Big Data's value, popularity, and scale of usage in business today come from a few of the indisputable benefits it has to offer: The data is coming from various resources that contribute to its accuracy; The constant influx of data guarantees its relevance; Instead of manual analysis, it is processed automatically with the help of algorithms, which reduce the error probability and allows increasing the data volume; Centralized data access has become possible with the help of Big Data technologies. The world statistics show that since 2015. the number of companies using Big Data has grown from 17% to 50% The increase rate is impressive, and the truth is, it’s no longer just a fancy word a cool tech guy would use when discussing what’s behind supercomputer VIKI from . I, Robot In fact, many large industries have already adopted Big Data technologies and are gaining profit. In this article, I'll look at three industries in which big data is making a dent in 2020. Big Data in Medicine and Healthcare When discussing Big Data in healthcare, one should distinguish the three aspects of its application. Firstly, it’s the so-called . clinical aspect that involves disease diagnosis, treatment, and prevention Then comes aimed at better management of healthcare institutions by improving their operational and economic efficiency, on both regional and governmental levels. the management aspect Finally, is the one where Big Data can play a truly revolutionary role. Disease studies and drug development are the core areas here. the scientific aspect How exactly can Big Data technologies be useful to a particular patient and a specific doctor? The fundamental concept lies within the development of electronic health records (EHR). is a system that related to an individual’s health. EHR contains the , all the hospitalization records and doctor visits, laboratory tests, vaccinations, examinations, allergies, or any other related facts. Apart from serving as a storage of accurate medical data, EHR can control the patient undergo regular screenings and treatments by sending corresponding reminders and notifications. EHR collects and stores medical and other personal data patient’s disease and ailments’ history Many experts claim Blockchain to be a good technology choice for EHR: it fulfills some of its major requirements, such as completeness of data, its protection, and verification. makes it possible to use millions of EHR’s for as social, territorial, age-related, demographic, genomic, etc., which in its turn, allows providing a patient with exceptionally individual recommendations. The synergy of these three rising technologies allows creating a diagnostic system of a brand new quality level. Combining Blockchain with Big Data and AI detecting hidden dependencies between a disease along with other side-factors is a prototype example of such a system. Its database as well as 2 000 000 text pages from medical journals and clinic tests. By processing this data, the program . Watson for Oncology by IBM includes more than 600 000 diagnosis records can produce the most optimal treatment plan A retrospective analysis of treatment plans prescribed says that in regards to lung cancer, . In comparison, the rate of around . Watson selected efficient treatment tactics in 90% of the cases US hospitals averaged 50% Big Data also represents the core technology for forecasting medical institutions’ spending. It relies on a multifactor analysis of such statistical data as the number of repeat visits, ailments recorded against specific experts and departments, the prevalence of certain pathologies, number of chronic patients, epidemiologic indicators, etc. serves as a good example here: they . Repeated hospitalization, missed doctor appointments, drug supply are the major factors included. British National Health Service use Big Data to analyze the efficiency of surgery sub-departments McKinsey’s recent research says that . McKinsey reports that it can be achieved through Big Data capability to unite the data stored in separate sources wholly isolated from one another. For instance: Big Data helps to not only reduce healthcare costs but also contributes to the quality of life enhancement Consolidating these types of data from the sources above opens up unique possibilities for the medicare. Clinic data (medical history, laboratory tests, etc.); Patients’ behavior insights based on purchase preferences - the data collected from portable and home medical devices; Scientific research and tests; Medical establishments’ records of the services provided: pharmacies’ reports on the drugs sold, price statistics from the healthcare market. Optimizing the operational activities is essential for bringing the established treatment practices to a whole new level. Personalized and preventive approaches based on remote monitoring can become the new reality thanks to vast volumes being analyzed. Big Data in Retail Every minute millions of people are purchasing by carrying out millions of transactions, so it’s no surprise that retail is one of the top industries leveraging Big Data. The significant tasks retail is trying to solve from both are the following: technological and entrepreneur standpoints Any retail business is looking for very explicit recommendations which steps one should take in a particular situation. Nowadays, Big Data analytics can help with that. One of the aspects of a company’s steady income depends on — is the . Price correction is one of the principal retail management mechanisms. The studies show that, on average, managers spend half of their work time on goods reevaluation, which still isn’t accurate enough due to human factors. In addition, one cannot guarantee that the process operates such crucial variables as seasonality, stock availability, supply and demand structure, competitors’ activities, etc. That is why large . smart pricing policy retail chains switch to automatized price reevaluation using Big Data technologies Process huge amounts of data;Get updates on the sales performed and the stock dynamics in the entire retail chain; React quickly to the changing situations and produce forecasts by addressing all the contributing factors (weather conditions, seasonality, holidays, distribution points, competitors, etc.); Analyze promo activities. , has implemented a similar solution, which has . What’s also important here, the new price wasn’t just somebody’s judgment call but was carefully deduced, relying on the variables mentioned above. Macy’s, which operates 800 stores with 73 trade items spared the need for pricing correction by 22 times Using the same method, . Amazon is adjusting its prices every two minutes Apart from the optimizations the technology brings to the existing businesses, it plays a big role in making strategic decisions when developing a new entity. By analyzing competitors’ locations nearby, transport access, potential customers’ income rate, their habits, and preferences, it gives a comprehensive idea of the territory’s commercial potential for future business. Big Data in Law Enforcement Historically, law-enforcement facilities have been working with huge volumes of data. There are few directions where data-based insights can be of particular value to the law-enforcement establishments. First and foremost, it’s cybersecurity. As unfortunate as it may seem, but fraudulent activities and malware have become a very often type of crime for today’s police. is said to be . Big Data algorithms can detect suspicious activities before they actually occur and alert consumers or companies about a potentially fraudulent action. It’s becoming a must for many businesses to take proper care of enterprise data security. Big Data analytical function today’s most efficient instrument for fraud identification and prevention Big Data analytics is also behind modern policing strategies. It allows the police to take a more proactive role in combating criminal activities. By using various sources of data such as the number of arrests, crime rates, fines issued in regards to a particular neighborhood, the police can monitor the areas prone to criminal activities more closely. Predictive policing — is the term used to describe this method in criminology. Lastly, on various levels. It gives the authorities unprecedented access to very different kinds of precise information from all over the world to help understand the global picture of a situation and make well-informed decisions. Economy, health, climate, social issues are just a few fields the law enforcement agencies need data science analytics for. advanced analytics Big Data offers is an efficient tool for governing establishments Summary “Information is the oil of the 21st century, and analytics is the combustion engine” — Peter Sondergaard at Gartner. It’s safe to say that data truly is the new oil, today. But a great opportunity can be a big challenge at the same time. So if you are having a hard time with structuring and organizing your business data and you feel like there is a better way to deal with it, reach out to me!
