Technological advancements and digitization have become inevitable in this online world. The more and more revolutions, world is growing faster than the previous day pace. In this, Big data is becoming a crucial part of these innovations. Many other technologies such as Artificial Intelligence, Machine learning, and emotion AI are all affected by the revolution of Big data. Even at industrial level, Big data and Artificial Intelligence techniques are used to streamline the practices of companies. For instance, finance industry is using blend of this technology for to deter the risks of financial crimes. So before this, let’s look into what AI and Big data are; fraud detection Big Data: Big data is a collection of huge datasets. This data could be structured or unstructured that can be used to identify different patterns, interests, and trends such as human behavior and interactions to provide tailored facilities based on them. Artificial Intelligence: A technology that is overcoming all the human tasks by automating the machines and letting them work just the way humans do by thinking like humans. Algorithms are used to analyze and learn how humans behave in certain circumstances. AI involves the determination and analysis of huge data. This data is then sued to train the machines against various behaviors to let them know how to automatically behave in certain conditions. This technology hance, performs various user tasks and takeover human power. Complex algorithms are run underlying the system to teach them and as a result, the output is expected. Neural networks are trained using AI algorithms so that against out of box input, using previous data, the system gives the right result. Actual Dataset for Machine Learning Models The machine learning systems were previously employed using a sample dataset that was used to trained and then tested by the developer’s machine learning models. Although that was a great approach towards training and testing the data, the limited amount of data does not cover a diversity of scenarios that can be given as input from the user side. Now for efficient Artificial Intelligence and Machine Learning models, a huge amount of data is needed. The data that belongs to diverse categories, resemblance, varieties, and forms, is more likely to produce efficient machine learning and AI models. Here, big data jumps in the game. Big data, a big name carries big power in automating the machine learning models with better accuracy and precision in results. Big data is generated and is considered the actual data that is produced by digital users, showing their interest, activities, and behaviors that help various businesses analyze the human behaviors over certain parameters. The same data can be used to train the models. Edge Computing Cloud computing is distributed computing in which data is processed and stored, computations are done at the edge of architecture. This is a cutting edge technology that is utilized across the industry. The concept of edge computing is used in the Internet of Things (IoT) to allow the system to collect, process and analyze the data directly from the source. Looking at the underlying scope, it is clearly depicted that edge computing is a small-scale representation of Artificial Intelligence that is using big data. IoT devices comprise various sensors, functions, specifications, and microprocessors that used to work in a decentralized and autonomous manner. They collect data and send it to some cloud storage where all the data can be seen and filtered as per need. There are multiple advantages of cloud computing: At the core, big data process huge data that is more than enough to analyze the data set to use appropriately. Although edge computing comprises of micro-controllers, microprocessors, and sensors, huge data empowers predictive computing and hence makes processing and computation power quicker and higher. In these systems, no particular or complex architecture is used, they are easy to maintain and deploy that also provides high-quality customer service. For edge computing, high-end processors are not required, therefore they serve the purpose of power consumption and are efficient in its operations. High Computation Power The processing power of machine learning models and even embedded systems is always a challenging task. Maintaining a balance between computation power and efficient results are always in the race. Similar is the case while deploying AI algorithms and techniques in the processors for computing. Processing abundant data in real-time and processing results simultaneously is the goal to achieve by AI models. For this, what developers do is, that they attach various GPUs and CPUs together to distribute the computational work among them and get huge filtered data at the same time. So that computation will increase and the availability of data will be there in time. Even for big data, it is true, but when big data is coupled with the techniques of edge computing, the overhead of computation power eliminates and therefore makes the system more efficient, robust and reliable. Intelligent Chatbots Today intelligent chatbots are integrated with online systems to supports customers and their queries. These bots are now hard to determine whether it is a real person or a chatbot behind the system to whom you are talking to. Years back, chatbots were not that much efficient that they efficiently handle every query of customers. But now, as big data is integrated into the systems and chatbots keep on learning new data, new queries and exercise daily, they are empowered in such a way that they are able to entertain queries of customers and answer them knowing the intend. Blockchain Era Blockchain technology is penetrating into various industrial use-cases. Other than the IT sector, from to finance and crypto industry to government practices, blockchain technology is harnessed. Blockchain is a decentralized way of securing data in the distributed ledger. This technology is able to secure huge digital data regardless of what size or format is. This leverage has made it quite easy for data analysts and scientists to secure all the confidential and abundant data into the blockchain to ensure its safety. Blockchain with big data is reshaping the digital world with splendid revolutions and innovations with each passing day. A combination of both these technologies is the future of file storage and management, networking and security systems. healthcare Artificial Intelligence and Big data are the major fields in the IT industry that together are going to tighten the reins of how digital world works.

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