THE DIGITAL REVOLUTION AND PREDICTIVE ANALYSIS
With predictive analysis, future results are sought using data from the past; the models use different methodologies and mathematics with a very similar general objective; there are some techniques that are specific to classification (the results of the model are binary; a yes or no, in the form of 0 and 1) and others that are regression techniques that allow a value to be predicted. It can also be applied to any type of unknown event in the past, present, or future.
The Digital Revolution provides BIG DATA with an abundance of structured variables, such as data tables, and unstructured variables, such as texts, images, or videos, it offers new possibilities for prediction and brings about a change in layout. Flexible and heterogeneous prediction rules are now being built with a proven ability to predict well data different from those used to estimate them; the final predictor used combines different models, procedures, and data types.
Decision Trees, Neural Networks, Support Vector Machines, Bayesian Analysis, Logistic Regression, Linear Regression, Time Series and Data Mining, K-Nearest Neighbors, Ensemble Models, Gradient Boosting, Incremental Response Models, Replace, Introducing Multiple parameters extracted from Big Data, with many advantages over the models traditionally used by statistics.
Big Data Analytics is the technology used to analyze a huge amount of structured and unstructured data that is collected, organized, and interpreted by software, transforming it into useful information for decision-making and to generate ideas about market trends. In addition, it contributes to the generation of ideas for new products and services, customer attraction, audience understanding, security, and more benefits to making strategic decisions.
The most used models are:
- Decision Trees, are statistical algorithms or Machine Learning techniques that allow us to build predictive data analytics models for Big Data based on classification according to certain characteristics or properties, or on regression through the relationship between different variables to predict the value of another.
- Neural Networks, Artificial Intelligence, and Deep Learning, a pattern recognition technique that mimics the neurons of the human brain, capable of modeling extremely complex relationships and using them when the exact nature of the relationship between input and output values is not known. The exit ones. Deep learning processes data to detect objects, recognize conversations, translate languages, and make decisions.
- Support Vector Machines (SVM), are supervised machine learning algorithms in order to recognize patterns and status related to classification or regression problems.
- Bayesian analysis, is a statistical inference in which evidence or observations are used to update or infer the probability that a hypothesis might be true.
- Logistic Regression and logistic regressions are used to predict the result of a categorical variable (a variable that can adopt a limited number of categories) based on the independent or predictive variables. It is useful for modeling the probability of an event occurring as a function of other factors. For example, it can be used to predict credit risk.
- Linear Regression, consists of a straight line that shows the “best fit” of all the points of the numerical values. It is also called the method of least squares because it calculates the sum of the squared distances between the points that represent the data and the points on the line that the model generates. Thus, the best estimate will be the one that minimizes these distances.
- Time Series and Data Mining, consists of using large databases to obtain perspectives on behaviors that are repeated consistently. This is achieved by developing algorithms that manage to identify patterns in the data and establish correlations between them.
- K-Nearest Neighbors is a clustering algorithm. It consists of recognizing patterns to calculate the probability that an element belongs to a class according to its proximity in space to the elements of that classification. It is a method of classifying cases based on their resemblance to others; it was developed as a way to recognize patterns in data without the need for an exact match to stored patterns or cases.
- Ensemble Models is famous for its accuracy due to the availability of boosting and bagging algorithms, which are general procedures for reducing the variance of a statistical learning method. The basic idea is to combine simple (weak) prediction methods, to obtain a very powerful (robust) prediction method. Create a new model by training multiple similar models and combining the results to improve accuracy, reduce variance and bias, and identify the best model to use with new data.
- Gradient Enhancement, performs a resampling (resampling method [H1] ) of a data set to generate results that form a weighted average of the data set. It can also be used to build hypothesis tests
- Incremental Response Models, used to reduce Churn or check the effectiveness of different marketing actions. The probability change caused by an action is modeled.
The most used advances to implement the new developments are:
Until now, the latest development of mobile networks to meet the demands of connectivity and solutions of Artificial Intelligence, Big Data and Internet of things, designed to react faster from a distance, such as for a directed surgery, a video conference, a robot. It will allow mobilizing offices to operate from anywhere as required by the financial sector, health institutions and retail businesses; advice can also be provided with applications such as Virtual Reality and Augmented Reality.
Robotic Process Automation (RPA)
RPA is the way in which a software robot, also called a bot, is designed to imitate or replace human actions and can execute a set of previously programmed instructions. These are not physical robots, but virtual ones, in the form of a software interface. In addition, it should be noted that to automate you must have a digital data input and send the robot a series of instructions based on clear rules.
They are the automation tools that allow simulations in business methods and are essential to identify, describe and improve the processes that make the organization work. It is the basis for determining which parts of the processes can be modified to make the business more efficient and competitive. New technologies thus allow cost savings and facilitate simulations to see if the planned changes are feasible and will give good results.
You can do routine work to streamline tasks that do not require creativity and critical vision, freeing up human resources for other tasks that require it. Artificial Intelligence also allows programming bots that are designed to imitate or replace human actions. They operate in an automated way, so they can work much faster than a person. This way they can dedicate better customer service by emulating the rational logical thinking of people. Currently, AI is present in mobile facial detection, or virtual assistants.
Blockchain technology is one of the most innovative and disruptive concepts of recent years. It is based on a decentralized and public blockchain of operations. This technology generates a shared database to which its participants have access, who can track each transaction they have made. It is like a large, unchangeable, and shared ledger that is written by a large number of computers simultaneously.
It is the basis of crypto-economics and represents the greatest advance in cyber security at the business level and minimizes the risk of carrying out operations in the metaverse, where the actors do not know each other. In addition to being an almost infallible way of tracing the course of a transaction (as long as the currencies are not Cryptocurrencies), it is also used for countless other processes. For example, Blockchain can be used in the area of Human Resources, especially in personnel selection, since it allows candidates to be identified thanks to the analysis of their professional profiles. In this way, subjective criteria are eliminated in the selection processes and hiring times are greatly reduced.
Closely related to the Blockchain, the crypto economy is becoming more and more fashionable. The rise of Bitcoin and other Cryptocurrencies such as Ether has made it possible to pay for almost any type of product or service, such as a house, employee salaries, coffee, or computer programs. Today, nobody knows what the future of the crypto economy will look like, but all experts agree that it will continue to be one of the booming trends in the coming years.
Internet of Things
The Internet of Things refers to everything related to the connection of devices and objects other than computers and mobile devices to the Internet. It is about connecting everyday objects such as appliances, clothing, or any other object to the Internet.
Most companies are looking at how they can integrate the Internet of Things into their processes. It is not necessary that they are digital companies, but traditional companies also need to transform their business by applying new technologies such as IoT. The food industry, for example, uses sensors to know when and how to irrigate fields and automate packaging and logistics processes.
On the other hand, there is augmented reality. Technologies based on augmented reality allow a new user experience to be provided to customers and also to all those people who are part of your value chain. In simple terms, Augmented Reality allows you to apply some aspects and facilities of the digital world to the physical world; very useful in sales and marketing, especially if the company offers physical objects that can be represented through augmented reality in a digitized way.
Data analysis helps us describe, explain and predict consumer behavior, as well as business operation, adding artificial intelligence tools, such as Machine Learning. In this way, the speed of the analytical processes is greatly increased and allows the processing of large amounts of data. This new paradigm can be implemented in any type of industry, especially for those that work with experts in Big Data and are interested in introducing Artificial Intelligence into their processes.
The metaverse is a digital reality that can be accessed with special devices such as virtual or augmented reality glasses, through which it will be possible to interact with other users. Each of these users has an avatar (their character in the virtual world) and will be able to work, have social gatherings and even play with other users in investment worlds. These are interactive spaces, with corporeal environments, autonomous by themselves, decentralized, without limits, and with virtual economies.
By 2023, the most advanced use of technology such as action conquest is projected, which will mean that in addition to looking and sounding more, avatars will adopt our own unique gestures and body languages. We may start to see more developments in the fields of autonomous avatars, meaning they won't be under our direct control, but AI (artificial intelligence) will enable them to act like us in the digital world as we interact with each other. other people, completely alien and allows the representation in the virtual world of everything that exists in the physical; the avatar is the representation of a human being in the digital world and is very applicable in medicine for remote surgeries. A person in the physical location wearing the glasses, while the specialist sees the scene and guides the process.
Using remote control, a technician can carry out maintenance or repair of a machine, however complex it may be, from the country where it has headquarters in less time than required, reducing many expenses (transport, hotels and others) through the devices of augmented reality. Communicating with a native allows you to acquire phonetic notions that facilitate learning by democratizing access to speakers of all languages and voice recognition allows you to evaluate pronunciation and make contact through non-verbal communication, a fundamental aspect when learning a new language.
Any company, whether large or small, should make it a top priority to invest in Cyber security that not only protects your databases, but also your networks and applications. A breach in security could even mean the end of the business, or at least the reputation with customers, employees, and suppliers. It is important to take into account the Data Protection Law (GDPR) that affects all European countries and ensure compliance with the law. If not, it exposes itself to paying fines to the public entities responsible for data protection.
Any person or animal can be susceptible to wearing a wearable,
(set of electronic gadgets and devices that are incorporated into some part of the body and interact continuously with the user and with other devices to perform a specific function, such as smartwatchs or smartwatchs, sports shoes with built-in GPS and wristbands that control the state of health, are examples among many others of this technological genre that is little by little more present in human life) everywhere. This not only implies that the possibilities of this new technology must be taken into account, but also that the enormous amount of data generated by each wearable device can be used. A smartwatch (an intelligent watch that has the peculiarity of being linked and synchronized with the Smartphone). A Fitbit can give a lot of information about the user who wears it: how many kilometers he walks a day, what kind of distances he travels, how many hours a day he sleeps, what is his maximum activity time, etc.
New technologies provide endless opportunities, both in terms of improving productivity and saving costs for organizations and people who want to specialize in one of the area’s most in demand by companies and with a promising future, taking advantage of the options offered by universities.