Tag: indus net technologies

Data analytics plays a crucial role in clinical trial design and analysis by providing valuable insights into the effectiveness of new treatments and therapies.

The role of data analytics in clinical trial design and analysis

March 31, 2023

What is the role of data analysis in clinical trials? Can there be better clinical trial data analysis using R and other technologies? Is there a case for using big data analysis in clinical trials? Experts would certainly say Yes to all these questions. Clinical trials themselves have gone through sweeping changes over the last decade, with several new developments in immunotherapy, stem cell research, genomics, and cancer therapy among numerous segments. At the same time, there has been a transformation in the implementation of clinical trials and the process of identifying and developing necessary drugs.  To cite a few examples of the growing need for clinical trial data analysis, researchers gain quicker insights through the evaluation of databases of real-world patient information and the generation of synthetic control arms, while identifying drug targets alongside. They can also evaluate drug performance post-regulatory approvals in this case. This has lowered the cost and time linked to trials while lowering the overall burden on patients and enabling faster go-to-market timelines for drugs too.  What is driving data analysis in clinical trials?  Clinical trial data analysis is being majorly driven by AI (artificial intelligence) along with ML (machine learning), enabling the capabilities of collection, analysis, and production of insights from massive amounts of real-time data at scale, which is way faster than manual methods. The analysis and processing of medical imaging data for clinical trials, along with tapping data from other sources is enabling innovation of the entire process while being suitable for supporting the discovery procedure in terms of quickening the trials, go-to-market approaches, and launches.  The data volumes have greatly increased over the last few years, with more wearable usage, genomic and genetic understanding of individuals, proteomic and metabolomic profiles, and detailed clinical histories of patients derived from electronic health records. Reports indicate 30% of the data volumes of the world are generated by the global healthcare industry. The CAGR (compound annual growth rate) for healthcare data will touch 36% by the year 2025 as well. The volume of patient data in clinical systems has already grown by a whopping 500% to 2020 from 2016.  Data analysis in clinical trials- What else should you note?  Here are a few factors that are worth noting:  Synthetic control arm development  The role of data analysis in clinical trials is even more evident when one considers the development of synthetic control arms. Clinical drug discovery and trials may be fast-tracked while enhancing success rates and designs of clinical trials. Synthetic control arms may help in overcoming challenges linked to patient stratification and also lower the time required for medical treatment development. It may also enable better recruitment of patients through resolving concerns about getting placebos and enabling better management of diverse and large-sized trials.  Synthetic control arms tap into both historical clinical trials and real-world data for modelling patient control groups and doing away with the requirement for the administration of placebo treatments for patients which may hinder their health. It may negatively impact patient outcomes and enrolment in trials. The approach may work better for rare ailments where populations of patients are tinier and the lifespan is also shorter owing to the disease’s virulent nature. Using such technologies for clinical trials and bringing them closer to end-patients may significantly lower the overall inconveniences of travelling to research spots/sites and also the issue related to consistent tests.  ML and AI for better discovery of drugs ML and AI may enable a quicker analysis of data sets gathered earlier and at a swifter rate for clinicians, ensuring higher reliability and efficiency in turn. The integration of synthetic control arms in mainstream research will offer new possibilities in terms of transforming the development of drugs.  With an increase in the count of data sources including health apps, personal wearables and other devices, electronic medical records, and other patient data, these may well become the safest and quickest mechanisms for tapping real-world data for better research into ailments with sizeable patient populations. Researchers may achieve greater patient populations which are homogenous and get vital insights alongside. Here are some other points worth noting:  The outcomes of clinical trials are major metrics with regard to performance, at least as far as companies and investors are concerned. They are also the beginning of collaborations between patients, groups, and the healthcare sector at large. Hence, there is a clearly defined need for big data analysis in clinical trials as evident through the above-mentioned aspects.  FAQs How can data analytics be used in clinical trial design and analysis? Data analytics can be readily used for clinical trial design and analysis, expanding patient selection criteria, swiftly sifting through various parameters and helping researchers better target matching patients who match the criteria for exclusion and inclusion. Data analysis methods also enable better conclusions from data while also improving clinical trial design due to better visibility of the possible/predicted risk-reward outcomes.  What are the benefits of using data analytics in clinical trial design and analysis? The advantages of using data analytics in clinical trial design and analysis include the integration of data across diverse sources, inclusive of third parties. Researchers get more flexibility in terms of research, finding it easier to analyze clinical information. Predictive analytics and other tools are enabling swifter disease detection and superior monitoring.  What are the challenges of using data analytics in clinical trial design and analysis? There are several challenges in using data analytics for the analysis and design of clinical trials. These include the unavailability of skilled and experienced resources to implement big data analytics technologies, data integration issues, the uncertainty of the management process, storage and quick retrieval aspects, confidentiality and privacy aspects and the absence of suitable data governance processes.  What are the best practices for implementing data analytics in clinical trial design and analysis? There are numerous best practices for the implementation of data analytics for the analysis and design of clinical trials. These include good clinical data management practices, clinical practices, data governance

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Hackathon Diaries #3

Hackathon Diaries #3 Digital Democracy: Web-app Vote, One-click Remote

March 29, 2023

The INT. Hackathon 2023 was a call to all the tech enthusiasts, problem solvers, and innovators at our company to be a part of an electrifying opportunity to showcase their abilities, collaborate with their peers and bring their groundbreaking ideas to life. This offered a platform that left every one of us awe-inspired and amazed through the unleashed creativity.  In this edition, our tech gigs focused on our commitment to the Digital India initiative as we are already serving a plethora of government bodies time and again. ‘Digital Democracy’ is what the team emphasised with the motto, ‘No stress, no mess, just a simple click and your vote is expressed.’ Digital Democracy Digital democracy is a cutting-edge web application to revolutionise democracy through a decentralised voting system. It harnesses the power of blockchain technology to ensure secure, transparent, and tamper-proof elections. It acquires the potential to avoid long queues and outdated voting systems to welcome a new era of democracy. The Team Shankha Chatterjee Shankhya Subhra Datta Lokenath Karmakar Sayantan Sur Market Potential Increased demand for remote voting: The COVID-19 pandemic has accelerated the trend of remote voting, as more people are looking for safe and convenient voting remotely.  Blockchain technology adoption: Blockchain technology is growing across a variety of industries, and its potential applications for voting and elections are increasingly being explored. Potential cost savings: An online voting app with blockchain can provide cost-saving options compared to traditional voting methods, such as paper ballots and in-person voting. Problem Statement Voting: India is the largest democracy in the world, however only 67% of people vote Security: Electronic voting machines are vulnerable to hacking, tampering, and other forms of interference hampering the voting procedure Transparency: Voters face ambiguities in the counting of their votes and the accuracy of results Reliability: The data stored in the database can be hampered and manipulated resulting in trust issues Paper trail: Voting solutions lack a paper trail making it difficult to audit the results raising the possibility of disputes Expensive: Current conventional voting system is costly The Solution and Its Benefits Digital Democracy – A Voting Web-App having the following features: Decentralised identity verification through Blockchain technology allows each voter to create a unique digital identity that is linked to their physical identity Tamper-proof and transparent ledger to provide an immutable record of all casted votes, making it more difficult to breach results Maintaining privacy to keep an individual’s vote secret Voters would be incapable to give their voting rights to third parties  Easy voting and making everyone eligible to vote Maintaining immutability by keeping the unmodifiable records of the casted votes on the blockchain The system is easy to use and accessible to all voters, regardless of their technical abilities Facilitating seamless verification of votes to ensure validity  The system upholds voter anonymity to ensure their choices remain private The solution processes votes quickly and efficiently to make the results available on a real-time basis  The system is resilient to cyber-attacks and can withstand attempts to compromise the integrity of the voting process How It Works Workflow #1 Workflow #2 Tech Stack FrontEnd: React Js Backend: Node Js Web 3.0: Metamask, Solidity, Polygon, and Hardhat Database: MongoDB Future Business Scopes The platform can establish partnerships with other companies or organisations to offer additional services, such as voter education materials or voter outreach campaigns. These have the potential to generate revenue through joint marketing efforts or revenue-sharing agreements.  Tie up with the government and corporate sectors  The online voting system can offer customisation services for election authorities, like creating custom ballots or integrating the system with existing voter databases

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INT. Pulse

SNBL

March 22, 2023

As the whole world is going bananas over BNPL (buy now, pay later), Africa has dropped a new fintech model on its shoppers. And it’s something so cool, you’ve never heard of it – SNBL, aka, save now, buy later. While BNPL has skyrocketed worldwide and given us juggernauts like Klarna, this arm of fintech is facing backlash too, with many realising it encourages overspending and can lead to nasty debt traps. The wise are also asking if it’s commercially sustainable, as Klarna saw its valuation cut 85% from USD46B to USD7B. Save now, pay later is like an upfront answer to that. SNBL providers across emerging markets reiterate that the model is better aligned with existing cultural practices and furthers consumers’ long-term financial health. African fintech investors are believing the story wholeheartedly too. Let’s try saying this aloud – ‘Flipkart save now, buy later.’ ✅ Sounds like a million bucks already. AI/ML: When A Monkey Took A Selfie From horses to automobiles, postcards to emails, or even film to digicams, there’s a long history of backlash towards emerging technologies. As exhibited by the image above, when cinema introduced audio, people asked: “But what will happen to the orchestra?” The obvious worry was that the orchestra that played alongside silent films would be out of a job. Though the concern was valid, ultimately, the introduction of sound into movies dramatically expanded the music industry, increasing net employment many times over. Also, jobs like Sound Editor and Sound Mixer emerged out of empty auditorium seats. As generative AI reinvents industries (yes, some jobs will be replaced), it’s worth remembering past reactions to new technologies, and that the pie has often grown larger, albeit in ways we cannot foresee when we are in the moment. 💡 The design world vehemently opposed photoshop when it dropped. Of course photoshop has its downsides, but it also ushered in a new era of visual expression and spawned millions of jobs worldwide. 🙈 Also note that you can’t copyright AI art (you may be infringing when you create AI art though), meaning when a monkey took a selfie, AI art lost the battle before it even started. BFSI: The Safest Bank In The World Before your thoughts start running away to things like ‘mattress’, ‘underground’, or even ‘false ceiling’, please consider this. Many years ago, a startup called Narrow Bank, cooked up a business model of just taking deposits and holding 100% of them in Federal Reserves. The plan was simple. It would basically make Narrow the safest possible bank. But sadly, they were never granted a Fed Account or even access to their electronic payment services. The Narrow Bank even went to court over it and lost. What’s Wrong With Super Safety? 🤔 If one bank is “too safe”, it can suck deposits out of the whole system towards itself, meaning most of the current two-tier banking system wouldn’t make sense, if that full-reserve bank existed. Moral Of The Story: Regulators ironically want banks to be safe, but for none to be too safe. 🔔 If you’re a professional making banking ‘safer’ with technology, Souvik is always around to help you explore and deploy the best-fit tech stack for your BFS system. Reach him here. . . ­Pharma: GPT4 And Drug Discovery Drug discovery is an incredibly complex process. Zeroing in on a target molecule, testing each compound for value and toxicity, and then modifying the molecules appropriately for clinical trials are the general steps involved. As a result, it often takes years to find a viable chemical using this ‘hit to lead’ method. Then There’s GPT4 Toying With It Simply give it a currently available drug and it can: Find compounds with similar properties Modify them to make sure they’re not patented Purchase them from a supplier (includes sending an email automatically with a purchase order). Here’s the complete paper for your perusal. ✋ If you need to know more about how data, analytics, ML and AI can augment your pharma business (we understand there’s much more to it than discovering drugs using AI), get in touch with Dipak, our lead data scientist. Stuff We Are Watching 📌 Overdue Diligence: Please spare a thought for the Saudi National Bank, because just a couple of months back, they invested USD1.5 billion in Credit Suisse to pick up a 10% stake. Today the same stake is valued at ~ 🥜🥜, a total write off in a matter of weeks. 📌 Expensive Errors: Beyond the human cost of healthcare medication errors, the WHO estimates the global cost to be USD42 billion annually. Per this study, 8 out of 10 healthcare tech professionals are willing to increase spends to minimise preventable medical errors. 📌 The Coolest Tech Billionaire: Meet Mark Leonard, the founder and CEO of Constellation Software – a company like none other. Why? Because since its debut at USD70 million at the Toronto Stock Exchange, the company has increased in value by ~ 70,000% 🚀­🙋🏻‍♀️ Before we wrap up the March edition of Pulse, here’s a conversation we overheard on social. Chappie #1 – Instagram is dead. In the next 3 – 5 years, every single image on social media will be generated by AI. And here is the kicker: It will be impossible to tell fake from reality. Chappie #2 – Instagram is the kingdom of fake. Care to elaborate how better fakes represent a danger to the business model? Party Crasher Elon – These days, if it looks shoddy and fake, it’s probably real. 🤷🏻‍♀️ 💡 Simply hit reply to this email and get instantly connected to a team of 850+ experts to start any kind of conversation, or to be featured in this monthly newsletter – read by over 22,000 professionals like yourself. See you in April. Cheers! Team INT.

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Business Intelligence & Data Analysis – The Next Big Thing

August 31, 2021

33.3 billion dollars is what global business intelligence (BI) is targeting in the next five years. The report suggests in 2021 itself recorded a jump from 21% to 26% of the adoption rate of BI. Therefore business intelligence is going to be the next big thing in the business space. But it is not BI only that is taking over the world, and it has become imperative to extract insights from the data. Thus, refocussing on data analysis is also one of the big things we will see in the near future. Business Intelligence is a technology-driven process to collect data from different sources, analyze them & finally deliver an ‘Actionable Information‘ that helps the company to make important predictive business decisions. This is possible by using various BI tools such as Power BI, Tableau and many more. Some of the important features of BI tools are : Reporting Analytics and Interactive Dashboard Development Data mining and Process Mining Complex Event Processing Benchmarking Predictive and Perspective Analytics Data gaining popularity in 2022 For businesses to reach the strategic endpoint, data analysis plays a vital role. Here are a few ways by which we know why Data Analysis is so popular in 2021 No-Code Process: BI tools are so easy to use & require no coding knowledge, thus attracting both technical & non-technical individuals. Anyone can pull data from various sources, modify & create visualizations – all without writing a single line of code. This encourages everyone to be data-driven and more interested in pursuing a career in Data Analysis. Easy Collaboration: One of the main reasons for data analysis using BI tools getting popular in 2021 is because of its ‘Collaborative’ nature. The process is called ‘Collaborative BI’, which merges the BI tools with other collaboration tools. This allows the data visualizations/ reports to be shared with co-workers in the same organization so that they can understand. This method allows everyone in the team (even the non-technical ones) to be on the same page & help them make wise decisions about the business. Collaborative BI promotes : Knowledge sharing Faster Decision-Making Better Teamwork More transparency & Visibility Wide range of Data Sources:  Data Source, in BI, refers to the location from where the information or raw data is originated. Our modern BI tools are designed so that they can pull data from various sources, such as Excel Workbook, SharePoint folder, Pdf, XML, JSON and even from the databases (SQL, Oracle & a lot more). Power BI, as a BI tool, has the ability to be connected with a MySQL database, and one can run SQL queries for more refined analytics. This ability to connect with more platforms makes Data Analysis more reachable for today’s professionals.  Top 5 Benefits of Business Intelligence (BI) : Today, businesses can collect data along with every point of the customer journey. This data may include different attributes, like system usage, no. of clicks, interactions with other platforms and a lot more. The organizations have the ability to pull this data from various sources & transform it into a meaningful insight that is easily understandable by everyone in the team. Following are some of the key benefits of adopting Business Intelligence: Fast & Accurate Reporting: Companies can create customized reports based on the data pulled from different data sources, including financial, operational & sales data. These reports are generated in real-time in the form of graphs, tables, charts etc. and can be shared easily within the same organization so that the team can make decisions quickly. Most of the visualizations created with BI tools are so interactive that anyone can play with the data by changing the variables. Valuable Business Insights: The reports generated from the BI tools help the organization understand what’s working and what isn’t. Hence, they can take necessary actions regarding the business process. Improved Decision Making: In today’s competitive business world, where customer satisfaction is paramount, it is required to identify the failures or business problems accurately and take necessary steps to stay on top of the industry. Hence, Business Intelligence comes into the picture, which helps to visualize the data rather than manual calculations using thousands of records. So, definitely, BI tools come in handy when it comes to better decision making. Identifying Market Trends: Analyzing new opportunities & building out strategies with supportive data can give organizations a competitive edge, thus impacting the long-term profitability. The companies can leverage market data with internal data & detect new opportunities by analyzing market trends & also by spotting business problems. Increased Revenue: Undoubtedly, this is the ultimate goal for any business. Data visualizations help organizations dig deeper into business problems by asking questions about what went wrong & how to make impactful changes in the business. When organizations take care of customer satisfaction, watch their competitors, & improving their own operations, revenue is more likely to increase. Popular BI Tools in 2021: Here are some popular BI tools which are trending in the market right now : Microsoft Power BI Tableau Board Domo Oracle Analytics Cloud Tibco Qlik SAS Business Intelligence Vs Business Analytics : Business Analytics & Business Intelligence are very similar and somewhat connected. Pat Roche, Vice President of Engineering at Magnitude Software believes, “BI is needed to run the business while Business Analytics are needed to change the business.” Although it’s a debatable topic, most people in the modern business world still believe that Business Analytics & Business Intelligence tend to work well when paired together. The main usage of BI is to present the data in front of the team in the form of various visualizations, thus helping them make the right business decision, whereas the role of business analytics is to ‘analyze the business’ & think of ways to improve a company’s future performance. Generally, both BI & BA requires analytical skills which ultimately helps the business to succeed. However, despite the similarities & differences between Business Intelligence & Business Analytics, we can certainly agree that both

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Top Tech News from Indus Net Technologies

September 15, 2016

LinkedIn Ducks Data With Lite To counter patchy data networks in India, LinkedIn is set to launch LinkedIn Lite, a lighter version that uses bare minimum data while browsing on mobile. This move certainly helps those with a slow Internet connection to join the world’s largest business network service. Also launched LinkedIn Placements and LinkedIn Starter Pack.  #mobile #social Chess Fans Couldn’t Have Asked For More Ever thought of watching a live sports event that takes you close enough to the player’s perspective, that too sitting at home? Well, now you can. Watch the upcoming World Chess Championship in a fully immersive 360 degree mode. Want to know how? #vr Google’s AI Speech More Real Than Humans’ You won’t believe your ears after hearing this robot speak.  Google’s new AI program WaveNet can synthesize human-like voice without any assistance. Soon you’ll be conversing naturally with your robot friend. Still can’t fathom it? Hear it for yourself. #ai  No More Constraints on Tweet Length From next week onwards, Twitter will not count attachments including pictures, GIFs and videos, as well as quoted tweets usernames as part of the 140 character-limit. Let your creative forces flow freely through longer tweets. But yes, there’s a small catch here. #social  5. Instagram Cracks The Whip on Trolls Taking the bully by its horns, Instagram enables you to keep trolls at an arm’s length. You can automatically filter inappropriate content from your comments feed.  There’s a lot more you can do to steer clear of hobgoblins.  #social  

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Today’s Top Tech News From Indus Net Technologies

September 14, 2016

New Tracking Sensors for Enriching Mobile VR uSens tracking sensors will enhance user interaction with virtual objects. The new sensors are inclined closely towards mobile VR.  Their advanced ability to messed up algorithm after Facebook laid-off its human editorial staff.  #social 3. Follow Wisely With Tailor-Made Instagram Stories Don’t worry if you find your Instagram friends boring. Instagram will now Behavioral Targeting will allow marketers to target users based on their activity within the app. Advertisers always felt a lack of targeting and measurement on Snapchat; better late than never. #social  5. Google Makes Tag Management Easier This new collaborative feature is aimed to resolve workflow challenges faced by team workers while

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Is Cloud Application Development for You?

October 30, 2015

Developing applications on a cloud-based platform entails your development team acquiring suitable skill sets. Despite its challenges, it distinctly leverages the capability of your organization. Cloud application development can be done in SaaS (Software as a Service), IaaS (Infrastructure as a Service) and PaaS (Platform as a Service).  According to a recent Gartner report, “Enterprise IT spending on public cloud computing, within addressable market segments, will overtake spending on traditional IT in 2025. In 2022, more than $1.3 trillion in enterprise IT spending is at stake from the shift to cloud, growing to almost $1.8 trillion in 2025.” The statistics clearly indicate that cloud application development is becoming crucial for organizations’ IT mix. Developing applications in the cloud comes with ample benefits like: Enabling developers to take virtual snapshots of troubling applications Leveraging economies of scale Improving productivity Cost efficiency and lifecycle management Challenges faced by developers Due to its ability to run the same program on many different systems, Java is one of the top cloud programming languages. Here we have listed some of the unique challenges faced by Java developers during development: 1.      Fragmented data As the business grows, the number of cloud applications deployed increases. Every application solves a different business problem. But this has resulted in fragmentation of business data across various disconnected applications. Developers are increasingly using low-code platforms to build applications. Though data can be easily tracked and may look to be at the same place, it is actually fragmented. Writing custom point-to-point integration in APIs or by adopting a standalone cloud integration platform like Zapier, Dell Boomi or Informatica, can solve this problem. Nonetheless, this task does require a specialized skill set in the development team.  2.      Understanding application resource dependencies A cloud application often runs in a distributed environment with at least two servers deployed for the operation. The primary focus for a developer is to understand application service dependencies. Application service dependencies include databases, message servers etc. In a cloud environment, several services interact amongst each other and developers can’t be sure what IP address the application uses. On the contrary, in a traditional application development environment, identification of resources is easy and a developer knows what service is being used by the application on deployment. Hence, the developer needs to understand service usability and be able to locate resources. Quite often, developers use a discovery pattern to find the services. In a Java application environment, the developer gets JNDI (Java Naming and Directory Interface) that helps in locating the services required. Resource mapping during deployment helps developers to avoid hard coding by following a logical sequence. 3.      Addressing horizontal scalability In cloud computing, horizontal scalability is the ability of the application to connect with multiple hardware or software such as servers when required. The connection enables the whole system to function as a single logical unit. Cloud applications, owing to their parental nature, are horizontally scalable. But unfortunately, not all applications are horizontally scalable.  This issue can be resolved by writing applications in a manner that renders them potentially scalable. 4.      Precautionary measures Localizing data storage can be fatal to your cloud infrastructure. The essence of cloud computing is to have distributed data management to dodge server failures. Furthermore, developers must rely on location patterns to abstract physical IPs rather than using physical IP or disk-based locators to find out resources for using in the application. 5.      Testing application in the cloud Developers often face the challenge of testing the application in a cloud environment. The transition process of application from the local environment to the cloud environment for testing is not free from glitches. Only a smooth transition will ensure product development cycle. So, the use of appropriate testing tools is important for a smooth transition. 6.      Inability to differentiate The majority of the organizations are relying on the same technology and same cloud-based platforms. So, it has become difficult for them to offer unique features to their clients. This undermines their ability to gain a competitive edge over others. No doubt, the development of cloud applications is cheaper and more efficient. But developers need to devise new capabilities, new strategies and follow an innovation-driven approach to entice their clients. Advantages of application development in the cloud The leading cloud-based development platforms in PaaS and IaaS include Google App Engine, Amazon Web Services, Microsoft Azure and Salesforce.com. Metrics review has already proven that cloud application development offers a lot of benefits like: 1.      Save application development and deployment time The application development time in the cloud is significantly lowered owing to the cloud platform’s ability to streamline the development process. The platform is further capable of quickly getting development assets online. Traditionally, the development of custom applications used to take months as developing a complete application required additional components. However, with cloud computing services, developers can quickly avail all the required software and tools in the cloud working their way out more efficiently. Furthermore, cloud applications can be deployed quickly by getting into production mode thus enabling less time to market. 2.      Cost-effective development environment By delivering applications through the SaaS model, organizations can save a lot of costs. Both financial and infrastructural worries have been side-lined by incorporating cloud computing services for application development. The capital investment required to set up a complex environment for building, testing and deploying custom applications was unfeasible for many small-scale organizations. The subscription models in cloud computing offer the clients the flexibility to spend as per their demand and avoid tying up additional hardware/ software costs. 3.      Simple and efficient Developers can easily access applications through a web browser. Even the most complex enterprise-level applications are developed without actually getting into technical complications. 4.      Optimum utilization of resources The IT resources are efficiently utilized while application development in the cloud. Moreover, applications utilizing virtualized IT services are technically more efficient and

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