations, particularly in the healthcare industry, are managing data governance in-house. Nearly half of the businesses surveyed had already established dedicated data governance teams to oversee daily operations and mitigate potential security risks.

This strategic investment highlights the proactive approach to enhancing data practices to achieve a competitive edge and improve their financial performance. The emphasis on organisational focus highlights the pivotal role of dedicated teams in upholding data integrity and compliance standards.

Choose data governance investments wisely

With AI changing how businesses are run and being seen as a critical differentiator, nearly three-quarters of our research said data governance is the cornerstone to better AI. Why? Effective data governance is essential for optimising AI capabilities, improving data quality, automated access control, metadata management, data security, and integration.

In addition, almost every business surveyed said it will invest in its data governance approaches in the next two years. This includes investing in high-quality technologies and tools and improving data literacy and skills internally.  

Regarding automation, the research showed that under half currently use automated tools or technologies for data governance; 48% are exploring options, and 15% said they have no plans.

This shows us a clear appetite for data governance investment, particularly in automated tools and new technologies. These investments also reflect a proactive stance in adapting to technological changes and ensuring robust data management practices that support innovation and sustainable growth.

Looking ahead

Ultimately, the research showed that 86% of businesses recognised the growing importance of data governance over the next five years. This indicates that effective data governance will only increase its importance in navigating digital transformation and regulatory demands.

This means businesses must address challenges like integrating governance into operations, improving data quality, ensuring scalability, and keeping pace with evolving technology to mitigate risks such as compliance failures, security breaches, and data integrity issues.

Embracing automation will also streamline data governance processes, allowing organisations to enhance compliance, strengthen security measures, and boost operational efficiency. By investing strategically in these areas, businesses can gain a competitive advantage, thrive in a data-driven landscape, and effectively manage emerging risks.

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The Benefits of EV Salary Sacrifice: A Guide for Employers and Employees

As the UK government continues to push for greener initiatives, electric cars have become increasingly popular. The main attraction for both employers and employees is the EV salary sacrifice scheme.

By participating in an EV salary sacrifice scheme, both employers and employees can enjoy cost savings and contribute to environmental sustainability along the way! This article will delve into the specifics of how these schemes operate, the financial advantages they offer, and the broader positive impacts on sustainability.

We will provide a comprehensive overview of the mechanics behind EV salary sacrifice schemes and discuss the various ways in which they benefit both employees and employers, ultimately supporting the transition to a greener future in the UK.

What is an EV Salary Sacrifice Scheme?

An EV salary sacrifice scheme is a flexible financial arrangement that permits employees to lease an EV through their employer. The key feature of this scheme is that the leasing cost is deducted directly from the employee’s gross salary before tax and National Insurance contributions are applied. By reducing the taxable income, employees can benefit from substantial savings on both tax and National Insurance payments. This arrangement not only makes EVs more affordable for employees but also aligns with governmental incentives to reduce carbon emissions.

For employers, implementing an EV salary sacrifice scheme can lead to cost efficiencies as well. The reduction in National Insurance contributions on the employee’s reduced gross salary can offset some of the costs associated with administering the scheme. Additionally, such programmes can enhance the overall benefits package offered by the employer, making the company more attractive to prospective and current employees.

Benefits for Employees

1. Tax and National Insurance Savings

By opting for an EV salary sacrifice scheme, employees can benefit from reduced tax and National Insurance contributions. Since the lease payments are made from the gross salary, the taxable income decreases, resulting in substantial savings.

2. Access to Premium EVs

Leading salary sacrifice car schemes often provide access to high-end electric vehicles that might be otherwise unaffordable. Employees can enjoy the latest EV models with advanced features, contributing to a more enjoyable and environmentally friendly driving experience.

3. Lower Running Costs

Electric vehicles typically have lower running costs compared to traditional petrol or diesel cars. With savings on fuel, reduced maintenance costs, and exemptions from certain charges (such as London’s Congestion Charge), employees can enjoy significant long-term financial benefits.

4. Environmental Impact

Driving an electric vehicle reduces the carbon footprint and supports the UK’s goal of achieving net-zero emissions by 2050. Employees can take pride in contributing to a cleaner environment.

Benefits for Employers

1. Attract and Retain Talent

Offering an EV salary sacrifice scheme can enhance an employer’s benefits package, making it more attractive to potential recruits. It also helps in retaining current employees by providing them with valuable and cost-effective benefits.

2. Cost Neutrality

For employers, EV salary sacrifice schemes are often cost-neutral. The savings on National Insurance contributions can offset the administrative costs of running the scheme, making it an economically viable option.

3. Corporate Social Responsibility (CSR)

Implementing an EV salary sacrifice scheme demonstrates a commitment to sustainability and corporate social responsibility. This can improve the company’s public image and align with broader environmental goals.

4. Employee Well-being

Providing employees with a cost-effective means to drive electric vehicles can contribute to their overall well-being. With lower running costs and the convenience of driving a new EV, employees may experience reduced financial stress and increased job satisfaction.

How to Implement an EV Salary Sacrifice Scheme

1. Assess Feasibility

Evaluate whether an EV salary sacrifice scheme is feasible for your organisation. Consider the number of interested employees, potential cost savings, and administrative requirements.

2. Choose a Provider

Select a reputable provider that offers a range of electric vehicles and comprehensive support services. Ensure they can handle the administrative tasks and provide a seamless experience for both the employer and employees.

3. Communicate the Benefits

Educate your employees about the advantages of the scheme. Highlight the financial savings, environmental impact, and access to premium EV models. Provide clear guidance on how they can participate in the programme.

4. Monitor and Review

Regularly review the scheme’s performance to ensure it continues to meet the needs of your employees and the organisation. Gather feedback and make adjustments as necessary to enhance the programme’s effectiveness.

Conclusion

The EV salary sacrifice scheme offers a win-win situation for both employers and employees in the UK. With significant financial savings, access to premium vehicles, and a positive environmental impact, it’s an attractive option for forward-thinking organisations. By implementing such a scheme, employers can demonstrate their commitment to sustainability and employee well-being, while employees can enjoy the benefits of driving an electric vehicle at a reduced cost.

Adopting an EV salary sacrifice scheme is a step towards a greener, more sustainable future for everyone.

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Machine Learning Interpretability for Enhanced Cyber-Threat Attribution

Source: Finance Derivative

By: Dr. Farshad Badie,  Dean of the Faculty of Computer Science and Informatics, Berlin School of Business and Innovation

This editorial explores the crucial role of machine learning (ML) in cyber-threat attribution (CTA) and emphasises the importance of interpretable models for effective attribution.

The Challenge of Cyber-Threat Attribution

Identifying the source of cyberattacks is a complex task due to the tactics employed by threat actors, including:

  • Routing attacks through proxies: Attackers hide their identities by using intermediary servers.
  • Planting false flags: Misleading information is used to divert investigators towards the wrong culprit.
  • Adapting tactics: Threat actors constantly modify their methods to evade detection.

These challenges necessitate accurate and actionable attribution for:

  • Enhanced cybersecurity defences: Understanding attacker strategies enables proactive defence mechanisms.
  • Effective incident response: Swift attribution facilitates containment, damage minimisation, and speedy recovery.
  • Establishing accountability: Identifying attackers deters malicious activities and upholds international norms.

Machine Learning to the Rescue

Traditional machine learning models have laid the foundation, but the evolving cyber threat landscape demands more sophisticated approaches. Deep learning and artificial neural networks hold promise for uncovering hidden patterns and anomalies. However, a key consideration is interpretability.

The Power of Interpretability

Effective attribution requires models that not only deliver precise results but also make them understandable to cybersecurity experts. Interpretability ensures:

  • Transparency: Attribution decisions are not shrouded in complexity but are clear and actionable.
  • Actionable intelligence: Experts can not only detect threats but also understand the “why” behind them.
  • Improved defences: Insights gained from interpretable models inform future defence strategies.

Finding the Right Balance

The ideal model balances accuracy and interpretability. A highly accurate but opaque model hinders understanding, while a readily interpretable but less accurate model provides limited value. Selecting the appropriate model depends on the specific needs of each attribution case.

Interpretability Techniques

Several techniques enhance the interpretability of ML models for cyber-threat attribution:

  • Feature Importance Analysis: Identifies the input data aspects most influential in the model’s decisions, allowing experts to prioritise investigations.
  • Local Interpretability: Explains the model’s predictions for individual instances, revealing why a specific attribution was made.
  • Rule-based Models: Provide clear guidelines for determining the source of cyber threats, promoting transparency and easy understanding.

Challenges and the Path Forward

The lack of transparency in complex ML models hinders their practical application. Explainable AI, a field dedicated to making models more transparent, holds the key to fostering trust and collaboration between human and machine learning. Researchers are continuously refining interpretability techniques, with the ultimate goal being a balance between model power and decision-making transparency.

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