Big Data Analytics

Big data analytics probe and analyze huge amounts of data to i.e., big data - to uncover hidden patterns, unknown co-relations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. Operate and carry by specialized analytics systems and software, big data analytics can lay the way to various business benefits, including new revenue opportunities, more effective marketing, improved operational efficiency, competitive advantages and better customer service.

 Descriptive Analytics: This summarizes past data into a form that people can easily read. This helps in creating reports, like a company’s revenue, profit, sales, and so on. Also, it helps in the tabulation of social media metrics.

 Diagnostic Analytics: This is done to understand what caused a problem in the first place. Techniques like drill-down, data mining, and data recovery are all examples. Organizations use diagnostic analytics because they provide an in-depth insight into a particular problem.

 Predictive Analytics: This type of analytics looks into the historical and present data to make predictions of the future. Predictive analytics uses data mining, AI, and machine learning to analyze current data and make predictions about the future. It works on predicting customer trends, market trends, and so on.

 Prescriptive Analytics: This type of analytics prescribes the solution to a particular problem. Perspective analytics works with both descriptive and predictive analytics. Most of the time, it relies on AI and machine learning.

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Big Data in Nursing Research

With advances in technologies, nurse scientists are increasingly generating and using large and complex datasets, sometimes called “Big Data,” to promote and improve Health Conditions. New strategies for collecting and detailed examination large datasets will allow us to better understand the biological, genetic, and behavioural underpinnings of health, and to improve the way we prevent and manage illness.

Big data of nursing refer to the vast amount of data related to care and health, including big data of hospital nursing, big data of regional health service platform, and big data based on nursing research or disease monitoring in large populations.

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Big Data Technologies

Big Data is the name given to huge amounts of data. As the data comes in from a variety of sources, it could be too diverse and too massive for conventional technologies to handle. This makes it very important to have the skills and infrastructure to handle it intelligently. There are many of the big data solutions that are particularly popular right now fit for the use.

 • Operational Big Data Technologies

• Analytical Big Data Technologies

• Foremost Big Data Technologies Trending in 2020

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Big Data and Data Sciences

Big data approach cannot be easily achieved using traditional data analysis methods. Instead, unstructured data requires specialized data modelling techniques, tools, and systems to extract insights and information as needed by organizations.

Data science is a scientific approach that applies mathematical and statistical ideas and computer tools for processing big data. Data science is a specialized field that combines multiple areas such as statistics, mathematics, intelligent data capture techniques, data cleansing, mining and programming to prepare and align big data for intelligent analysis to extract insights and information.

• Unstructured data – social networks, emails, blogs, tweets, digital images, and digital audio/video feeds, online data sources, mobile data, sensor data, web pages, and so on.

• Semi-structured – XML files, system log files, text files, etc.

• Structured data – RDBMS (databases), OLTP, transaction data, and other structured data formats.

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Big Data to AI

Artificial intelligence is entering a rapid transition from theory to reality, which will greatly improve our quality of life. As an engine of big data, artificial intelligence is accelerating the implementation of deep data application services. In the era of massive connections in which the Internet of Everything data is exploding, we believe that companies that have mastered artificial intelligence and big data-related technologies will become the wave of the times.

Big data isn’t quite the term de rigueur that it was a few years ago, but that don’t mean it went anywhere. If anything, big data has just been getting bigger. That once might have been considered a significant challenge. But now, it’s increasingly viewed as a desired state, specifically in organizations that are experimenting with and implementing machine learning and other AI disciplines.

“AI and ML are now giving us new opportunities to use the big data that we already had, as well as unleash a whole lot of new use cases with new data types, senior digital strategist at Anexinet. “We now have much more usable data in the form of pictures, video, and voice [for example]. In the past, we may have tried to minimize the amount of this type of data that we captured because we couldn’t do quite so much with it, yet it  would incur great costs to store it.

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Forecasting from Big Data

Forecasting is to predict or estimate (a future event or trend). For businesses and analysts forecasting is determining what is going to happen in the future by analysing what happened in the past and what is going on now.

Big Data is a revolutionary phenomenon has recently gained some attention in response to the availability of unprecedented amounts of data and increasingly sophisticated algorithmic analytic techniques. Big data play a critical role in reshaping the key aspects of forecasting by identifying and reviewing the problems, potential, better predictions, challenges and most importantly the related applications.

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Cyber Security and Data Analytics

Cyber security analytics combines big data capabilities with threat intelligence to help detect, analyse and alleviate the insider threats, as well as targeted attacks from external bad actors and persistent cyber threats.

Security analytics can be implemented for a wide variety of use cases, from user behaviour monitoring to network traffic analysis. Some of the most common use cases include:

• Analysing network traffic to detect patterns that indicate a potential attack

• Monitoring user behaviour, especially potentially suspicious behaviour

• Detecting insider threats • Detecting data exfiltration

• Identifying accounts that may have been compromised.

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Artificial Intelligence

Artificial Intelligence (AI), is the ability of a computer-controlled robot to perform tasks commonly associated with intelligent beings. Integration of various systems is necessary for a promising Artificial Intelligence. The pillars of Modern AI include computational intelligence, Neural Networks, Genetic Algorithms, Swarm Algorithms and Fuzzy Logic. Modern AI uses tools and data from the fields like computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory etc. The above session will put a clear picture about various facets of Modern Artificial Intelligence.

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Cloud Computing

Cloud computing is the delivery of computing services—servers, storage, databases, networking, software, analytics, and more—over the Internet (“the cloud”). Cloud computing relies on sharing of resources to achieve coordination and economies of scale, similar to a public utility. Companies offering these computing services are called cloud providers and typically charge for cloud computing services based on usage.

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Artificial Intelligence in Healthcare

Total overall spending on Artificial Intelligence (AI) will reach $40.6 billion by 2024. Recent years have recognised the innovative development brought by AI technologies. These changes can advance many practices and health is no protection. The amazing changes in healthcare also brought many research opportunities in huge range of application fields, such as Health, health data quality assessment, personalized health with sensor data, cross-source learning for better lifestyles and health data visualization. The part of AI advance in client benefit and the test postured by AI calculations which are set to change the financial managements division.

Artificial intelligence in healthcare is an overarching term used to describe the use of machine-learning algorithms and software, or artificial intelligence (AI), to mimic human cognition in the analysis, presentation, and comprehension of complex medical and health care data.

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Artificial Intelligence in Block Chain Technology

Block chain and AI are two of the technologies are trending now and these two technologies are really different developing assemblies and applications, Integrating the two can lead to solutions for challenges that have been worrying crucial players for long periods of time. Block chain provides a way to exchange value embedded data without abrasion and AI enables putting data into action to create value without human efforts. AI can be used as the leading factor for maintaining immutability in a block chain network thereby making one in the entire world’s most secure ecosystem for transactions and data exchange.

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Embracing the Future AI

The future Artificial Intelligence (AI) has the possible to change the world. While from the time when the Turing Analysis was introduced, computers have become so smart. Artificial Intelligence is quick turning into a major economic energy. Definitely it will be an essential part of human life in future. However, an important question remains is that what will occur if the review of robust Artificial Intelligence be successful and an Artificial Intelligence system come to be better than humans. We have confidence in this session will help us to discuss, improve and avoid such possible outcomes in the future.

Time since the Turing test was offered, computers have become so intelligent. Artificial Intelligence is fast becoming a major economic force. For sure it will be an integral part of the human life in the future. However, an important question remains is that what will happen if the pursuit for strong Artificial Intelligence succeeds and an AI system becomes better than humans. We need to discuss, prepare and prevent such potential outcomes of the future.

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Internet of Things (IOT)

The Internet of things (IoT) is the network of physical devices, vehicles, home appliances and other terms embedded with electronics, software, sensors, actuators,and network connectivity which enable these objects to connect and exchange data. Each thing is uniquely identifiable through its embedded computing system but is able to inter-operate within the existing Internet infrastructure The Internet of things allows objects to be sensed or controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems, and resulting in improved efficiency, accuracy and economic benefit in addition to reduced human intervention. When Internet of things is augmented with sensors and actuators, the technology becomes an instance of the more general class of cyber-physical systems, which also encompasses technologies such as smart grids, virtual power plants, smart homes, intelligent transportation and smart cities.

• IoT Security

• IoT Analytics.

• IoT Device (Thing) Management.

• Low-Power, Short-Range IoT Networks.

• Low-Power, Wide-Area Networks.

• IoT Processors.

• IoT Operating Systems.

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IoT- The Way Forward

Surely the future will be much different from the present. Connecting everything through the Internet of Things devices will radically change our world in ways we can ever imagine. Infect it will change the way we think, live and act. However, every change involves many questions which need to be addressed. Greater connectivity through the Internet of Things helps to provide new business and social opportunities but simultaneously demands more responsibility. As the risk is higher, the demand for qualified professionals is also high who can tackle the complex IoT situation.

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IoT-Systems of Systems

The Internet of Things (IoT) refers to the networked interconnection of objects equipped with ubiquitous intelligence, or simply “smart objects”. Several endeavors have been made in the last decade to bring together standard modelling languages with generic simulation frameworks. The applications for internet connected devices are widespread. A growing number of Internet of Things (IoT) devices are designed for human use. This session will how the IoT has been now an inseparable part of our lifestyle and the issues and technologies related to it.

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