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Clarity InsightsClarity Insights

Clarity Insights is the largest consulting company in the US that focuses exclusively on data strategy, engineering, science and visualization. We help our clients—Fortune 1000 companies across multiple industries—leverage data and analytics to find actionable insights that can help them seize new opportunities and solve their toughest business challenges.

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Predictions on Software Development Trends of 2022

Article | July 14, 2021

The world has started stepping into the “new normal” era. With the boost in vaccine inventions and countries rapidly vaccinating their citizens, we will be back to living a ‘new normal’ life. We keep mentioning normal as the ‘new normal’ because things will never be the same as before the pandemic. A majority of changes have happened for the best. Nevertheless, challenges emerged in the pandemic, and these were answered by innovations. Let us precisely talk about the innovations in software development trends. Digitalization played a vital role in transforming society and overcoming the hurdles created by the pandemic. Hybrid working style, chatbots, IoT, AI, and development in applications to improve performance and customer experience are the key software development trends that are on the rise. Growth Predictions Post Pandemic ● 63.3% of companies consider accelerated digital transformation. ● IaaS market solutions will be worth $64 billion. ● Online sales will account for 22% of global retail (currently it is 14%) ● The utilization of low code products will reach 50%. ● The outsourcing services industry is estimated to reach more than $66 billion. Software development trends have led to a boom in the software industry. As a result, all the sectors have turned towards software for solutions. Observing this change of scenario, here are some of the predictions on software development trends that will rule the industry by 2022. Software Development Trends IoT The combination of AI and Big Data with IoT has led to significant changes in the IoT industry. IoT has profoundly incorporated its way into daily human life. It eases everyday chores by connecting all the devices with sensors and syncs them automatically. The machines understand our timely needs and act subsequently. IoT has come a long way from just connecting the phone and the laptop. Instead, the day starts with Alexa, Siri, or Google. From telling them to turn on your coffee maker to adjusting your AC temperature, every little thing is manageable by the internet of things! As a result, more and more devices are built with sensors to simplify everyday processes. Thus, IoT is one of the software development trends to be utilized in various sectors by 2022. IoT has groundbreaking potential and has been adapted in smart cities. The smart cities project is a possibility only because of IoT. Progressive Web Apps (PWA) Progressive Web Apps are a trend in software development that is gaining popularity in these challenging times. PWA are apps that combine the functions of native apps and website accessibility. They provide the same user experience as native apps without having the hassle of upgrading and installing for web or mobile devices. Easy maintenance, one codebase, easily searchable, lightweight, and operating offline are some of the advantages of progressive web apps. PWA is here to stay and is the latest in software development. It is progressive, responsive, connectivity-independent, secure, easily installable, and linkable. As a result, many companies are switching their websites and apps to PWA for hassle-free code development and a great user experience. Low-Code Development Be it software developers, web developers, or users, low-code development is a hit amongst all. This new technology in software development saves time, is fast and intuitive. The long hours spent in coding every line are held by low code development. Herein the code is sketched like a flowchart and fed into the machine. As a result, a lot of manual effort is saved. Low-code development is one of the latest technologies in software and the future of the software industry. Traditional developers thought that this process did not have much potential, but the pandemic changed this thought. Low-code development will allow people with little digital skills to digitalize their ideas. Building apps quickly is the need of the hour, and low code development helps achieve that. This trend will also help in bridging the gap between the supply and demand of software engineers. AR (Augmented Reality) Augmented reality has appallingly changed the marketplace. Customers can virtually try new makeup or beauty products without even touching the product. The beauty industry has seen incredible conversion while using AR for its marketing. Similarly gone are the days of 2D mapping. AR has managed to bring 3D mapping into our lives. Be it gaming or navigation; augmented reality has strongly made things attractive. AR is a hit in advertisements. Companies are luring customers by adding filters or creating environments in apps. This has shown great conversion numbers to the businesses. This is because AR is software that is more than visually appealing. It improves functionality, enhances effectiveness, and creates brand value. As a result, we are going to see more from this technology in 2022. Big Data Using Big Data is building credibility. Security has a whole new meaning post-Covid-19. The public has become aware of the information that it will allow access to. This has led to a boost in the use of Big Data. By 2022 Big Data can be used as DaaS (Data as a Service). This will allow companies to access the required data, and thus redundancy is avoided. The use of Big Data has proven to provide data-driven solutions. It is giving the customers exactly what they are looking for. And this can be achieved only when you have proper segregation and security of a large amount of data. Netflix has proven its popularity by utilizing Big Data and giving the viewers the exact content they are looking for. Thus, Big Data is a software trend that will be a compulsion for companies to adapt in the future. AI (Artificial Intelligence) This list would be incomplete without mentioning the hottest software trend in the market these days. In the last five years, AI is one industry that has gained tremendous momentum. This is because machines are trained to think and perform tasks that were possible only for humans. The combination of machine learning, deep learning, neural networks, and machine control has already enhanced customer experience in various sectors. The improved user experience, better efficiency, less prone to errors, reduced costs, and increase in ROI have made AI a dominant trend in the technology world. By 2022 there will hardly be a sector that has not implemented AI. From the demand and supply chain industry to predicting stock markets, we will see a lot of AI everywhere. Conclusion: Be Ready for 2022! These are some of the predictions of software development trends 2022. There will be enormous changes in the lifestyle, working style, and adaptive measures taken by humans. And in this changing era, technology trends will guarantee maximum productivity along with comfort. As the pandemic unfolds and most of the population gets vaccinated, there will be turning points in the latest software trends and the IT industry. There will be minor glitches and fluctuations, but these newest software development trends will help overcome them all. They assure an increase in revenues and adding value to the brand of the company. Software development is not just a trend in software engineering but a process of continuous innovation. Of course, the predictions of technological processes are pretty unpredictable as inventions surge. But one predictable thing is that game-changing technology trends will keep emerging, and there are no stopping innovations in these fields. Frequently Asked Questions What are the top 3 emerging technologies in software? AI (Artificial Intelligence) dominates the emerging technology industry, followed by IoT (Internet of Things) and then AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality). These play a predominant role in changing the face of technology. What is trending in software development nowadays? The current trends in software development are AI chatbots, powerful programming languages, and active incorporation of IaaS, PaaS, SaaS, DaaS to provide flexibility and improve productivity. These effective solutions are implemented to build apps, websites, manage hybrid working culture, and ease communication processes between teams. Why should you track trends in software development? It is the need of the hour to digitalize the business. If you keep up with the rapidly changing software trends, you can be distinguished from your competitors, and it will help you stay ahead of the race. Your products/services will be productive, efficient, and trusted by the customers. If you do not digitalize your businesses and incorporate the required technology, your business will cease to exist. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What are the top 3 emerging technologies in software?", "acceptedAnswer": { "@type": "Answer", "text": "AI (Artificial Intelligence) dominates the emerging technology industry, followed by IoT (Internet of Things) and then AR (Augmented Reality), VR (Virtual Reality), and MR (Mixed Reality). These play a predominant role in changing the face of technology." } },{ "@type": "Question", "name": "What is trending in software development nowadays?", "acceptedAnswer": { "@type": "Answer", "text": "The current trends in software development are AI chatbots, powerful programming languages, and active incorporation of IaaS, PaaS, SaaS, DaaS to provide flexibility and improve productivity. These effective solutions are implemented to build apps, websites, manage hybrid working culture, and ease communication processes between teams." } },{ "@type": "Question", "name": "Why should you track trends in software development?", "acceptedAnswer": { "@type": "Answer", "text": "It is the need of the hour to digitalize the business. If you keep up with the rapidly changing software trends, you can be distinguished from your competitors, and it will help you stay ahead of the race. Your products/services will be productive, efficient, and trusted by the customers. If you do not digitalize your businesses and incorporate the required technology, your business will cease to exist." } }] }

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Helping Customers Reach the Cloud Benefits

Article | July 14, 2021

Get to know Klas and his story! With strong background in change and product management in IT, Klas Erikson started at Nordcloud as a Cloud Advisor and is nowadays heading Nordcloud’s delivery and operations in Sweden, Norway and Denmark from our Stockholm office. Where are you from and how did you end up at Nordcloud? I am from Stockholm, Sweden and have been working most of my career in Telia here in Stockholm. I left Telia after the organisation had, yet another time, changed and I felt I needed to try something completely different. I had already started talking with my old colleague working for Nordcloud and was fascinated by a company in such fast growth.

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Basics of Artificial Intelligence and Machine Learning

Article | July 14, 2021

Lately, we all often come across two very hot buzzwords — Artificial Intelligence (AI) and Machine Learning (ML). Perhaps the impact of artificial intelligence and machine learning on today’s business world is more than our daily lives. According to a Bloomberg report, around $300 million were invested in 2014 to promote AI-powered startups. It was 300% more than the previous year’s investment in venture capital. It’s hard to deny the fact that artificial intelligence and machine learning are all around us. Whether it is about protecting confidential information at work or just playing your favourite games on PS5, AI and ML are there. Researchers, scientists, computer engineers, and analysts are working hard together to pass on human-like intelligence in machines so that they can think and act according to real-life scenarios. Businesses have changed their approach to AI keeping enterprise adoption in mind rather than treating it as just a research topic. Tech giants such as Google, Facebook, Microsoft have already invested billions in Artificial Intelligence and Machine Learning and already have started to reshape the customer experience. But the AI and ML incorporation we see today is just the tip of an iceberg. In the coming years, you will see them take over products and services one after another. What Is Artificial Intelligence and Machine Learning? It is nowadays common to see several companies marketing themselves as AI-powered startups even though their operations don’t really revolve around AI. To understand this type of gimmicky marketing, it is essential to first understand what Artificial Intelligence and Machine Learning are. Let’s be clear in the beginning about one fact — AI and ML are not the same things. If you think they are, kill this perception before it makes things very confusing. Both these terms crop up especially when the discussion is about the use of Artificial Intelligence in marketing, the use of Machine Learning in marketing, analytics, Big Data, and the modern-day tech that is transforming the world. To ease down the learning, here’s the best answer: Artificial Intelligence is a science used to develop systems that can mimic decision-making and behaviour like humans. In simple words, the main application of Artificial Intelligence is to make intelligent machines. Machine Learning is the subset of artificial intelligence that uses data to perform tasks. It involves designing and applying the data models or algorithms that can learn from their past experiences. There’s a subset of Machine Learning, too — Deep Learning. It counts on multilayered neural networks to perform tasks. Early Days of Artificial Intelligence The early mentions of AI trace back to Greek mythologies that have stories of a mechanical man that could mimic our own behaviour. Plus, the early computers were termed as “logical machines'' in Europe. These machines could solve arithmetic operations and even store memory. Scientists, fundamentally, were inspired by them to create mechanical brains. Over time, technology got more and more modern. And, our understanding of how the human mind works improved. Both these factors lead to the current AI revolution. Today, the use of AI is more focused on mimicking the decision-making process of humans rather than performing complex calculations. The prime motive of this is to allow machines to think and act more like humans. AI-powered machines that are designed to act intelligently come into two basic groups — General AI and Applied AI. General AIs are relatively less common and can theoretically handle any task. The most exciting improvements in the field of AI are happening in this specific area. In fact, it’s generalized AI that led to the rise of Machine Learning. On the other hand, applied AIs are designed to perform relatively smaller tasks like smartly trading shares and stocks, or guiding an autonomous vehicle to its destination, etc. The Rise of Machine Learning As mentioned earlier, Machine Learning is a subset of AI and can also be treated as the current state-of-the-art. It came into reality primarily because of the two major breakthroughs — the rise of the internet and human realization. In 1959, an American pioneer in the field of computer gaming and AI, Arthur Samual, realized that it can be possible to teach machines how to learn to perform tasks themselves rather than us telling them how to. As long as the emergence of the internet is concerned, that helped scientists with tons of digital information that could be analysed for the betterment of AI and eventually, ML. After these innovations, it was more efficient for scientists and engineers to program machines in a way that they learn to think like humans and then connect them to the internet so that they have all the needed information. Vertical AI And Horizontal AI No matter what kind of AI research it is, knowledge engineering is its essential part. Machines need plenty of information to think and act like humans. Therefore, AI needs access to objects, categories, properties, and relations between them to apply knowledge engineering. AI is responsible for generating analytical reasoning power, problem-solving abilities, and common sense in machines. And, it is not an easy task! The way AI serves us can be divided into two parts — Vertical AI and Horizontal AI. Vertical AI is used to perform single jobs such as automating repetitive tasks, scheduling meetings, etc. Vertical AI bots are so accurate in performing a single job that people often mistake them for human beings. Horizontal AI, on the other hand, can handle more than one task at the same time. The best examples of horizontal AI are Alexa, Siri, and Cortana. Different Types of Machine Learning ML can be best used to fix complex tasks such as enabling self-driving cars, face recognition, credit card fraud detection, etc. It uses huge, complex algorithms that keep on iterating frequently over big data sets. The following are the 3 major Machine Learning areas: ● Reinforcement Learning ● Unsupervised Learning ● Supervised Learning Reinforcement Learning In reinforcement machine learning, algorithms allow machines and software agents to automate ideal behaviour within a particular context to improve the performance of an overall system. It is characterised by learning problems rather than learning methods. If any method can solve a problem, it can be a reinforcement learning method. This Machine Learning technique assumes that the dynamic environment is connected to a software agent such as a computer program, bot, or robot. Ultimately, it chooses a specific action in order to rapidly deliver the most efficient result. Unsupervised Learning Due to the involvement of unclustered data, unsupervised machine learning is more complex than others. With it, the machine has to learn independently without any supervision. No fixed or correct solution is provided for any problem in this technique. The algorithm has to identify the data patterns and find the solution. The recommendation engines we see on several eCommerce websites and Facebook friend requests suggestions are the best examples of this sort of Machine Learning. Supervised Learning Training datasets are used in supervised learning. The algorithms are created in such a way that they can analyse the data patterns and develop an inferred function. The produced correct solution is then used to map new examples. The best example of supervised machine learning is credit card fraud detection. Final Words Artificial Intelligence and Machine Learning never fall short to surprise us with their exciting innovations. Their impact has reached all the industries including eCommerce, customer service, finance, education, healthcare, pharma, infrastructure security, and whatnot. Needless to say, all these industries are very keen on reaping all the benefits of Artificial Intelligence and Machine Learning. The human-like AI was an inevitable thing as most technologists thought. Today, we are indeed closer to this goal than ever. This exciting journey in the past couple of years is the result of how we predict AL and ML works. FAQs Why is AI Marketing important? With AI marketing, businesses and marketers can analyse and consolidate a large amount of data from emails, social media, and other platforms faster. The achieved insights can be used to improve campaign performance and eventually boost the returns on investment in a relatively lesser time. AI marketing is the best and the most efficient way to eliminate the risks of human errors while optimizing and streamlining the campaigns more effectively. The following benefits of AI marketing justify the attention it has received all over the world. ● A better understanding of your consumers ● Optimization of digital advertising campaigns ● Offer comprehensive customer profiles ● Allow real-time interactions with consumers ● Refined content delivery ● Reduced marketing costs ● Improved ROI Is artificial intelligence and machine learning the same? The straight answer to this question is NO. They are not the same thing. AI allows machines to learn human behaviour while ML is the subset of AI that teaches machines to learn on their own with the help of past data. Does AI need machine learning? Fundamentally, ML is not required for AI as AI systems do not need to be pre-programmed. Instead of such software agents, they get help from algorithms that can use their own intelligence to solve queries. These can be Machine Learning algorithms such as Deep Learning neural networks and Reinforcement Learning algorithms. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Why is AI Marketing important?", "acceptedAnswer": { "@type": "Answer", "text": "With AI marketing , businesses and marketers can analyse and consolidate a large amount of data from emails, social media, and other platforms faster. The achieved insights can be used to improve campaign performance and eventually boost the returns on investment in a relatively lesser time. AI marketing is the best and the most efficient way to eliminate the risks of human errors while optimizing and streamlining the campaigns more effectively. The following benefits of AI marketing justify the attention it has received all over the world. A better understanding of your consumers Optimization of digital advertising campaigns Offer comprehensive customer profiles Allow real-time interactions with consumers Refined content delivery Reduced marketing costs Improved ROI" } },{ "@type": "Question", "name": "Is artificial intelligence and machine learning the same?", "acceptedAnswer": { "@type": "Answer", "text": "The straight answer to this question is NO. They are not the same thing. AI allows machines to learn human behaviour while ML is the subset of AI that teaches machines to learn on their own with the help of past data." } },{ "@type": "Question", "name": "Does AI need machine learning?", "acceptedAnswer": { "@type": "Answer", "text": "Fundamentally, ML is not required for AI as AI systems do not need to be pre-programmed. Instead of such software agents, they get help from algorithms that can use their own intelligence to solve queries. These can be Machine Learning algorithms such as Deep Learning neural networks and Reinforcement Learning algorithms." } }] }

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What is AI-guided selling?

Article | July 14, 2021

B2B selling has become increasingly complex for buyers and sellers. Buyers are inundated with content on a variety of channels, from an assortment of vendors. Sellers are often pulled in several directions, with many tasks and responsibilities to tackle. AI-guided selling is helping sellers navigate the complexity of digital-first sales cycles. Artificial intelligence (AI) and machine learning (ML) are helping sellers realize this vision by transforming data from content analytics into intelligent insights that enable go-to-market teams to make the most of every revenue moment. In this post, we’ll share the ins and outs of AI-guided selling, how it will affect go-to-market activities, and what it means for the future of sales and marketing.

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Spotlight

Clarity InsightsClarity Insights

Clarity Insights is the largest consulting company in the US that focuses exclusively on data strategy, engineering, science and visualization. We help our clients—Fortune 1000 companies across multiple industries—leverage data and analytics to find actionable insights that can help them seize new opportunities and solve their toughest business challenges.

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