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IT security trends in 2024

As much as we would like it, the number of cyber attacks will not be going down any time soon, on the contrary, companies must prepare for the fact that it can affect them anytime!  As change is constant in the technology market, the cybersecurity landscape is also dynamic and subject to rapid changes. Therefore, it’s required for companies to undertake and review their security action as a top priority along with focusing on their ability to check and secure their blind spots and strengthen their IT security. Below is the list of some general areas that have been important in recent years, and are continuing to be relevant in 2024:

Zero Trust Security Model: The Zero Trust approach, which assumes no trust within or outside the network, is likely to gain more prominence as organizations strive to enhance their security posture. At its core, Zero Trust is founded on the principle of never trusting and always verifying. Unlike traditional security models that rely on perimeter defenses, Zero Trust assumes that threats can originate from both external and internal sources. Every user, device, and application is treated as potentially untrusted, requiring continuous authentication and authorization. Zero Trust addresses the shortcomings of perimeter-based security, offering a more resilient and adaptive approach to protect sensitive data and systems. Several major companies have successfully implemented Zero Trust, showcasing its effectiveness in diverse industries.

 

Artificial Intelligence and Machine Learning in Security: AI and ML are being used to enhance threat detection and response capabilities. As attacks become more sophisticated, these technologies can help in identifying patterns and anomalies. and help improve the efficiency and effectiveness of cybersecurity efforts by automating tasks, detecting threats in real time, and providing proactive defense mechanisms against a wide range of security challenges.

 

IoT Security: Securing these devices requires a holistic approach that addresses both technical and operational aspects. As the number of connected devices continues to grow, ensuring robust IoT security measures is essential to protect users’ privacy and prevent potential disruptions caused by security breaches.

 

Ransomware Protection: Ransomware attacks have been a significant threat, and organizations will likely continue to invest in advanced measures to protect against and recover from ransomware incidents.

 

Identity and Access Management (IAM): Strengthening IAM controls will remain a focus area to ensure that only authorized individuals have access to sensitive data and systems.

 

Endpoint Security: As remote work becomes more common, securing endpoints (devices like laptops, smartphones, etc.) will be crucial to prevent security breaches.

 

Regulatory Compliance: As data protection regulations evolve, organizations will need to stay compliant with existing and new regulations, which may influence security strategies.

 

Remember that the field of cybersecurity is rapidly evolving,and new trends and technologies may emerge. Staying informed, adopting a proactive security posture, and continuously improving security measures are key components of an effective ransomware protection strategy.

 

Maximizing Efficiency and Profits with Big Data: The Role of Advanced Analytics in Driving Data-Driven Decisions

In the world of big data and advanced analytics, insights are no longer just numbers on a screen, but powerful tools that can drive real action and propel businesses forward. In today’s fast-paced digital landscape, big data and advanced analytics have become the secret weapons for businesses looking to make informed decisions that drive success. As every click, swipe, and transaction generates a wealth of information, businesses have an unprecedented opportunity to transform raw data into actionable insights. From predicting consumer behavior to optimizing operational strategies, the power of leveraging big data is simply mind-boggling. In this blog post, we’ll explore how organizations can harness the power of big data and advanced analytics by combining cutting-edge technology with strategic decision-making.

 

In business, the term “big data” generally refers to data sets so large and complex that traditional data processing applications are inadequate. Advanced analytics is the process of extracting value from big data through the use of techniques such as artificial intelligence (AI), machine learning, and predictive modeling. When used together, big data and advanced analytics can help organizations make better-informed decisions by providing insights that would otherwise be hidden in huge data sets. For example, a retail organization might use big data and advanced analytics to identify patterns in customer behavior in order to make recommendations about product stocking and pricing.

Organizations that are able to effectively leverage big data and advanced analytics will have a significant competitive advantage in today’s marketplace.

 

Understanding the Benefits of Leveraging Big Data and Advanced Analytics

 

As organizations face increasing pressure to compete in today’s digital economy, they are turning to big data and advanced analytics to help them make better, faster decisions. By leveraging the power of big data and advanced analytics, organizations can gain a competitive edge by understanding their customers better, improving operational efficiency, and making better decisions.

Big data is often described as high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced insights and decision-making. Advanced analytics is a term used to describe a range of analytical techniques that can be applied to big data sets to uncover hidden patterns, correlations, and other insights.

 

Organizations can use big data and advanced analytics to improve their understanding of customers and markets, optimize their operations, and make better decisions. For example, by analyzing customer purchase history data, organizations can identify trends and develop targeted marketing campaigns. By analyzing manufacturing data, organizations can identify process improvements that will lead to increased efficiency and quality.

The benefits of leveraging big data and advanced analytics are many, but there are some challenges that need to be considered as well. These challenges include ensuring data quality and governance, managing organizational change, and developing the necessary skillsets. Despite these challenges, the benefits of using big data and advanced analytics far outweigh the challenges.

 

Identifying the Right Questions to Ask When Leveraging Big Data and Advanced Analytics

 

Organizations are sitting on a wealth of data, but often struggle to make sense of it and drive actionable insights. Big data and advanced analytics can help turn this data into insights that inform decision-making, but only if organizations ask the right questions, such as:

  • What business problem are we trying to solve?
  • What are our goals?
  • What metric will we use to measure success?
  • Who is the target audience?
  • What type of insights are we looking for?
  • What data do we have available?
  • How can we best visualize the data?
  • What analytical methods will we use?

 

Asking these questions can help organizations better understand their data and what they want to achieve with it. With a clear understanding of their goals, they can then develop a plan to turn their data into actionable insights.

 

Strategies for Collecting Data to Support Decision-Making

 

There are a variety of data collection strategies that can be employed to support decision-making, and the most appropriate strategy will depend on the specific situation and data requirements. Some common strategies for collecting data include surveys, interviews, focus groups, observations, and secondary data sources.

 

Analyzing the Data to Generate Insights

 

Big data and advanced analytics are increasingly being used to drive data-driven decisions. However, before insights can be gleaned from data, it must be properly analyzed. This process begins with understanding the business problem that needs to be solved and then determining which data sets can provide the most relevant information. Once the data has been collected, it must be cleaned and organized so that it can be effectively analyzed.

 

There are a variety of methods that can be used to analyze data, including statistical analysis, machine learning, and text mining. The most appropriate method will depend on the nature of the data and the business problem that needs to be solved. However, no matter which method is used, the goal is always to generate insights that can help inform decision-making.

 

 Statistical analysis is often used to identify relationships between different variables in a data set. For example, if sales of a particular product are being analyzed, statistical analysis could be used to identify whether there is a relationship between sales of the product and other factors such as advertising spend or changes in consumer behavior.

Machine learning is a more advanced form of data analysis that can be used to identify patterns in data sets too large for humans to discern. This technique is often used in fraud detection or identifying customer churn risk.

Text mining is a type of data analysis that focuses on extracting information from unstructured text data. This could include things like social media posts or customer reviews.

 

Taking Action Based on the Insights

 

Organizations are under constant pressure to improve performance and achieve their desired outcomes. To meet these goals, they rely on data-driven decision-making. In fact, a recent study by McKinsey Global Institute found that data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain them, and 19 times as likely to be profitable as compared to their less data-driven counterparts.

Despite the clear advantages of being data-driven, many organizations struggle to leverage big data and advanced analytics to drive their decision-making. This is often due to a lack of understanding of how to best use these tools. As a result, organizations either don’t use them at all or only use them for narrow tasks such as marketing campaigns or fraud detection.

To truly reap the benefits of big data and advanced analytics, organizations need to take a holistic approach that encompasses the entire organization from top to bottom. Only then can they make decisions that are based on insights gleaned from all of their data. Once an organization has decided to take a holistic approach to data-driven decision-making, it needs to put in place the necessary infrastructure. This includes ensuring that there is clean and accurate data, setting up the right governance framework, and establishing processes and tools for analyzing the data.

 

With the right infrastructure in place, organizations can then start using their big data and advanced analytics capabilities to drive real business results.  Businesses should take steps to ensure they have the right systems in place to collect and analyze their big data so they can capitalize on all of its potential benefits. We at Xorlogics, help companies to embark on their digital journey so they can unlock new opportunities for growth and innovation within their organization!

 

The role of AI-driven Forecast Models in Business Operations

 

In today’s fast-paced business landscape, organizations are constantly seeking innovative ways to optimize their operations and unlock hidden sources of value. Artificial Intelligence (AI) has emerged as a game-changer, revolutionizing various industries with its data-driven insights & predictive capabilities. AI-driven forecast models, in particular, have the potential to transform how businesses make decisions and operate efficiently. In this article, we will explore the power of AI-driven forecast models and their impact on enhancing operational efficiency and value creation.

What are AI-driven forecast models?

AI-driven forecast models are advanced analytical tools that leverage machine learning algorithms and data analysis techniques to predict future outcomes based on historical data patterns. These models can process vast amounts of structured and unstructured data, learning from historical trends and making accurate predictions about future events.

 

The Role of AI in Operations

AI plays a crucial role in transforming traditional operational processes. By analyzing complex datasets at unparalleled speeds, AI-driven forecast models empower businesses to make well-informed decisions promptly. They enable organizations to proactively address challenges and opportunities, thereby optimizing various aspects of their operations.

 

  • Extracting insights from vast data: One of the primary advantages of AI-driven forecast models is their ability to process and analyze vast amounts of data from multiple sources. Businesses can gain valuable insights from this data, allowing them to identify patterns, trends, and correlations that were previously hidden or too complex to discover using conventional methods.

 

  • Improving accuracy and reducing errors: AI-driven forecast models boast exceptional accuracy levels when predicting future outcomes. By minimizing human intervention, these models eliminate the risk of human errors and biases, providing reliable and consistent forecasts. Organizations can rely on these predictions to make better decisions and allocate resources more effectively.

 

  • Allocating resources effectively: Resource allocation is a critical aspect of operational management. AI-driven forecast models can help organizations optimize resource allocation by analyzing historical data and predicting demand patterns. This enables businesses to allocate their resources efficiently, ensuring that they meet customer demands while minimizing waste and unnecessary costs.

 

  • Inventory management and supply chain optimization: AI-driven forecast models revolutionize inventory management by predicting demand fluctuations and inventory needs accurately. With this information, businesses can streamline their supply chains, reducing inventory holding costs and avoiding stockouts or overstock situations.

 

  • Predicting customer preferences: Understanding customer behavior is vital for businesses to tailor their products and services to meet customers’ preferences effectively. AI-driven forecast models analyze customer data and behavior to predict trends and preferences, helping organizations stay ahead of the competition and retain their customer base.

 

  • Anticipating market trends: In a dynamic marketplace, predicting market trends is crucial for business survival and growth. AI-driven forecast models leverage historical data and market indicators to anticipate upcoming trends, enabling organizations to respond proactively to changing market conditions and gain a competitive advantage.

 

  • Real-time monitoring and detection: AI-driven forecast models facilitate real-time monitoring of operations, enabling organizations to identify inefficiencies promptly. With instant alerts and insights, businesses can take immediate corrective actions, preventing potential disruptions and enhancing operational efficiency.

 

  • Implementing corrective actions: By pinpointing operational inefficiencies, AI-driven forecast models guide organizations in implementing targeted corrective actions. Whether it’s optimizing production processes or improving customer service, these models provide valuable recommendations to enhance overall operational performance.

 

  • Streamlining processes with AI: AI-driven forecast models can streamline complex processes within an organization, reducing manual intervention and associated time delays. By automating repetitive tasks, businesses can free up resources and focus on strategic decision-making, driving efficiency and productivity.

 

  • Automating repetitive tasks: AI automation streamlines routine tasks, enabling employees to concentrate on high-value activities that require human creativity and problem-solving skills. Automation also minimizes the risk of errors, leading to increased productivity and cost savings for businesses.

 

The Future of AI-Driven Forecast Models

 

  • Advancements and potential applications: As AI technology continues to evolve, so will AI-driven forecast models. Advancements in machine learning algorithms, computing power, and data availability will unlock new possibilities for forecasting accuracy and expand the range of applications across industries.

 

  • Ethical considerations in AI adoption: As AI-driven forecast models become more ubiquitous, ethical considerations become critical. Organizations must adhere to ethical guidelines and principles to ensure responsible AI deployment, safeguarding against potential negative impacts on society and the workforce.

 

Conclusion

AI-driven forecast models are a transformative force in today’s business landscape. By leveraging vast amounts of data and powerful algorithms, these models enable businesses to optimize operations, enhance decision-making, and unlock multiple sources of value. As organizations embrace AI’s potential, they must also address challenges related to data privacy, bias, and ethical considerations to harness the true power of AI-driven forecast models.

How Technology can Enhance and Elevate Business & Employee Performance?

Technology has been advancing at an ever-increasing rate over the past few decades, and it has had a profound impact on how we live our lives. It’s no wonder, then, that technology is also having a huge impact on performance and enhancingperformance in both individuals and teams. Nowadays, the high level of performance is achieved by automating repetitive tasks, providing real-time feedback and analysis, facilitating communication and collaboration, enabling remote work, increasing efficiency and accuracy, and providing access to a wealth of information and resources. Additionally, emerging technologies such as artificial intelligence and machine learning are continuously helping to optimize and streamline complex processes & operations and decision-making leading to better outcomes and increased productivity within companies.

 

Below are the most common technologies that are used to enhance business performance, including:

 

  • Cloud computing: Provides access to on-demand computing resources, allowing businesses to scale up or down quickly, reduce costs, and increase flexibility.
  • Big data analytics: Is helping businesses make more informed decisions by analyzing large data sets to identify trends and patterns.
  • Artificial intelligence and machine learning: Helping business to automate routine tasks, make predictions, and optimize processes to improve efficiency and productivity. If integrated correctly, AI and AL can play a significant role in performance enhancement by analyzing vast amounts of data to identify patterns and insights to make predictions that humans may not be able to detect. For example, AI and ML can be used to optimize manufacturing processes, predict equipment failures, and analyze customer behavior to improve marketing strategies.
  • Internet of Things: These technologies are used to collect and analyze data from connected devices, providing insights into performance and enabling proactive maintenance.
  • Customer relationship management software: CRM software can help businesses manage customer interactions, improve customer service, and identify new opportunities for growth.
  • Collaboration and communication tools: These tools can help teams work together more effectively, whether they are in the same office or working remotely.

By leveraging these technologies, businesses can streamline processes, increase efficiency, and gain a competitive edge, resulting in increased revenue, profitability, and customer satisfaction.

How Technology can Enhancing and Elevate Business & Employee Performance?

Let’s now have a look on the most common technologies that are used to boost employee performance, these include:

 

  • Performance management software: This type of software can help track employee progress, set goals, and provide feedback and coaching to improve performance.
  • Learning management systems: These systems can help employees acquire new skills and knowledge through online courses, webinars, and other forms of e-learning.
  • Employee engagement platforms: These platforms can provide a forum for employee feedback, recognition, and collaboration, helping to increase employee motivation and satisfaction.
  • Data analytics and reporting tools: These tools can help managers track key performance metrics, identify areas for improvement, and make data-driven decisions.
  • Collaboration and communication tools: These tools can enable employees to work together more effectively, whether they are in the same office or working remotely.
  • Personal productivity tools: These tools can help employees manage their time and tasks more efficiently, reducing stress and improving work-life balance.

By leveraging these technologies, organizations can create a more engaging, productive, and efficient work environment, resulting in higher employee satisfaction, retention, and overall business performance.

It Takes Next Level Preparation to Achieve the Best of Your Cloud Migration

a cloud migration steps

Nothing is built for eternity in IT. Applications that were state-of-the-art ten years ago no longer meet the needs of agile enterprises. Every day, industry leaders are competing with digital upstarts that develop their business exclusively in the cloud. To fight this battle, Innovative CIOs are therefore migrating their applications and data management to the cloud.

They want to benefit from the flexibility, diversity, security, and scalability of powerful and highly available cloud services for their digital transformation. But you only unlock these potentials if you prepare yourself and your IT departments well enough. Here below is a five-step preparation to respond to the demand.

 

  1. Question everything and rediscover your business

Do not leave one stone on the other and analyze all previous processes. Ask the right questions: What needs to change? What are the consequences of migrating certain applications to the cloud? Which adjustments are necessary for the work processes, the responsibilities? Take all departments with you on your journey. As cloud migration means much more than the introduction of new technology, the entire organization to the last employee must understand where the journey is going, what is being done, and what needs to change. Rather, it means developing into an agile organization because the cloud also works with agile methods, since every four to six weeks is an update. So, a company is constantly benefiting from new and best practice solutions when it is ready to adapt. To keep pace with this rapidly changing infrastructure, the new cloud services need to be designed and implemented so that you and all departments move at the same pace. For many companies, this is a significant change.

 

  1. Define agile business processes to unlock all of the cloud potentials

If you have not yet established agile work processes, you will need to introduce them with cloud migration at the latest. Because the effects of constant updates circulate in all areas. The departments also need to be more agile to ensure continuous integration of new features. You need to involve senior executives in prioritizing and approving. The specialist departments and project teams will have to collaborate in the future like an interconnecting gearbox in a single machine. As the development tool spins faster to support agile processes, it also forces everyone else to spin faster. This may be annoying at first, but the long-term benefits will be enormous. The organization as a whole becomes more agile, which speeds up day-to-day operations and workflows. Product development, marketing, and sales can react much faster to market opportunities and competitive pressure. Developers can quickly implement new features to meet important customer needs. Thanks to the scalability of cloud applications, they can optimize IT investments along with the services they request.

 

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  1. Think networked in processes, technologies and especially in people

In the face of agile and accelerated processes, cloud migration is never just a technology introduction, but always a change process for the entire company. Ask about the effects on people and processes: which people are directly, and which are indirectly affected? Who needs to be hired and who needs further education? What effects does this have on the ongoing processes? In order to handle the three dimensions of people, processes, and technology equally, you need a change in the current management method.

 

  1. Set priorities and start with the easy-to-reach Quick Wins

The implementation of cloud migration is a complex challenge in which some tasks are highly useful and can be implemented quicker. Other areas, however, have a low benefit and require high expenditures. Prioritize all tasks with an XY matrix, where you divide the quadrants into high and low utility and low and high overhead. Then start with the implementation with the tasks that offer a high utility value with little effort. Such “quick wins” give their project energy and help to convince the skeptics. Tasks with little benefit and high effort can postpone your entire project. The intervening tasks should be sorted according to the organizational needs.

 

  1. Formulate your vision with clear goals and document your concept

Many cloud projects begin with an informal discourse that quickly brings about much agreement. It is better, however, to document the concept and to define the key factors in it. For example, a cloud migration project needs a vision with clear goals for the next one, three, and five years. Describe the benefit for your business and how it will evolve. Create a roadmap that defines competency progress and milestones. Sketch the solution architecture for full implementation and how your business will transform along the way. This document provides guidance to all project participants in the implementation process and ensures the long-term success of your company on the path to digital transformation.

 

Covid19: Things We’ve Learned About #CloudComputing, So Far

 

Things We've Learned About #CloudComputing, So Far

In a remarkably short period of time, cloud computing has moved from a marginal to a fundamental element of IT operations. Thus, in just ten years, CIOs were presented with an opportunity to break the rules and create a new model for the implementation of IT. IDC forecasted cloud infrastructure spending to grow 12.9% to $74.6 billion for 2021 and Gartner expects the cloud computing industry to grow a trillion-dollar value in 2022. While cloud computing is essential in the IT strategy, it’s good to highlight where the cloud has brought benefits and in which areas companies still have to improve.

Let’s find below which strategies are working and where there is still work to be done.

 

The practice of cloud computing to bridge gaps in services

Cloud computing should be seen as a form of flexible outsourcing. It is only one vector among others for the provision of services. In computing on demand, what matters is how the company subscribes to services and benefits, not how they are delivered.

Cloud computing has the advantage of offering a very different model from the traditional ways of purchasing enterprise computing, where an ISD would acquire hardware and software for a specific location. This may be appropriate for services limited to a regional market but can encounter problems of latency at the global level. This can be very problematic, especially if you are managing IT for a highly transactional business such as a financial institution, or if you ship large amounts of data. The cloud enables CIOs to ease these performance issues by purchasing on-demand computing to create omnipresent service delivery.

You can rely on the third party to provide the diverse service you need, while they, as an expert, have the capability to deliver peak capabilities and performance where and when you need it.  As a CIO, you can expect the platform to work and be available. Now, many IT executives will do their best to avoid possessing new physical hardware, while being assured that the service will be well provided. The cloud enables IT managers to take a step towards hosting and achieve high levels of backup and security for a defined fee.

 

Adopt a cloud computing mindset

A company must have a long-term goal to migrate as much IT capacity to the cloud as it provides a cost-effective way to gain access to new skills and expertise. It can be difficult to keep in touch with all the innovations associated with the cloud; so, make sure to spend enough time brainstorming and talking with future IT professionals to get an idea of ​​future changes. They are probably more aware of the next big phenomenon that will affect the company. The culture that surrounds IT management is evolving, and that’s why you have to take a look at the new services that are available on the market and encourage employees to adopt a mindset favoring cloud computing.

However, a migration to the cloud must be carefully managed, including governance and information security. By definition, major providers (such as Amazon and Google) should be much better at securing data. However, CIOs need to be aware that convincing the rest of the company of the benefits of cloud computing can be a slow process, particularly with regard to governance, security, and approval issues.

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Let the cloud take care of core domains

Cloud computing integration must bring a tremendous solution to your organization’s operational challenge. The starting point concerns a number of core areas that CIOs can easily deliver on-demand. If you are using products such as Salesforce and Office 365, you’d have to be crazy to want to host them yourself. Better to let someone else, an expert in this field, take charge of your operational concerns. The cloud also serves as a one-time solution to problems involving certain operational projects.

 

Finding a balance and determining how to manage legacy systems

IT managers would be foolish to dismiss cloud computing, if only in terms of the quality of the service. However, while businesses will continue to migrate on-demand services, much remains to be done. We’ve noticed that some companies are opting ​​for an on-demand model and there are others that buy more internal resources.

For CIOs, moving to an on-demand model can be a headache. You have your systems inherited and at some point, you will have to consider migrating these services to cloud computing, but it’s possible, as the momentum is in favor of computing demand, despite persistent concerns about security and governance.

 

Security and Privacy

The main challenge to cloud computing is how it addresses the security and privacy concerns of businesses thinking of adopting it. The fact that the valuable enterprise data will reside outside the corporate firewall raises serious concerns. Hacking and various attacks on cloud infrastructure are affecting multiple (potential) clients. These risks can be mitigated by using security applications, encrypted file systems, data loss software, and buying security hardware to track unusual behavior across servers.

 

Reliability and Availability

Cloud providers still lack round-the-clock service; this results in frequent outages. It is important to monitor the service being provided using internal or third-party tools. It is vital to have plans to supervise usage, SLAs, performance, robustness, and business dependency of these services.

4 Cloud Computing myths, debunked

Flexibility, scalability, and long-term business resilience are the huge boost to cloud adoption. The future of the cloud is bright. Over $ 287 billion growth is expected during 2021-2025 for the global cloud computing market. Yet there are many myths surrounding the use of cloud solutions that prevent companies from taking benefits of cloud services. Even after twenty years, the use of cloud applications such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) keeps coming up against it vague fears and rejection. It’s because, in addition to data security, access and control options also play a hugely important role. Cloud solutions certainly pose certain risks for companies and their data if not managed correctly. However, many myths are way much exaggerated. In addition, many risks not only affect the cloud, but also locally operated networks.

The following misconceptions about cloud computing prevent companies from taking advantage of the cloud and have made the acceptance of cloud services particularly difficult.

 

The company will lose control over its own data

Many CIOs and IT managers or administrators often feel that they will completely lose control of companies’ sensitive data and its management once it’s migrated to the cloud. Additionally, they also carry the fear of dependence on providers as the control over the server is also given away to the cloud provider. Overall companies are particularly concerned with the location of the data and a possible loss of control over their own data. But even though they have passed the operation and maintenance of servers into third-party hands, they are and will remain the sole owner at all times and can retain all rights and control over their data and can decide independently, depending on the services used, where the company-critical backup and archiving data is stored. Because administrators and those responsible for data no longer have to worry about small details such as updates or background processes, they can spend more time optimizing the infrastructure and suitable strategies for business growth.

 

The data is not safe in the cloud

For a long time, it was believed that cloud solutions are more susceptible to attacks than the company’s own IT. Cloud services, in themselves, are exceptionally secure. However, many companies are reluctant to cloud adoption and have huge concerns about cyber-attacks, data theft, and industrial espionage. Because there is no such thing as absolute security, more and more cloud providers are creating a secure cloud for their customers. Their business model hinges on preventing breaches and maintaining public and customer trust. Additionally, all cloud providers have to comply with stringent regulations and this requires them to put robust security measures in place, including the use of strict protocols and advanced security tools. Also, the latest data centers are equipped with various security measures and offer users a guaranteed high level of security for their data.

 

Migrating to the cloud is complicated

The companies’ IT departments are often considered to be busy maintaining ongoing day-to-day operations. They don’t have enough time or know-how to modernize IT operations through the cloud. They are persuaded that migration to the cloud will come along with additional requirements, will also increase the complexity of the IT infrastructure and administrative effort. BUT every cloud provider offers their support whether it’s before or during the migration and ensures that everything runs smoothly. The greatest advantages only become visible after the conversion and cloud automation of many tasks and processes, on the one hand, it relieves computer scientists in their everyday work as they no longer have to worry about updates, backups, archiving, or the complicated maintenance of IT systems.  On the other hand, it can meet the requirements of the specialist departments faster than conventional infrastructures.

A company that plans to move its applications from a data center to a large cloud platform, must check whether their applications are cloud-ready or need to be revised before the migration. Otherwise, they’ll end up paying a high price for a platform that they cannot take full advantage of.

 

Cloud is more expensive than the in-house computing

Cloud migrations are complex projects that quickly lead to unexpected costs. As with all operating costs, it is not just the monthly cost that needs to be considered, but also the total cost of ownership (TCO). The cost of going to the cloud depends on several factors such as license obligations, data center, and the company’s ability to control and optimize cloud consumption. The big advantage of the cloud is the flexible scaling and that you only pay for the capacities that you actually use. The up-front costs of cloud migration are often significant, but the longer-term savings usually dwarf that initial cost. Choosing the right provider and achieving more performance and lower costs requires know-how and experience with the multitude of services.

 

Almost every company knows how important it is to keep up with the times in the digital age in order to remain competitive. Cloud computing is playing a vital role in responding to the challenges of these unpredictable times. The cloud is seen as a tried and tested method to achieve the necessary flexibility and agility. It has proven to be an important driver of digital transformation.

 

Sources:

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Hybrid Cloud Myths Busted

Often presented as a third path between the private cloud and public cloud, companies, consulting firms, suppliers and hosts have started to take their interest hybrid cloud. What is the hybrid cloud? There is no strict and standardized definition of what the hybrid cloud is, each player on the market (consulting firms, hosting companies…) have their own definition.

 

Hybrid-cloud-

 

For Forrester, the hybrid cloud presents itself as “an IT infrastructure model in which at least one external cloud service is integrated with an application, data source, or internalized infrastructure element”. For Gartner, “Hybrid cloud refers to policy-based and coordinated service provisioning, use and management across a mixture of internal and external cloud services”. Basically, it’s a mix use of public and private cloud which are used together to create value.

benefits of Hybrid cloud

Combining the benefits of public clouds such as agility and low cost, with the strengths of private clouds (control, performance and safety) the hybrid cloud brings the best of both technologies. These assets play an essential role in the success of companies, even if few of them still wonders what really a „hybrid cloud“ is. Two options are offered to businesses: get on the board or remain docked. To see more clearly, I propose to demystify the five major myths that usually surround the hybrid cloud.

 

Private + Public = Hybrid:

 

It is not enough to place together these two infrastructures to create a hybrid cloud. In fact, you may not gain any of the respective advantages of both types of clouds but end up multiplying the risk by both of them! First, by moving secure data to the public cloud, security breach can result in brand damage and loss of customers’ trust, and requires significant time and effort to remediate; secondly, migration of apps from a public cloud to a private cloud can lead to unexpected costs. By having a hybrid cloud, you control your workload, your network and storage resources while minimizing risk and increasing productivity.

 

A Hybrid Cloud is Complex and difficult to implement:

 

The use of complete IT solutions allows you to reduce complexity and to choose standard technology – (Microsoft, OpenStack, Vmware) on which your hybrid cloud is standardized, but also the type of public cloud with which the private cloud deployed on site by customer can interact. A complete solution accelerates three essential elements of development: – Integration of end-to-end testing to verify that all components work together; – Use of a converged infrastructure that simplifies the implementation and deployment; – Predefined plans for services, with workflows that must automate provisioning through a self-service portal.

 

The public cloud is more cost-efficient:

Cost savings via Hybrid cloud

A New study by IDG Research Services shows that if we take into account the governance issues, risk and compliance, the hybrid cloud displays in fact a lower total cost of ownership. When data or workloads migrate to the public cloud, it is easy to override local or international regulations on data protection. The local laws and requirements vary from market to market, and some are so complex that companies simply prefer to avoid public clouds. May be that’s why you may want to choose private cloud for sensitive workloads. In Germany for example, the rules on how data is stored and processed are especially strict. The solution lies in how to mix public cloud and private cloud offering each workload the advantages of one or the other, depending on their requirements.

 

On the cloud, the data control escapes you:

 

While extraction or data migration can be difficult via some particularly cloud service providers, a well-orchestrated hybrid cloud environment enable you to keep hand on your work. A well-managed hybrid cloud can provide quickly required public and private resources, provide IT departments a high level of visibility and control, as well as self-service and on demand access for developers and applications users.

 

It is difficult to know which applications are suitable for cloud:                

 

Companies are often hampered by the critical interdependencies of IT infrastructure, ignorance of their IT assets and their relationships to business applications. With a simple spreadsheet and without rigorous methodology, it’s impossible to know precisely if an application is suitable or not for cloud – and even less to know the position in a cloud architecture. Experts who use automated platforms for collecting and analyzing data can provide a complete comprehensive view of the application portfolio and tell whether you need to migrate, consolidate, modernize or simply stop the use of an application.          

 

hybrid Cloud as digital transformation

 

Even if the definition of hybrid cloud is still unclear, its undeniable benefits in terms of agility and cost reduction are now the essential model of tomorrow. Companies that are preparing or starting their digital transformation have every reason to anticipate a future adoption and now choose technologies that will integrate public and private worlds, i.e. converged infrastructure and proven software solutions.

 

Sources:

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Artificial intelligence and connected objects, trends of the upcoming years?

Artificial intelligence

Artificial intelligence, great topic of the moment? Yet the term dates back to the 1950s! AI is the term used most commonly for Artificial Intelligence. The concept is to develop computer programs that perform tasks that are normally performed by human. The goal is to give machines (robots) ability to seem like they have human intelligence. I’m pretty sure that at this point we all have seen robots doing the grunt work in factories, intelligence driverless cars, and companies are using AL to improve their product and increase sales.

 

Since 2007, Gartner has been predicting key strategic technology trends for the coming years – not an easy task considering the rapid change in the IT market. According to a classification made by Gartner, Artificial Intelligence, Big Data, Cloud Computing, sensors, connected objects, smart machines and modern 3D printing are the key trends of the years 2016-2020. Automation and artificial intelligence figure prominently in the top 10 technology trends of the future presented by Gartner at its conference Symposium / ITxpo 2015.

 

Multiple devices, mobile to electronic devices via the connected devices and sensors are the first big trend mentioned by the research company. More and more devices are becoming connected and “resulting in smarter homes, smarter cars, smarter everything. IoT is leading to a point where “no object will just be an object—it will all be wirelessly connected to something else.

 

 Gartner expects more interaction between these connected devices via different networks in the coming years and beyond (via 4G + 5G technologies). The user experience and virtual environments comes in second position. According to Gartner, this presents a big opportunity and competitive advantage to IT developers and enterprises. 3D printing are third in this ranking, which isn’t yet a mature market, but getting stronger. Thus, global shipments of 3D printers for businesses should show 64% of an average annual growth rate until 2019.

 

Information on the massive data processing era (Big Data), followed by advanced machine learning and deep learning are also on the top 10.

 

“The explosion of data sources and complexity of data classification makes traditional (manual) analysis almost impossible and unprofitable for organizations. With artificial intelligence, the chances of error are almost zero in addition to that greater precision and accuracy is achieved. Plus according to Gartner, in 2018, 20% of all business content and documents will be produced by machines.

 

Gartner have published results of a survey on the topic Big Data, artificial intelligence and the relationship between the two domains. Without further ado, here are the main results:

  • 69% of respondents says that artificial intelligence will improve with the massive use of data
  • 68% think that Big Data will be used very long term by public authorities and businesses
  • 67% believe that the Big Data presents long-term benefits for the health and well-being
  • Finally, 65% approves that they use avatars that are digital assistants who interact with the users in order to save the need of human resources.

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Artificial intelligence can provide unexpected business intelligence for organizations, enhance knowledge on their customers and improve customer interaction with the company, and in some case even replace entire departments as intelligent, learning machines perform tasks until now strictly reserved for humans. Not surprisingly, demand for solutions made possible by artificial intelligence is increasing in the private sector as well as in the public sector. “In every organization, IT experts should explore how to use intelligent agents and these autonomous connected objects to improve the activity” said David Cearley, vice -President and associated Gartner.

 

Source: Webbmedia Group – 2016 Tech Trends

Cloud computing implementaion and its benefits

This week I’ve decided to talk over cloud computing because I’ve noticed even though it’s an existing technology, talking about it is still Chinese for some people. So to better understand this IT evolution, I’ve decided to provide some explanations, based on several studies, of what’s good to know about #cloudcomputing.

 

Let’s first dive in some history because it’s important to understand where did it came from. Basically Internet exists since 1960s, but it’s only in 1990s that it showed any importance for businesses. The famous WWW “World Wide Web” was born in 1991, and in 1993 a web browser was released that allowed users to view web pages.

Since then the arrival of cloud computing has revolutionized the use of computer services in organizations. Before companies need to manage their IT assets in order to get the more out of it. Now, with cloud computing, companies can use on-demand IT services, without worrying about the infrastructure issues, security and maintenance.

 

The uses of computing in cloud are endless and there are only good reason: it’s the same as with traditional IT, except that the servers / machines that store and process information are not in the same building and are high-performance, reliable servers designed to help you grow and scale any business quickly and easily. In short, below are some uses of cloud computing:

 

  • Use of services / softwares online
  • File storages
  • Disaster recovery
  • Backup
  • Collaboration via shared workspaces and synchronous communication tools

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When I think about it, life before cloud computing was quite pain in the ass because the company’s employees used to access to IT resources (servers, applications, storage spaces …) via the internal corporate network. (Means no home working). There’s no doubt that cloud computing is enhancing out ability to work anytime anywhere.

 

If we compare, traditional enterprise applications are still too complicated and expensive. The number and variety of software and hardware required for their execution is overwhelming. A team of experts is needed to ensure the installation, configuration, testing, implementation, security and update of these software’s.
Cloud computing is the new way to work. The company’s employees are able to access to computer facilities provided by one or more cloud providers via the Internet. These infrastructures are pooled among several companies to be proposed at the lowest cost. Organizations don’t manage any hardware or software. With this kind of infrastructure you only pay for what you need, upgrades are automatic and the evolution of the system is easy. Many businesses are moving to cloud because cloud computing increases efficiency and helps improve cash flow and offers many more benefits.

 

Is implementing cloud services worth it?

“Anywhere, any device, anytime!” For cloud computing vendors the answer is obvious: yes! Companies have every incentive to put their data in clouds. For various reasons: they do not buy the product license and doesn’t need to care of updates of the software and equipment maintenance.

Other arguments: the lack of investment in major infrastructure (most of the time, the computer room one of most important part of the building to which was added an air conditioning system), a very fast service (a server can be activated in minutes) and flexibility (for IaaS and PaaS).

 

Advantages of Cloud Computing:

  • If you’ve ever implement a new applications / service, I’m pretty sure that you are aware of the time it can take. But with a cloud based application, you can cut through this complexity and use the application within no time because you don’t have to worry about maintenance or management.
  • There’s no initial investment if IT tools and no hardware maintenance
  • Costs reduction because users only pay for what they consume. Also strong economy of energy costs and cost of licenses. Also with cloud based applications organizations can increase and decrease the number of users based on your needs.
  • Reduced risk of hardware failure. Data is secured and IT is truly mobile.
  • Not to forget mobility aspect, the user can at any time and from any device connect to applications and workflow. All you need is a terminal with an Internet connection. It’s more productivity and presents a gain of time.
  • It has no size limits, so you have no worries of its capacity.
  • Data is stored securely in clouds, if in case you’ll lose your computer, you’ll never use your important information

 

How the Cloud has convinced organizations?

The number one reason is the facility of connecting their employees using a multitude of different devices. Whether it’s a computer, smartphone, laptop or tablet.

According to the McKinsey Global Survey, more than 80% of respondents indicated they are using or experimenting with cloud technology. And 27% of users affirms that cloud computing has increased the performance of their business by saving time to its employees.

Finally, 93% of users declared that they have improved the efficiency and utilization of their “data center” through the cloud.

 

The impact of cloud on the business model of companies

According to IBM, on average, the cloud helps companies to halve their operating costs. “A unified computing is a 30% cheaper service. The automation of load distribution represents 11% savings in addition to cost governance” says Ian Brooks, in charge of promoting the cloud at HP.

 

With all these information, we can conclude that cloud computing presents the boom and bust in information technology. End of 2020, 840 million people worldwide will be using “Cloud Computing” solutions and companies will be saving at least 210 billion annually.

 

Contact us if you have any question about cloud computing implementation. Our dedicated team can help you save A LOT than you can imagine.

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