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Cloud Encryption: Best practices to deal with Data Security Issues

For modern businesses, digital transformation is critical, and cloud services offer a proven path to thrive in the digital economy. However, the shared responsibility model states that the cloud service provider is responsible for the security “of” the cloud, while the customer is responsible for the security “in” the cloud, for network controls, identity and access management, application configurations, and, most importantly, data security. Although data in the cloud is often stored abroad, this data storage is the safest option for companies to store files in compliance with the GDPR thanks to end-to-end encryption.

 

Data is already in the cloud: We all know that growing amounts of data and the desire for flexibility made the cloud increasingly popular as a data storage medium. The advantages are obvious: the files hardly need any local storage space, the cloud is highly available and the data can be accessed from anywhere.

Many programs use the cloud as data storage or backup without the customers being aware of it. This happens when synchronization is set by default or when the program is specially designed for cloud use. This is the case, for example, with Microsoft Office. This is at the root of a serious privacy problem: loss of control. Eventually, information is sent to servers that are beyond the control of whoever owns the data.

 

Beware of collaboration software: Hesitations about the cloud relate primarily to the lack of data protection. Despite this, too few companies are still taking the initiative. Countermeasures are only slowly being implemented. As a result, the number of data leaks reported to Belgium’s Data Protection Authority, APD, increased significantly every year. “Over the past twelve months, reported cases of breached data have gone up to 1,529,” the newspaper cites APD spokesperson Aurélie Waeterlinckx as saying. “The year before, there were 1,232.” Many companies are aware of their security problems. But too few actively take care of the solution.

Particular caution is required when using collaboration tools: software such as Microsoft Teams enables the simple exchange of messages and files. It’s a cloud-based team collaboration software that is part of the Microsoft 365 and Office 365 suite of applications, thus the data is sent to the cloud.

 

Simple solution: always remember that your business is at the mercy of cloud file attacks or that you are in the grip of data leakage. Only then you’ll take data protection into your own hands with the most important tool: encryption.

Encryption is effective when files are still encrypted on the device on which they are created or edited. In this way, the information is protected during transmission to the cloud and during the entire storage period. You can use it to ward off attacks by ransomware and protect yourself from access by the cloud provider or foreign authorities.

Encryption is a good tool for more data security. High-quality encryption software fits seamlessly into existing workflows. This additional layer of protection is also ideal for backups. Data encryption for information stored on the cloud network makes sure that even if the data is lost, stolen, or mistakenly shared, the contents are virtually useless without the encryption key as the keys are only made available to authorized users.

Serverless: Knowing its limitations means using it properly

Serverless infrastructure advantages

“Serverless” is one of the new hype words in the IT industry. According to MarketsandMarkets Analysis, the global serverless architecture market size is projected to grow from USD 7.6 billion in 2020 to USD 21.1 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 22.7% during the forecast period. The major growth driving factors of the serverless architecture market include the rising need to shift from CAPEX to OPEX by removing and reducing the infrastructure cost. Gartner analysts also predict that half of all companies worldwide will have implemented a serverless model by 2025, compared to 20 percent today.

 

However, the term “serverless” is sometimes misunderstood. It’s not about getting rid of system hardware entirely. Rather, it’s about a new idea of ​​managing applications and apps while still carrying out basic operations as usual. In plain language, this means: With serverless, the technical, application-relevant level of system architecture is managed independently of hardware-specific issues. The app managers only take care of the top functional level or the service. The cloud platform takes care of the provisioning logic, right through to the virtualization of resources and server control, giving the app manager room for other activities.

 

Serverless computing is an architecture where a cloud provider fully manages code execution, instead of the traditional method of developing & deploying applications on servers. Gartner believes that serverless computing requires IT leaders to take an application-centric approach. Instead of physical infrastructure, interfaces for application programming (APIs) and service level agreements (SLAs) are managed. Thus, developers and businesses can run their services without carrying the burden of managing the underlying infrastructure. Pricing is based on an application’s actual resource consumption, not prepaid capacity units. Also, server management decisions and capacity planning decisions are transparent to the user.

 

Even though the entry into the world of serverless is quite easy, the complexity increases very quickly when developers want to use more sophisticated resources, such as API gateways that sit between the client and several backend services and the calls management. The more the respective company builds on serverless architectures, the greater the danger of vendor lock-in. Decision-makers should keep this in mind if they want to define a serverless strategy that allows them to avoid long-term vendor and security risks. If there is a corresponding awareness in the company, it can use the advantages of serverless without having to fear potential pitfalls.

 

You must also acknowledge that serverless architecture is not the right choice for all cases. If the designated “serverless” application requires significant scaling and generates extremely high traffic for prolonged periods of time, it can become expensive. In this case, a cheaper alternative is a computer cloud such as Amazon EC2, which provides computing capacity in the cloud. Serverless scenarios are also unsuitable for applications that require noticeably short response times, such as real-time applications.

 

The mindset of the developers must also match the specific requirements of serverless. For example, it is imperative that they have an in-depth understanding of how serverless and event-driven architectures are built. Developers must also know the specifications and limitations of the platform used and keep an eye on application and data security. The risks and consequences of implementing serverless are severe unless the benefits have been demonstrated for a specific use case and the organization has carefully considered the ultimate costs and outcomes. Decision-makers should therefore only decide on a potential switch to serverless based on a detailed cost-benefit analysis.

 

The benefits of serverless computing are increased agility, unlimited scalability, easier maintenance, lower costs, and back-end services provided by the provider. It also ensures that companies and their developers no longer must worry about the servers and their configuration. In addition, serverless computing supports multi-cloud environments and makes the pay-as-you-go model a reality. Furthermore, the serverless approach promotes the sustainability of data-supported strategies in financial terms. And that’s exactly why serverless computing is reshuffling the cards in ​​data integration. Now the possibilities in the field of data-on-demand are almost unlimited. Because companies can decide how, where, and when they process data in a way that makes economic sense for them.

Best practices for Cloud cost Optimization 

Cloud Cost Management

Cloud computing is the driver of digitization because firms expect competitive advantages and massive financial savings from moving their business to the cloud. But they are often unaware that they end up paying more for their cloud infrastructure than they have to. This is often due to a lack of cloud governance, a lack of global overview of the resulting cloud costs, and/or rising prices for increased storage capacities. A study by Gartner shows that in many cases, the cloud costs of companies are up to 70 percent higher than what they would need. This leads to massive profit losses.

Therefore, cost management for multi-cloud environments is a crucial step not to be ignored. A wide range of options is available for optimization – if they are properly understood and used. This guideline clarifies what is important and which criteria are essential.

 

Scalability and cost transparency, such as the “pay-per-use” principle common to cloud providers, are two of the main arguments in favor of the cloud. Accordingly, the cost savings for small and medium-sized companies is the main argument for migrating their IT environment to the public cloud. However, this thesis is only true if they keep an eye on the topic of cost optimization before, during, and above all after the migration. The cost-optimized use of IT resources in the cloud is only possible if the company hires someone who keeps an eye on numerous factors such as the number of users, budgets, storage space, and instances used. In other words: without someone in charge who knows what to look for in cost-optimized cloud usage and how to proceed in cases of budget overruns, it becomes expensive.

 

Waste management, identifying unused cloud resources, and avoiding unnecessary spending. It sounds easy at first, but with typically several hundred thousand cloud resources, it is not possible to find out manually which resources are not required. By comparing billing data with monitoring data, tools identify potentially redundant cloud spending. In addition, among all the hundreds of thousands of cloud resources, those that are not needed at night or at the weekend can be identified. A distinction can also be made between productive and non-productive environments. The cloud architects and DevOps teams can make informed decisions about which cloud services are redundant and which are not.

 

Workload management, The costs for virtual machines are quite different for individual providers. The designation of the workloads in the cloud, and the offers and configurations of the cloud providers also vary significantly. This makes it difficult to compare offers.

But the price of workloads isn’t the only reason to choose a provider. With ready-made cloud services, cloud providers try to bind customers to their cloud platform. And indeed, their offers may seem attractive because the provider promises to care for maintenance and updates.

To help in decision-making, tools can indicate which cloud instances are most likely to cover a given workload. Usually, there are between 40 and 50 similar configurations that could be suitable in principle. If the tool knows the configurations of existing on-premises servers, it can also determine which cloud instances they could be replaced with. This enables comparisons to be made as to which cloud offerings are most suitable in terms of price/performance ratio.

 

Rightsizing computing services, there are a number of right-sizing tools that provide more or less good suggestions for sizing cloud servers so that they are the right size for actual use. Right-Sizing also helps with cloud optimization, which means achieving peak performance from the resources you are paying for. Another special benefit of the rightsizing compared to the data center is its elasticity. This means if you need to scale up for a few days and then scale back down, you’re able to continuously right-size your infrastructure to match your needs so you’re not stuck with one size.

Physical & Cloud #DataProtection: Best Practices for your #Backup and #RecoveryProcess

Data, one of the most valuable assets of organisations. Massive data is the new currency. Thanks to advancements in technology and connectivity, data creation is skyrocketing. According to IDC, Global DataSphere Forecast, 2021-2025, the global data creation and replication will experience a compound annual growth rate (CAGR) of 23% over the forecast period, leaping to 181 zettabytes in 2025. That’s up from 64.2 zettabytes of data in 2020 which, in turn, is a tenfold increase from the 6.5 zettabytes in 2012. These data are stored in ever-increasing environments and connected devices, therefore backup and restoring the capability of an information system is a real challenge to ensure business continuity and the availability of associated data.

Volume of data created and replicated worldwide

What must IT departments do to fulfill the data security mission? Well, the data security policy is at the heart of each business concern and should be a fundamental part of their security strategy. Planned security measures can then create tactical and operational rules through the joint efforts of security and storage teams. To this end, storage must be an integral part of the company’s security strategy.

 

To achieve these objectives, a company must establish a cluster around the following five essential aspects:
• Allocation of responsibilities;
• Risk Assessment;
• Development of a data protection procedure;
• Communication of data protection procedure;
• Execution and testing of the data protection procedure.

 

  1. Allocation of responsibilities

The goal is to make storage security a fully-fledged feature of the IT security architecture. Even if the company decides that the responsibility for backup or storage security rests within the storage team, it must nevertheless integrate any safety measures in this area with task to secure the rest of the infrastructure. This integration will contribute to the establishment of in-depth protection. It is also advisable to share responsibility for extremely sensitive data. It’s, therefore, better to ensure that the person authorizing access is not the same as the person responsible for enforcement.

 

  1. Assessment of storage risks in the area of ​​IT security

#Managers must review each step of their backup methodology to identify security vulnerabilities. Can an administrator secretly make copies of backup tapes? Are they stored in boxes accessible to everyone? Is there a rigorous end-to-end monitoring chain for backup tapes? If critical data is backed up and transported, vulnerabilities of this nature could make it easy prey. If the risk analysis reveals many vulnerabilities, the company must seriously question the encryption of its data.

 

  1. Development of an information protection program that guarantees the security of company data, at all times, wherever they are

Multi-level protection should be adopted by taking existing best practices for the data network in order to apply to the storage network, while adding specific layers adapted to the characteristics of the archived data, for example:

  • Authentication: application of multi-level authentication techniques and anti-spoofing (anti-identity or address spoofing).
    • Authorizations: access rights according to roles and responsibilities (as opposed to total administrative access).

It is imperative to duplicate backup tapes because it is never good to depend on a single copy of the data. Despite the longevity of the bands, they are still exposed to environmental and physical damage. A common practice is to perform nightly backups and then store these off-site tapes without any verification. Recommended best practices include duplicating backup tapes and then storing offsite copies.

Magnetic tapes remain the preferred storage mode for backups because they are economical and offer sufficient capacity to back up an entire operating system on a single cartridge. When stored properly, archival tapes have a lifetime of more than 30 years, making them an exceptionally reliable storage medium.

 

  1. Communication of the procedure to be applied with regard to the protection and security of information

Once the procedure for protecting and manipulating sensitive data has been defined, it is important to ensure that those responsible for their safety are informed and trained. Safety rules are the most important aspect of assigning responsibilities. Functional managers need to be aware of risks, countermeasures, and costs.

Data loss and intellectual property theft affect the entire enterprise, not just the IT department. As such, the Director of Security must undertake a data security approach by training the different functional frameworks in the risks, threats and potential harms arising from security breaches, as well as the cost of the various possible countermeasures in this area. In this way, company executives can raise awareness about the cost/benefit of investments in data security.

 

  1. Implementation and testing of Data Protection and Security Plan

Securing data is not about technology but about the procedure. This is why it is essential to test the procedure. In addition, as the growth of the company is accompanied by an evolution in security and data protection needs, IT security practices must also evolve. Once the complete security plan has been developed, defined, and communicated to the concerned team, only then it’s the right time to implement it. IT team must ensure the implementation of the tools, technologies, and methodologies necessary for the classification of information. New technologies may be required to classify information or label it with metadata so that it is backed up according to appropriate rules and procedures.

Once in place, the procedure must be tested, both concerning backup and restore. The test is to introduce, into the process, any possible and imaginable danger, whether it is the loss of a tape or a server, network problems, equipment or filing of data or any other scenario which could affect the company’s performance.

It is advisable to carry out tests with personnel who are less familiar with the procedure, to ensure that it can nevertheless be applied without difficulty in the absence of the usual supervisor (due to illness, holidays or departure).

IT Spending: Further increase in 2022

Worldwide IT spending is projected to increase by 4% from 2021, according to the latest forecast by Gartner, Inc. “Governments will continue to invest heavily in digital technologies. This includes investing in improving the customer and employee experience, strengthening analytical capabilities, and increasing operational agility.

 

Even though we are witnessing inflation, the Ukraine war, high gas + electricity prices, geopolitical disturbances, and currency fluctuations, none of this is being a reason for companies to cut back their IT spending. On the contrary, the Gartner market research institute is even assuming a renewed increase. It is expected that $4.4 trillion will be spent on IT globally in 2022, which would represent a growth of 4.4% year on year.

Worldwide IT Spending Forecast 2022

 

The corona pandemic has shown us that it is important to show a high degree of flexibility, especially in turbulent times. The rapid transition of jobs to the home office would not have been feasible at all without a solid investment in IT. The market researchers from Gartner assume that companies acknowledge that the way forward is by investing in tech, and therefore will invest additional available funds in their IT. Another HR survey from Gartner reveals that 41% of employees are likely to work remotely at least some of the time post covid pandemic.

Even if the investments run through all IT areas, Gartner assumes that software solutions ($675 billion, up 9.8% from 2021; ) and IT services (at $1.27 billion, up by almost 7%) are the two fastest-growing categories that will account for the largest share in 2022.

 

Another trend can be observed in 2022, when it comes to allocating the budget for IT, more companies are focusing on modernizing existing systems than looking toward new developments. Modernization in the IT area can be understood, for example, when legacy systems and traditional processes are shifted to a modern IT operating model. As aging legacy systems can be costly and slow the pace of change, organizations are implementing technologies that include lean processes and automation, which helps them improve workload placement, and eliminate unused or underused systems. Not renewing existing core applications, but modernizing them, not only represents a financial advantage for the company, it also has a positive effect on the environmental balance.

Cloud Computing: The emergence of Digitization in medium-sized companies

 

Firms of all sizes, across all sectors, and around the globe are increasingly filling digital adoption gaps and equipping their staff with digital tools. Even small and medium-sized companies, that use to see digitization as a burden have significantly increased their digital technologies’ adoption. Already in 2021, small businesses accelerated their digital investments so they could survive prolonged COVID-19 pandemic restrictions.  According to a new update to the International Data Corporation (IDC), the global spending on the digital transformation (DX) of business practices, products, and organizations is forecast to reach $1.8 trillion in 2022, an increase of 17.6% over 2021.

 

Digitization offers great advantages, such as the development of new business areas and larger, international customer bases by integrating into global markets. Provides better and quicker access to information, and communication between staff, suppliers, and networks Digitalisation also supports innovation, generates data, and analyzes their own operations in a new way & driving improved performance. According to IDC, at least 20 percent of small businesses globally will cease operations by 2025 if they don’t digitize fast enough.

 

At this point, SMEs must embark on digital transformation projects to accelerate their post-crisis recovery but also due to the emergence of a younger, more technologically perceptive generation.

The introduction of new technologies within companies must be done with well-thought planning. A digital project is time-consuming and requires appropriate skills and know-how. The growing numbers of digital companies show that the journey is worthwhile. Zoho, the Global tech company, therefore advises small and medium-sized businesses to take the following steps on their digitization agenda:

 

Don’t ignore the power of the cloud: The time to rely on classic IT infrastructures is over for cost reasons alone: ​​Clouds are significantly cheaper in terms of value for money than legacy systems in your own company. Mainly because companies don’t have to invest in their own server infrastructure. Also, organizations don’t need to worry about data storage and protection resources and costs as the cloud world offers extensive scalability. A scalable cloud can grow and manage the increasing demands of processing, along with ensuring that data, applications, and services are available at any time and from anywhere via the Internet and updates them in real-time. Digitization can simply not be achieved without implementing the cloud into your infrastructure.

 

Sustainable technologies: The pandemic has given medium-sized companies a boost in digitization: SMEs, like all other companies, have had to react to the imposed home office requirements. However, many companies have acted hastily when it comes to software and have opted for “short-term” digitalization aka temporary isolated solutions. In order to make their working models futuristic, they must think and adopt a long-term digitalization process in order to transform their business model from analog to digital. Instead of relying on/investing in short-term solutions, SMEs must understand and enable sustainable digitalization.

 

Focus on automation: Automation has already proven its benefits in previous technological revolutions. Automation reduces the number of process interruptions and usually leads to higher performance and a lower error rate. Automation thanks to digitization is possible in every SME and is also implemented continuously. Classic examples are approval and verification processes, which can be digitized from manual tasks to rule-based, program-controlled, and thus automatic tasks. SMEs that want to digitize are well-advised to find process interruptions and to determine the cost/benefit ratio of automation through digitization. Automation should be an ongoing task considering the ever-improving digital tools.

 

Digitization is reality. Of course, also in the SME sector. And it is a challenge since it can usually only be achieved through the cooperation of several companies, partners, and companies’ own workforce. Every SME can make rapid progress with the right digitization strategy. The experts at Xorlogics will be happy to support and guide you in your company’s digital transformation project!

Intelligent Process Automation: The stepping stone to Digital Transformation

To lead in today’s economy, organizations need to rethink the way their business operates. By integrating Intelligent Process Automation (IPA), they can optimize their business processes. These include robotic process automation, machine learning through artificial intelligence, and cognitive automation. Intelligent process automation also increases speed, productivity, and innovation within the company. Additionally, it lets you anticipate the future and adapt faster with smart intelligence.

 

People in many different industries have already been exposed to intelligent process automation in different areas, whether they are aware of it or not. For example, opening a bank account, chatting with a bot on a vendor’s website, or receiving various products or service offers without interacting with a human. The automation of processes not only reduces operating and product costs and errors, improve employee performance, attracts, and develops talent, improves sustainability, and modernizes and accelerates processes. Instead of the selective optimization of processes, the most extensive automation of entire process chains within organizations is stepping up increasingly. This is exactly where intelligent process automation of the entire value chain is required.

 

Leading companies are continuously looking for intelligent process automation use cases to address the more complicated challenges in the enterprise environment and derive real value from their data. The correct use of data analytics, robotic process automation (RPA), and artificial intelligence lead to an improved customer experience, more needs-based offers, and individually optimized pricing. This strengthens the relationship between existing customers and the organization. Therefore, this leads to more product sales. Optimized pricing based on data analysis and artificial intelligence also makes it easier to exploit pricing leeway and increase margins.

 

Process automation is not a new topic, but a lot has happened technologically in the past five years. For example, diverse types of bots are available today in robotic process automation (RPA). The global RPA market size was valued at $1.40 billion in 2019 and is expected to reach $11 billion by 2027, expanding at a CAGR of 34% from 2020 to 2027 (Grand View Research). The potential economic impact of knowledge work automation is expected to be $5-7 trillion by 2025. (Automation Anywhere)

 

Overall, process automation is being pushed further, not because of economic conditions led by covid in the organizations but because of the multiple advantages it has to offer. You might ask what helps these processes run smoothly? How were they designed to be efficient? How does workflow from one function to another without glitches? The answer to all these questions lies in understanding processes, breaking them down to the smallest task step, examining the interactive flow of information in each task, and analyzing the rules governing it. To improve a process, the organization must measure and critically evaluate the effectiveness of each process. A step-by-step approach has proven to be the best practice. Starting with the automation of a sub-area using RPA, the next step can be to focus on the entire process, the connected systems, and the relevant influencing factors. So-called workflow management systems, which can map a process as an interface between data management and human interaction, offer technical support here. This gives companies a detailed overview of where and when something is happening and where there is potential for automation.

#Data : An Important Piece To “The #InternetOfThings” Puzzle

Every day, connected objects generate billions of information that must be processed and analyzed to make them usable. Thanks to the development of connectivity on multiple devices, the arrival of inexpensive sensors, and the data inflation they transmit, IoT have taken an irreplaceable place in our daily lives. IoT Analytics forecasts the IoT market size to grow at a CAGR of 22.0% to $525 billion from 2022 until 2027. The number of connected IoT devices growing 9% to 12.3 billion globally, and cellular IoT now surpassing 2 billion.

 

These very serious estimations do not, however, take into account the full extent of this digital revolution. If the design of connected objects is the showcase of the IoT and its vast possibilities, it still requires strong skills in the processing of the exploited data collected from sensors terminals, machines, and platforms to interpret it in order to boost productivity and increase performance.

 

Just as in the jewel market, the big winners are gold/diamond dealers. In the IoT domain, this role is played by companies able to manage the mountains of data generated by these connected devices because the collected data is profoundly changing the way businesses used to operate. Almost every day, new applications are imagined, with consequences at all levels of organizations because the real added value of connected objects only comes from the uses and the ability of companies to create new services.

 

Several studies demonstrate that companies are still facing a gap between the collection of new data and the presentation of the analyzed information so that it can be understood and explored in great detail, whether it is for a connected house, connected car, or a portable terminal or an industrial solution.

 

Here below is the list of tips companies must consider before every IOT project implementation:

 

  • Sort valuable information among a big volume of data:
    Exploiting IoT means generating a huge amount of data. The challenge for companies is to filter the stray information and find the ones that are really important. This is why many companies integrate a flow analysis and a process analysis. The first provides real-time information from data streams such as navigation paths, logs, and measurement data, and the second is to take machine data captures.

 

  • Set and manage priorities:
    The IoT implies different levels of necessity in terms of urgency and latency. It’s important to take this into account because one expects to interact with the “real world” in real-time. For example, sensors in mines must trigger an alert as soon as they detect the presence of toxic gases. Similarly, other IoT information may not be needed “just in time”, such as regularly collected data to further refine and improve the predictive model itself. This data can potentially be collected and processed several times a day, for example.

 

  • Design considerations for IoT technologies:
    Information security, privacy, and data protection should systematically be worked at the design stage. Unfortunately, in many cases, they are added on later once the intended functionality is in place. This not only limits the effectiveness of the added-on information security and privacy measures but also is less efficient in terms of the cost to implement them. Although industries are actively working to address this, it stays a major IoT problem.

 

  • Cross the Data:
    In the case of preventive operations, for example, companies want to collect data from objects (such as smart meters) and cross them with relevant relational data, such as maintenance agreements, warranty information, and life cycle components. It is therefore essential that companies can rely on the data from which they make important decisions.

 

  • Tracing the data:
    The increased collection of data may raise issues of authentication and trust in the objects. In addition, it should also be noted that by using information collected about and from multiple objects related to a single person, that person may become more easily identifiable and better known. So in order to fully exploit the potential of IoT, tools must be much more flexible and allow users to shape and adapt data in different ways, depending on their needs or those of their organization.

 

Collaboration between the IT team and business experts is more critical than ever before in analyzing IoT data. In addition to those who understand the data, it takes experts to analyze gathered data from specific devices or sensors. While any analyst can understand the data in the context of a company’s performance indicators, only a data specialist would be able to explain what kind of hidden data contains a wealth of information, and how with the right tools, companies can unleash that potential.

Cloud Computing: Increase Profitability and business Growth

You’ve put a lot of effort into growing your company. That’s why you should use appropriate technology for corporate management. Cost reductions, profitability, and scalability pushed the adoption of cloud computing and modern technologies within companies around the globe. Meanwhile, businesses have also realized that the cloud holds various other advantages: it enables innovation and the development of new products. As a result, it provides competitive advantages, resulting in increased growth and higher profitability. The COVID-19 epidemic and the related changes in the business environment have accelerated cloud adoption worldwide.

The cloud drives profitability and growth

Before implementing new cloud services, businesses must conduct thorough preparation, including extensive cloud readiness assessments and a well-defined onboarding plan. In order to identify a proper combination of public, private, and hybrid cloud systems, the company’s workload requirements as well as its strategic orientation must be considered. Regulations on data protection and storage, such as the GDPR requirements of the European Union and the DSGVO, also add to the complexity of the entire project.

 

Organizations must maintain the appropriate balance when orchestrating workloads if they really want to achieve optimal performance and take full advantage of significant cloud opportunities. Companies can swiftly migrate workloads and obtain exceptional performance on the cloud platforms thanks to the interconnection between multiple clouds, resulting in improved innovation.

 

Cloud-native development goes beyond technology and extends to operating models and organizational behaviors. To support cloud-ready transformation, businesses must realign their organizational structures and embrace a culture of lifelong learning, experimentation, and improvement. This is how they will realize and maximize the benefits of technology to their business.

 

When companies integrate the cloud with artificial intelligence (AI), they are capable to enhance their overall performance through more intelligence, data-driven processes, and a tailored user experience with measurable benefits- this applies to every industry. Organizations can develop data platforms that integrate and unlock company data and deliver deep AI capabilities using on-demand computing capacity in the cloud, allowing them to expand their business with agility and make educated decisions. Organizations will rely significantly on the cloud to unleash new possibilities rather than spending time improving existing processes.

 

Furthermore, the global COVID-19 pandemic has tremendously increased cloud adoption. Likewise, it has been proven that the cloud – and its implementation in IT systems and business processes – has become synonymous with company resilience. According to the Infosys study Cloud Radar 2021, with over 2,500 respondents from companies across the U.S., U.K., France, Germany, Australia, and New Zealand, companies with 80% or more of their business functions in the cloud reported a stronger ability to unlock value from data and AI using the cloud. By 2022, more than 40 percent of enterprises surveyed plan to shift over 60 percent of systems into the cloud, from 17 percent today. Whether in manufacturing, retail, healthcare, or financial services, cloud technologies have provided firms resiliency and enabled them to respond rapidly in the wake of lockdowns and social distancing.

 

Businesses of all sizes can benefit from the cloud, regardless of their industry. Profitability, on the other hand, does not appear until firms have migrated a large amount of their IT activities to the cloud and made well-informed decisions about cloud model/arrangement and cloud system management. When a corporation switches at least 60% of its systems to the cloud, it gains significant speed and capacity advantages. Anything below this criterion helps with defensive priorities, but it doesn’t help much more with getting a competitive advantage.

Cloud Computing Increase Profitability and business Growth

Cloud adoption is happening at different speeds and scales in different markets. Compared to other markets, European companies reported lower amounts of IT in the clouds. Companies predict they will heavily rely on the cloud to unlock new potential by 2022. Progressive and offensive cloud objectives, such as,- enabling remote access, cost management, resilience, and security, improved digital capabilities, accelerating deployment, and achieving scale seamlessly will be the dominant reasons for companies to adopt the cloud.

 

Sources:

Cloud Radar 2021: Boosting profits and enabling competitive edge through cloud

Effective methods to avoid Data loss and Data leakage

In the age of digitization and technological developments such as Industry 4.0, companies are confronted with ever-increasing amounts of data that need to be stored, analyzed, and evaluated according to business activity/priorities. Even though data is playing an increasingly significant role as a resource, it also comes along with huge security challenges. It is becoming increasingly lucrative for hackers to steal data to use it for a competitive advantage or even to monetize stolen data. When the data is stolen, companies lose a lot of money. To counteract this, data security, i.e., the protection of data from unauthorized access, is of crucial importance.

 

The protection of a company’s valuable data from unauthorized access is the task of data loss prevention (DLP) tools. Data Loss Prevention (DLP) solutions have been an integral part of the IT security strategy of many companies for more than ten years now. It is one of the most used technologies, by worldwide companies, to prevent the loss of sensitive data.  The aim is to protect any form of data against manipulation, disclosure, loss, and other forms of threats.

 

Various countermeasures can be taken to minimize the loss of a company due to data loss & to protect critical business assets. When implementing them, it is important to know what value the respective data generates for the company. Data that leads to high financial losses in the event of damage must be given the highest priority in the implementation of data loss prevention.

 

  • Backups: The most used method to counteract data loss are backups. These do not directly prevent the data loss process, but if data is lost, it can at least be recovered. Thus, it is important that the backups are carried out on a regular basis. They must also be regularly checked for recoverability and malware.

 

  • Permission Restrictions: Another technique to limit accidental data loss by employees is to restrict permissions/access to valuable files. The permission layer supports the company’s data privacy by protecting access to restricted data. Also, if an employee does not have permission to delete a file cannot delete it either.

 

  • Training and antivirus programs: There are several measures that must be taken to protect against viruses. First, the employees should be trained so that a virus has no chance of being invited into the system. However, since errors can still occur here, network anti-virus programs must be installed on every computer, every server, and every communication interface. It makes sense not to rely on just one provider here to be able to intercept several viruses.

 

  • Data leakage prevention: Analogous to data loss prevention, data must be inventoried and categorized. It ensures that users do not send sensitive or critical information outside the corporate network. Business confidential and critical information is classified and protected so that unauthorized users cannot accidentally or maliciously share data, which would put the organization at risk.

 

  • E-mail scanning: To prevent unauthorized internal sending of confidential documents, companies can prevent outgoing e-mails with attachments. However, since this cannot be practically implemented in everyday life, it makes sense to scan outgoing e-mails and only deliver them if previously set rules for sending have been observed.

 

  • Training and antivirus programs: Finally, incoming electronic communication can also be checked. This is to ensure that no Trojan or other form of malicious software can nest in the corporate network. Incoming documents in particular offer opportunities for this. Anti-virus programs must be used here to prevent a virus from being loaded. Employees also need to be trained so that fraudulent e-mails don’t stand a chance.

Data loss prevention & data leakage prevention are two main data security strategies that are adopted by worldwide companies. Companies that store sensitive and critical data, such as personal data, should place a greater focus on data leakage prevention. Operators of universally available assets, on the other hand, should consider data loss prevention as a priority.

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