Cloud Computing in the Healthcare Industry

Cloud Computing in the Healthcare Industry
Data is omnipresent; the healthcare industry is no exception to this fact. As the Cloud takes over technology at an exponential rate, there is a vast amount of potential for Cloud computing in the healthcare industry. Since the Cloud provides on-demand computing, it has rapidly become the go-to tool, especially when healthcare institutes and hospitals require deploying, accessing, and handling network information at the drop of a hat.

As healthcare regulations push the healthcare industry towards the need to look for better storage, collaboration, and data sharing techniques, there is an imminent need to prevent any data loss. Since electronic medical records (EMR) are prone to data loss, the Cloud has proved to be a reliable, secure medium of data storage; this can thoroughly be ensured by defining security parameters with Cloud providers at the time of undertaking the services.

Moving to the Cloud for a Better Tomorrow
The Cloud provides endless benefits to the healthcare industry. While many hospitals and institutes have already moved to the Cloud, many others are in the process of implementing their facilities to become available. The Cloud facilitates better collaboration while giving access to secure storage and providing remote access to stored data. Further, there is a remote conferencing facility available, which can update a patient’s health condition in a matter of minutes, all leading to considerable time-saving.

To perform all tasks related to storage, data manipulation, transition, and collaboration internally, a healthcare unit would need to invest heavily in infrastructure and the resources for maintenance. However, this process would mean massive costs and dubiousness around the full utilization of resources. However, with the use of the Cloud, all these thoughts can be put at bay, since everything is performed at a fraction of the total cost, leading to enhanced efficiency.

As soon as providers move into the Cloud, traffic gets channelized to the Internet, instead of the data center. This way, there is a lesser load on internal servers, as the availability and bandwidth free up drastically.

Use of Hybrid Cloud Services
Not many healthcare providers are too keen on making the use of public or private Clouds. Instead, such institutions make use of hybrid Cloud services. Hybrid cloud services make use of on-premise private data-center and third-party public Cloud service, which helps create a hybrid setup between different servers. This way, providers have an option to choose the apps and resources they would like to utilize within their local data center as well as in the Cloud.

Top Three Benefits of Cloud Computing
We have established the importance of the Cloud in the healthcare industry. While security is a significant concern with the storage of the data in the Cloud, nevertheless, it is not a deciding factor at the same time. Here are the top three benefits which highlight the usage of the Cloud services in the healthcare industry, and why it has become such an integral part of the technological universe:

Improved Patient Care Services: Patients can benefit immensely, as different health services are moved from a physical environment to a digital environment. Through the Cloud, doctors and patients can initiate virtual sessions, which enable the use of enhanced patient care services. Users can share, view, and store their records in the Cloud, while doctors can archive and access them remotely as well. By placing documents in the Cloud, different healthcare centers can access patient data with the press of a button, without having to bother about endless paperwork and delayed treatment issues.

Freeing up Essential Resources: The Cloud has been aligned to provide exceptional support in operational, administrative, and HR functions. It can ensure an outstanding quality of services when it comes to scheduling, referrals, sourcing files, inventory management, as well as perform many other types of behind the back actions. All this can be achieved at relatively low costs, which makes the process all the more efficient and lucrative for the end users. In other words, through the use of the Cloud, health institutes can expect better resource allocation, at a fraction of the cost.

Paving the Path from Administration to Analytics: Since a significant part of analytics is about data storage and manipulation, the Cloud comes in handy when tasks are more analytical, as compared to administrative. In fact, Amazon’s Web Services (AWS) are currently in the process of analyzing genomic data, which can help medical practitioners take a deeper dive into the causes of breast cancer and ovarian cancer.

Given its collaborative nature, the Cloud is becoming the future of tomorrow, and the healthcare industry shall be no exception to this fact, not now, not ever.

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Four Key Steps That Can Enhance and Endure Cloud Migration

Four Key Steps That Can Enhance and Endure Cloud Migration
There are always specific steps that ensure a targeted result in any process; they make use of three essential prerequisites—background information, resource availability and a predetermined goal. This principle does not go unnoticed when considering cloud migration solution. Though, to achieve the optimum results out of this process, while in line with this principle, the migrators must employ systematic steps that stand to endure the whole process. Some of those critical steps have been explored below.

1. Testing and Re-testing
It is always necessary to run planned tests to achieve a better hold of the current situation. The first stepping stone to a successful migration is successful testing. A migration test performs steps to ensure the data migration is ready or identifies the areas in which improvements are needed so that the process runs seamlessly. No firm can afford the loss of data – primarily when it belongs to a third party. Therefore, it becomes essential to work on the safe side. A migration test helps determine that a business workload will run in the cloud successfully after migration. The process involves multiple sub-steps such as:

• Replicating business data to the cloud
• Ensuring the testing solution creates a real-time copy of the replicated data
• Attaching replicated data to the testing workload on the compute instance before bringing it into production
• Repeating the tests seamlessly without manual effort or downtime to the business

These sub-steps are essential for successful testing because the dynamic IT environment can be severely impacted by configurational divergence. These crucial, automated and non-intrusive tests repeatedly run parallel to the business operations without affecting foreground data in any way.

2. Ensuring Continued Visibility into Business IT Health
Monitoring business IT health is vital in guaranteeing compliance with internal and external regulations, in addition to ensuring business critical service level objectives. The spectrum of business workloads falls so sporadically in public clouds that the real-time visibility and analysis of business IT health becomes very complicated.

Organizational cloud adoption is becoming common nowadays but very minimally in public domains. Many companies rely on the legacy and critical workloads hosted on premises. Since business applications have spread across multiple geographic locations and one or more clouds, this geographical and functional fragmentation can potentially affect IT operations. The various teams managing these workloads also contribute to the lack of visibility into IT health, which in turn increases expenditure costs. Thus, it is very wise to keep a proper eye on business IT health.

3. Adding a Resiliency Safeguard
When a third party’s data is taken into custody, it naturally becomes the responsibility of the service provider to ensure its protection. The data cannot be said to be “safe” until, and unless, it is protected by a resiliency safeguard. Loss of potential data may likely impact the business’ financial and reputational aspects. It is mandatory to remain vigilant and prepared for an outage that is beyond any control; this can be achieved by implementing a resiliency solution for public cloud workloads other than the basic resiliency add-ons made available by the cloud provider. A robust solution, on the other hand, helps instantaneously alert a business when an outage occurs, and shifting of workloads to another zone or region in the cloud is quickly performed.

4. Being Prepared to Migrate out of the Cloud Whenever Needed
The custody of business workloads can often be tricky, especially when one opts to move out of the cloud. According to IDC’s 2016 Cloud Computing survey, Vendor lock-in is one of the prime concerns of organizations surveying the public cloud. Other pressing matters include the sourcing and storing of data, and the security of cloud computing solutions; this indicates how the custody of company data plays a vital role in strengthening the business’ backbone. Cloud platform vendors prefer to have a firm grip on the business’ data which, at times, has made foreign clients skeptical. For this reason, most public cloud vendors offer their own free native tools to migrate solutions to their cloud. However, with the organizational objective shifting, the goals often tend to diverge from their first states after a decade; this often results in the need to move out of the cloud platform. Therefore, the business must be ready to act upon the need of the hour. Companies need to be prepared to migrate out, if the need arises, which should not cause any disturbance to the organizational pace.

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True Business Efficiency Combines the Power of Cloud Computing and DevOps Practices

True Business Efficiency Combines the Power of Cloud Computing and DevOps

The use of both DevOps and cloud-computing have become a promising combination for companies these days. The blend of practices and implementations provides increased speed and efficiency, as well as higher agility and better end-user experiences. While the Cloud and DevOps are two independent technologies, they become intertwined, resulting in a workflow more efficient than ever before.

The Driving Force of the Cloud and DevOps

Implementation of Cloud computing techniques has rapidly ushered in the use of the DevOps philosophy. Through this trend, enterprises are increasingly making use of agile software to develop and implement administrative IT operations for their customers to enhance their services in the long run.

Through the concept of DevOps, businesses can break down their functional silos and drive discipline between their IT-related processes. Since the process of development is rather elaborate, more companies have to spend a lot of time, effort, and resources to plan and transform their IT infrastructure thoroughly – all to obtain the maximum benefit out of available resources.

The progression of the Cloud and DevOps has been rather sudden, as compared to other technological advancements in the enterprise market. The development of DevOps is aimed at making the approach more Cloud-centric; this means that most public and private Cloud providers are beginning to support the implementation of DevOps within their platforms. These practices will enhance and aid the continuous creation of development tools. Strong integration leaves little or no space for cost inefficiencies, as there is an efficient mode of centralized governance within the processes.

Through effective governance, there is tighter control on developers, since they have a more streamlined process to follow, which is controlled centrally via Cloud services. This way, in a subtle yet efficient manner, companies can bring their differentiated departments under control. Cloud-based DevOps also lessen the need for leveraging resources, thereby providing a usage-based accounting solution. Through such elaborate measures, companies can track their applications and developers related data.

Would it be right to say that the Cloud is running DevOps? The answer is quite merely ‘no.’ Given the interdependence between the two technologies, there is an imminent need for both the technologies to be present to derive maximum functionality. As per RightScale’s 2015 State of the Cloud Report, over 71% of companies have adopted 66% of DevOps within their Cloud Services.

DevOps Leads the way into the Cloud

The Cloud is ruled by DevOps – this fact has been proven time and again. With the powerful combination of the Cloud and DevOps working together, there is a lot of aggregate value for CTOs, who are working to remove technical challenges from the paths of implementation. To gain maximum efficiency out of the partnership between the Cloud and DevOps enterprises need to strive towards the rapid deployment of DevOps practices continually.

Due to the inherent lack of knowledge and deployment techniques, many large enterprises and developers alike fear the implementation, since the concept of utilization comes across as confusing and sometimes, even impossible. If Cloud computing is paving the path towards the future, chances are enterprises and developers will need to take this bull by the horns and make the most out of it. In other words, if the Cloud has to work, one must adequately know how to deploy and implement DevOps for best results. Companies such as Idexcel focus on providing DevOps consulting services which provide reduced development times and operational costs for businesses of all sizes.

Use the Cloud and DevOps to Your Advantage

Budgets need to be focused and modified to utilize the Cloud’s full potential and meet enterprise goals. DevOps is about using the right techniques to mold the Cloud’s functionality to one’s advantage. The better the implementation, the more efficient a process will be created. With the right approach and the proper knowledge, developers and enterprises can go a long way in advancing towards the right direction, especially when it comes to meeting all chalked out goals in the long run.

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The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

From working in solitary cubicles to working with artificial bots, automation has come a long way and has changed how the modern generation works. Today, Artificial Intelligence (AI) and Machine Learning (ML) have become regarded as the future of tomorrow’s workforce and culture. At Idexcel, we have been keeping track of these ongoing trends.

It has been said that “with great power comes great responsibility.” If we tweak this statement a bit to reflect more contemporary times, we can also assuredly say that “with great technology, comes heaps of data.” The more we progress on the path of digitization, the more massive our datasets have become, and the idea that fascinates all data scientists is linked with the emergence of AI and ML technologies – how can they be used efficiently?

Here are top 10 trends that you should look out for as they shape the direction of data analytics in our future:

Augmented Analytics: This technology broadly utilizes the power of machine learning to automate data preparation and presentation. Through the use of augmented analytics, data scientists hope to be able to aid human intelligence, to produce rapid outcomes in different data-driven domains.

Artificial Intelligence and Machine Learning: Many of us might still be living in a bubble when it comes to AI assisted work. However, the fact of the matter is, that this bubble is going to burst. With robotics and artificial intelligence taking over at an increasing pace, there is a very heavy emphasis on getting data up and running to meet organizational goals. AI and ML will be used extensively to simplify work processes through the use of Big Data analytics.

Big Data: As technology has been advancing over the years and more affordable machines have emerged, faster processing powers have been available to businesses. Now, as cloud services are taking over traditional storage methods, there is a lot to look forward to regarding the increased output of processed information. As all these sources of information generate data, there is an imminent need to draw meaningful conclusions from the data – this is where Big Data comes into the picture. As the sources for storage get defined, Big Data provides excellent methods for allowing the manipulation of stored data to draw analysis and get the ball rolling.

Cloud and Edge Computing: One can easily say that technology has reached the Clouds. Companies such as Amazon, Google, and Microsoft are providing Cloud Services to organizations for storing their day to day data. Edge Computing, which is another form of shared computing, has become the next generation’s technology. Through the means of Edge Computing, organizations can overcome connectivity and latency issues, so that the distance data has to travel is reduced significantly. Edge Computing has seen an increasing rate of growth in mobile computing, as well as in the decrease of computer hardware. The rising use of IoT-enabled devices has ushered in an era of new technology.

Predictive Analytics: As more problematic situations emerge, there is a need to develop systems which can solve problems with ease and provide meaningful solutions. Predictive analytics prove to be the solution for such issues. The better the insights, the more structured are the solutions. Such are the capabilities of predictive analytics, as they help organizations gear up to tackle the worst possible issues.

Blockchain Technology: Digital currencies, such as BitCoin, owe their very existence to Blockchain technology. Given the success rate of cryptocurrencies, there is a lot of focus on merging Blockchain technology with the world of data science. The idea is to fuse the two methodologies together, to maximize the results. Since Blockchain technology is a versatile source, it can store any digital data; it has become a well-received option with data scientists.

As more and more organizations are taking analytics and data science seriously, there is an imminent need to progress to the next level of technology. Here at Idexcel, we work with clients every day to provide DataOps Consulting and Services; it has become an inseparable part of the modern organizational structure. As we progress into the future, the thin line between business intelligence and artificial intelligence will be removed; data will become smarter than ever before.

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The Challenges and Benefits of Modernizing Legacy Applications in Cloud

The Challenges and Benefits of Modernizing Legacy Applications in Cloud
It was right from its inception that cloud computing displayed a revolutionizing potential—it had an unforeseen scope over diverse targets including individuals, companies and governments. The major services available in these sectors and the ever growing inventions of the modern world do indeed call for a more advanced and flexible application of cloud computing. It is seen by many as the new wave of information technology. In 2010, the World Economic Forum published a report which evaluated the impact of cloud computing technologies and signaled the large potential benefits of adoption, ranging from economic growth and potential improvements in employment to facilitating innovation and collaboration.

Need being the mother of invention, Cloud has evolved beyond basic SaaS, IaaS, and PaaS offerings, as the cloud matures to become the engine of enterprise technology innovation. It is moving towards a faster and more efficient world. However, the Information Technology is increasing its demands to solve the arising complexities. Take for example the modernizing of legacy applications in cloud. It extends both challenges and opportunities, as the facets of a coin, but in each way it moves towards a more advanced and intricate web of complexities.

Most of the large enterprises run at least some form of a legacy application, for which updates and replacements can sometimes be tricky. However, failing to modernize out-of-date systems may hinder the pace of information exchange due to slow runtime speeds and inefficient load balancing. Many organizations have, thus, begun to modernize their legacy applications which will yield long term benefits such as portability and scalability, better speed and resource management, and granular visibility.

Since the start, enterprises have run on time-consuming manual processes and tools that are involved with legacy applications also hinders modernizing efforts. Manual processes take up significant amount of time and still leave room for errors. However, at the same time, enterprises say they need to move to the cloud, but they don’t really understand why, nor do they realize how difficult it can be. This includes applying cloud services to a non-compatible old legacy application and facing challenges when trying to re-host. They must be cautious of the processes involved in migrating the valuable data. If one moves one application to cloud which has business logic or IT logic of another application that isn’t migrated to cloud, they might run into issues. Therefore, it is better to consult the professionals before landing into problems. In this league of advancement, the infrastructure might face challenges such as:

Cost adjustments: The cost of maintaining and upgrading Legacy systems renders the firm a challenge of combatting the financial balance. The challenge preparers the employees learn the skills of pulling the firm through the tight passage without de-establishing the financial pace of the organization.

Inflexible and closed architectures: There are some architectures used by organizations that hinder Web and mobile enabling and integration with contemporary platforms, therefore, they turn out to be challenging opportunities for the modern minds at work.

Limited Integration: Legacy systems might sometimes not go in cohesion with the integration to contemporary technologies like Mobile Apps/Devices, Enterprise Content Management Systems, Automated Workflow, E-Forms/E-Signatures, Geographic Information Systems, and so on, therefore pose a major obstacle for the integrators.

User Friendliness: The existing system uses command-based screens and cannot provide a contemporary Graphical User Interface (GUI), web, or mobile which have become commonplace, however, if it is in constant practice, the newer models of commanding may pose an oddity for quite some time for the old hands. Therefore, the migrators have to go an extra mile to ease the way by employing less complicated systems.

On the other hand, there are various benefits of applying this modernization. If the engineers handle the aforementioned challenges wisely and implement the newer technology with greater precision, there indeed some charming benefits await, such as:

Enhanced flexibility: Creates a flexible IT environment with new architectural paradigms such as web services; aligns IT systems to dynamic business needs.

Modern development tools: Legacy and new developers can use the same or similar tools, enabling both to develop Legacy applications.

Lower risks: Re-use of business rules where data becomes less risky than alternatives.

Shorter development times: Modernizes development tools and retrains developers which lead to shorter development times.

Reduced cost: Lowers high maintenance cost of existing old fashioned Legacy platforms and development tools, resulting in substantial savings in IT budgets.

Minimized disruption: Reduces the risk when modernizing Legacy platforms by combining two decades of development experience with contemporary platforms, a proven modernization framework and rich domain knowledge.

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Machine Learning’s Impact on Cloud Computing

Machine Learning’s Impact on Cloud Computing

Machine learnings impact on cloudcomputing
Increasing dependency on AI (Artificial Intelligence) and the (Internet of Things) have given new goals to cloud computing infrastructure administrators. The premises enfolding within this newly emerging subfield of Information and Technology are indeed very vast ranging from smartphones to robotics. Firms are developing new machinery requiring the least amount of dependency on human resources. Developments aimed at providing human-made mechanisms with levels of autonomy to become entirely independent.

To gain a level of autonomy over soft resources, developers have begun to depend on a mediator to assist ‘smart machines’ in increasing functional ability. As cloud computing is already taking over essential domains of human efforts such as data storage, this technological advancement will result in unprecedented impacts on the global economy.

Integrated cloud services can be even more beneficial than current offerings. The contemporary usage of cloud involves computing, storage, and networking; however, the intelligent cloud will multiply the capabilities of the cloud by rendering information from vast amounts of stored data. This will result in quick advancements within the IT field, where tasks are performed much efficiently.

Cognitive Computing
The large amounts of data stored in the cloud serve as a source of information for machines to gain their functional state. The millions of functions that are occurring daily in the cloud will provide vast sources of information for computers to learn. The entire process will equip the machine applications with sensory capabilities, and applications will be able to perform cognitive functions, making decisions best suited for them to achieve their desired goal.

Even though the intelligent cloud is in its infantile age, the propositions are predicted to increase in the coming years and revolutionize the world in the same way that the internet had. Expectations of those who would utilize cognitive computing including those in the healthcare, hospitality, and business fields

Changing Artificial Intelligence Infrastructure
With the aid of the intelligent cloud, AI as a platform service makes the process of smart automation more accessible for users by taking control of the complexities of a process; this will further increase the capabilities of cloud computing, in return growing the demand for the cloud. The interdependency of cloud computing and artificial intelligence will become the essence of new realities.

New Dimensions for the Internet of Things
Just as we are now aware how the IoT has overtaken our lives and created an undeniable dependency on gadgets, cloud-assisted machine learning is almost increasing rapidly. Smart sensors that allow cars to operate in cruise control will grasp their source of data from the cloud only. Cloud computing will become the long-term memory for the IoT where they can retrieve the data for solving in-time problems. The web’s massive of interconnectivity will generate and operate on an enormous amount of data saved in that very cloud; this will expand the horizons of cloud computing. In coming years, cloud-based machine learning will become as meaningful to machines as water is for humans.

Personal Assistance
We have already seen assistants such as Alexa, Siri, Cortana, and Google perform well in the consumer market; it is not absurd to think that an assistant will exist in every modern home by the next decade. These assistants make life easier for individuals through pre-coded voice recognition that also gives a feeling of human touch to machines.

Current assistant responses operate on a limited set of provided information. However, these assistants are very likely to be developed more finely so that their capabilities will not remain so confined. Through the increasing use of autonomous cognition, personal assistants will attain a state of reliability where they can replace human interaction. The role of cloud computing will be supremely vital in this regard, as it will become the heart and brain of these machines.

Business Intelligence
The tasks of a future intelligent cloud will be to make the tech world even smarter – autonomous learning coupled with the capabilities of understanding and rectifying real-time anomalies. In the same way, business intelligence will also become more intelligent wherein along with identifying faults, it will be able to predict future strategies in advance.

Armed with proactive analytics and real-time dashboards, businesses will operate upon predictive analytics that process previously collected data, making real-time suggestions and future predictions. These predictions from current trends and recommendations for actions would make things easier on leaders.

Revolutionizing the World
Fields like banking, education, and hospitality will be able to make use of the intelligent cloud, enhancing the precision and efficiency of the services they provide. Consider, for example, having an assistant in hospitals which diminishes doctors’ customary load of decision making by analyzing cases, making comparisons, and promoting new approaches to the treatment.

With the rapid development of both machine learning and the cloud, it seems in the future that cloud computing will become much easier to handle, scale, and protect with machine learning. Along with those mentioned above, more extensive businesses relying on the cloud will lead to the implementation of more machine learning. We will arrive at a point in which we will have no cloud service that operates as they do today.

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Advantages of Cloud Analytics over On-Premise Analytics

Advantages of Cloud Analytics over On-Premise Analytics
Majority of the organizations now agree that data science is a great tool to scale-up, build and streamline their businesses. But, with this huge amount of data they are collecting, are the organizations really coping up to analyze and implement the decisions in time? Most of them, in-spite of having on-premise analytics teams are in disconnection with their operations part.

Having the in-house analytics teams linked to your Enterprise Resource Planning(ERP) systems can be sometimes be irresponsive due to data loads, might cause your sales teams to lose the real-time data, also can cause delay in response to the queries. Collection of data from various internal applications, devices, online media networks, consumer data and converting them into actionable insights can be a cost consuming (both time and capital costs) process for the organizations.

Is there any better way of utilizing your Company’s data towards reaping benefits?
Yes, most of your valuable data from modes of communication to collecting track-able data of consumer behavior lies in the cloud. Cloud computing allows you to easily consolidate information from all your communication channels and resources, and helps you to do it in a wider scale.

Cloud, basically helps the business’ data teams to re-establish the connection with their operations. And hence the business will be able to minimize the time and capital costs incurred, from the research and development of the product, marketing and sales to increasing the efficiency of your consumer support teams.

How does Cloud Analytics serve as a better and real-time mode of efficient data management?

Agile Computing Resources
Instead of handling speed and delivery time related hassles from your on-premise servers, cloud computing resources are high-powered and can deliver your queries and reports in no-time.

Ad hoc Deployment of Resources for Better Performance
If you are having an in-house analytics team, you should be concerned about an efficient warehouse, latency of your data over poor public internet, being up-to date with advanced tools and experience in handling the high demands for real-time BI or emergency queries. Employing Cloud services in data science and analytics can help your business scale-up by establishing a direct connection between them, reducing the latency and response issues to less than a millisecond.

Match, Consolidate and Clean Data Effortlessly
Real time Cloud analytics with real-time access to your online data keeps your data up-to date and organized, helping your Operations and Analytics teams function under the same roof. This makes sure of no mismatches and delays, helping you to also predict and implement finer decisions.

Accessibility
Cloud services are capable in sharing data and visualization and performing cross-organizational analysis, making the raw data more accessible and perceivable by a broader user base.

High Returns on Time Investments
Cloud services provide readily-available data models, uploads, application servers, advanced tools and analytics. You need not spend any time in building up a separate infrastructure, unlike employing on-premise analytics teams.

Your marketing teams can forecast and segment your campaign plans, the campaign reports and leads generated are readily available to your sales teams to follow-up, insights from sales and marketing and more real time consumer data can help your strategy teams in predicting crucial decisions or your support teams being immediately notified with consumer queries. Better the collaboration, higher are your returns, and an ideal cloud service can make this possible.

Flexible and Faster Adoption
Cloud-based applications are built with self-learning models and have a consumer friendly user experience unlike the on-premise applications. Cloud technologies learn to adopt as your business grows and can expand or adjust as your data storage and applications needs increase or decrease.

Affordability
There are no upgrade costs or issues, and enabling new tools or applications require minimal IT maintenance. This keeps the business in a continuous flow without any interventions like the need for upgrading the on-premise infrastructure, and having to redo your integrations and other time consuming efforts.

Security
Robustly built, Cloud analytics are reportedly more reliable than on-premise systems in times of a data breach. Detecting a breach or a security issue can be within hours or minutes with Cloud security whereas with an in-house team, it takes weeks or even months in detecting a breach. Your data is more trusted and secure with cloud computing.

Implementing cloud services in data science can be the best and most-effective infrastructure you can give to your business. They are agile, secure and flexible and help you to streamline each of your business process as Cloud services enable all your teams function under the same data foundation.

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How Artificial Intelligence is Transforming Cloud Computing

1.	How Artificial Intelligence is transforming Cloud Computing
Everyone in touch with technology is aware of cloud computing. It has already turned out to be an important part of the current digital era. It has transformed the manner in which individuals, professionals and even companies store their essential information and data.

The market for cloud computing has tremendously made progress over the past few years which in turn has strongly affected the lifestyle and work culture in various ways. But the cloud is a new technology, due to which companies are worried about whether it will evolve over time or not. Recent trends such as the use of mobile phones instead of computers have even made petty changes in the cloud technology. Therefore, AI has come up to enhance the cloud technology (AI is the capability of a robot controlled by a computer or a digital computer that carry out tasks that are usually linked with the intelligent beings). Cloud computing and AI are bringing major changes in the corporate world and their fusion is believed and known to be the coming future of technology.

The cloud technology can help AI’s by providing the required information for the learning processes while the AI can help cloud by providing information that can offer more data. AI is capable of streamlining the immense capacities of the cloud. It equips cloud technology with enormous powers. It enables the machines to act, react, think and learn in the manner human beings do. AI assists different machines in learning and analyzing the historical data, making decisions and identifying the patterns. Such a process helps in eradicating the chances of human errors. Therefore, AI enhances the process of decision making of various organizations.

Cloud technology is spread among a number of servers in various languages with huge data storage and across various geographies. Organizations can make use of this data to make up intelligent and automated solutions for customers and clients. Cloud computing is getting more powerful with AI as its applications are extended across multiple diversified sectors in the economy. Thus, even organizations can make use of AI cloud computing to attain long-term goals for their businesses.

Another crucial aspect of the fusion of AI cloud computing is the process of machine learning. Such a process helps in making reliable and quick decisions, reducing the chances of cyber crimes and improving the experiences of the customers. In the recent years, machine learning has been able to quickly employ complicated mathematical calculations to large amounts of data. It is even capable of delivering more accurate and quick results on a huge scale which drives new business opportunities and growth strategies for organizations around the world.

The fusion of AI cloud computing has brought about a huge change in information technology and several other industries. It can potentially change the manner in which the data was stored earlier and processed among several geographies. Such an amalgamation also offers unique opportunities for the professionals of AI and cloud to look over the boundless possibilities for future.

Cloud, when stood alone, has the capability of becoming a significant computing commodity in several fields. But the AI cloud computing integration will enhance its requirement in the market. With huge strides existing in the growth of both cloud and artificial intelligence, their future seems to be highly tied together. Cloud computing gets much easy to protect, scale and handle with artificial intelligence. Above that, the more the businesses are getting on the cloud, more it needs to be integrated with AI to attain efficiency. A point will come when no cloud technology would be existing without artificial intelligence.

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Top Roles of Cloud Computing in IoT

Top Roles of Cloud Computing in IoT
Transformation is an ever going trend, which is becoming an absolute need of the hour in today’s fast paced world. With technology churning every bit of information in a refined new format, there is a lot of scope when it comes to data storage and manipulation.

As smart phones and social media begin to rule the roost, there is a lot of conversation happening around what’s coming next. The evident answer of the hour is, the Internet of Things or IoT. With the Internet churning out huge chunks of data every second, there is a pending strain on the data infrastructure, making it necessary to look for solutions to ease the use of data storage.

Since the rise of the Cloud, there is a massive shift towards using it as a means of storage for people and businesses alike. Given the scalability and the data dynamics, there is a lot of stress being given on the use of Cloud computing to make data available remotely.

Putting this scalability to use, the Cloud has proved to be an efficient tool for transferring data through the traditional Internet channels as well as through a dedicated direct link. The traditional method is not preferred extensively; however, at the same time, many businesses prefer to the use the direct link to transfer data to the Cloud, given the quality of the data and the security it ensures during the transfer phase.

This is not all; the Cloud has become an integral part of the Internet world. Simply put, the cloud can be termed as an enabler when it comes to IoT. The Cloud is undoubtedly an ideal solution to meet all data driven needs of businesses. As this technology is developing, it is providing an agile platform for developers to create meaningful apps to establish better data devices over the Internet.

How Cloud Computing Aids IoT?

The underlying idea behind IoT and the Cloud computing is increase efficiency in the day to day tasks, without disturbing the quality of the data being stored or transferred. Since the relationship is mutual, both the services complement each other effectively. The IoT becomes the source of the data, while the Cloud becomes the ultimate destination for it to be stored.

As we progress through the years, we will see a lot of changes happening; some of these changes will be gradual while others will be more rapid. Companies likes Amazon AWS, Google and Microsoft will become the undisputed leaders of Cloud IoT Services, making the challenge even more worthwhile.

As the Cloud gathers more attention and speed slowly, there are a multitude of Cloud service providers which are beginning to offer pay per use models to businesses. This way, businesses only need to pay for what the computer resources they use.

Some more Reasons which Highlight the Importance of the Cloud in the World of IoT are:

Reduced cost of ownership: Inflation is a never ending menace which every business has to face sooner or later. The Cloud technology provides ample resources to businesses so that they do not have to spend through the nose on setting up their infrastructure. In the absence of on-site systems, hardware and software, the IT department is more focused on their day to day up keeping activities, which are often an evident benefit with the Cloud.

Business continuity programs: The Cloud computing is capable of running businesses even in the midst of sudden disasters. Since the data is maintained on additional separate servers, there is no imminent danger to the private data, making the Cloud an indispensable part of Internet based firms.

How will the IoT and the Cloud Expand?

Startups: As more and more Cloud vendors pop up, startups will continue to evolve and become more efficient, making the technology flow stronger yet smoother. The transition from one source to another will become a cinch, making the Cloud a strong place to function.

Developing countries: The strongest and biggest source of revenue for the Cloud comes from the developing countries, as they are trying to play catch up with the times. However, this revenue will drastically dip, once these countries are able to adopt their technology to the Cloud, marking the adaptation as complete.

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Overcoming Cloud Security Threats with AI and Machine Learning

Cloud-security

The increasing flexibility of Cloud services has made the enterprises to embrace them in storing, sharing and managing their data efficiently. Cloud computing has not only increased their operational efficiency, but also have helped them save thousands of dollars in IT investments.

From helping the organizations deliver faster, cost-efficient and quality results to effectively managing their resources, Cloud services has definitely been a boon for enterprises. It helps them focus on their businesses rather than spending their precious time in building and managing their IT infrastructure.

But, with any kind of new technology comes greater and complex security needs associated, making the universal adoption of Cloud services questionable. Some threats associated with Cloud services are:

-Having large amounts of sensitive data in the Cloud (especially for industries like Finance and Healthcare) can be a promising target for the hackers.

-The enterprises are liable to face heavy dues and even criminal charges in-case of consumer data leakage, under compliance regulations like HIPAA.

-BYOD (Bring Your Own Device) systems have been a great advantage for both employers as well as employees in terms of data mobility and accessibility. But, stolen or misplaced devices, if goes in the wrong hands can be a huge expense for an Organization as they are almost impossible to track without proper tools in hand.

-Weak authentications and leaving the credentials in one’s device can also lead to loss in enterprise data in case of any phishing, ransomware and brute-force attacks.

Offering great value for enterprises in terms of scalability, feasibility and cost savings, it is important that they untangle these security concerns before adopting comprehensive Cloud strategies.

AI and Machine Learning for Advanced Cloud Security Solutions:

AI is a system that has the capability to learn and adapt to the change in its environment. Often used with Machine Learning, AI uses predictive analysis which can pre-model the results by analyzing the past events. With the cyber threats advancing at an alarming rate, there is a real need for us to employ the tools that forges ahead of them.

Crucial Role of AI in Detecting Cyber Security Threats

-A recent study on global security conducted by Nemertes research says: the average time taken for an enterprise to spot the threat and respond with a cloud security solution was 39 days. Some companies were able to detect and respond within hours.

-Faster response time means the threats are detected and blocked immediately from the user’s side, preventing further data leakage.

-The organizations those were able to detect the threats faster employed automation which can only achieved by employing AI and Machine learning based cloud security solutions.

-Fully automated AI cloud security solutions use behavioral analytics to determine a path on which the systems operate. Any deviation from the flow, it takes the system off the network bringing this ‘response time’ to effectively zero. Notably, 28.6% of all companies have already employed full automation to their key business processes, as per Nemertes’ reports.

Moving at a Faster Pace than Cyber-Criminals with AI

Cybercriminals were always ahead of the traditional security standards deployed by the enterprises, posing continuous nightmares to the IT teams. They had to spend most of their time and capital investments in optimizing their security standards, each and every time they experience a data breach.

Now, with the AI and Machine learning technology in hand, their adaptive learning capabilities prove as an efficient cloud security solution for enterprises in thinking and acting ahead of cybercriminals:

-The number of patterns processed by the Machine learning programs increases with the increase in data injected. As the patterns increase, it makes AI easier to give early indications of cyber threats whenever it senses a slight change in this pattern flow.

-Machine learning not only processes the real time data quickly, but can also co-relate them across time and geographical locations. This helps the organizations to be aware of the security breaches and prevent them, days before the event.

-Email has always been an easier platform for cybercriminals. AI and machine learning based cloud security solutions can help to plot relationships between different kinds of content sentiments, mail services and communications. In case of any suspicious patterns, the organizations can alert their employees, days before a threat is potentially identified.

The current machine learning technologies have begun to detect even unusual threat events with high volumes of data. The organizations can now leverage their business process more efficiently through Cloud services with AI in hand as their most powerful tool against security threats.

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