Today, the use of Big Data technologies is no longer a question of whether it is necessary. The question is how to apply it effectively. You’d be amazed where Big Data analytics can be used — in church communities and election campaigns. But there are specific niches that can benefit the most from using Big Data.
Using big numbers in FinTech is becoming a vital tool for banks and other financial service providers in providing customers with better and more efficient services.
The key benefits of Big Data analysis for this niche are:
- customer segmentation;
- fraud detection;
- risk management;
- personalized services;
- compliance with legal requirements.
A New York-based startup called Kasisto applied conversational AI and Big Data to create KAI, a banking chatbot. KAI is capable of holding human-like conversations with bank customers and assisting in such issues as payments, transactions, account insights, personal finance management. As a result, it increases customer satisfaction. Such a giant as JP Morgan already uses it. Thanks to the chatbot, customers can easily surf the 1200-page bank site.
Healthcare is not just one of the most promising areas. It uses the latest Big Data technologies, and they save lives. The most common use case is an electronic health record (EHR). The medical and treatment histories of patients are stored in healthcare databases and can be used and shared over secure networks among authorized organizations.
In the US, 94% of hospitals have already adopted EHRs. As for the EU, centralized European health record system should become a reality by 2020. Also, Big Data technologies and tools allow predicting the number of patients and optimizing the schedule of medical personnel. Four Paris hospitals have successfully implemented such an experiment.
Data collection is developing through wearable devices (for example, if you have agreed to transfer data from your fitness bracelet) and prescription drug fraud prevention.
Big Data analytics is becoming critical for cybersecurity. On average, one hacker attack brings a company the $5 million loss.
And only the analysis of massive data helps you to quickly identify already known viruses and malware, concentrating on the fight against new ones. Top Big Data technologies allow studying threats, assessing risks, and predicting attacks. It is Big Data processing that allows cybersecurity experts to more effectively cope with their tasks — to detect suspicious activities. For example, they can notice anomalies in the behavior of devices, employees, and contractors, based on the analysis of a massive amount of previously obtained data. And machine learning and cloud Big Data technologies make the process even more efficient.
In insurance, the latest Big Data technologies are becoming an essential tool for effective work. First, the marketing component of the business is important. Big numbers processing allows you to segment customers, deliver personalized service, and provide optimal tariff plans. Secondly, Big Data analytics allows you to manage risks, predict indicators, identify hypotheses about customer behavior. Thirdly, it reduces the level of insurance fraud.
For instance, the Canadian company Manulife was the first in the country to use artificial intelligence to process Big Data and classify clients, which accelerated Canadians’ access to life insurance.
Retail and Wholesale
Retailers and wholesalers today are forced to use Big Data analytics technologies as this is the only way they can compete with each other, optimizing the cost of unclaimed products and stimulating sales by analyzing customer needs.
In the trade field, one can use massive data analytics in three main areas:
- customer behavior analytics;
- brand analytics;
- building a trading strategy.
American retailer Costco has set an example of how retailers can approach data collection in detail. Having received a message about fruit defects from the supplier, the Costco managers were able to text only those customers who bought this product. And Amazon’s personal pricing offers are one of the catalysts for the success of this retail giant.
Media and Entertainment
In this niche, Big Data processing is also one of the main success factors in the competition for the user. Media and entertainment platforms analyze customers’ wishes to provide them with personalized content. And the better the client data is processed, the more chances that the provider offers relevant news, music tracks, or videos.
Spotify is deservedly called the leader in this niche, which offers daily and weekly playlists based on your preferences.
Big Data Is All About Business-Friendly Solutions
Refusing Big Data analytics today is the same as continuing to use a calculator instead of a PC.
Big Data is not a goal, but a state. And in case of a rational approach and the use of the right tools, this is the means. Means of forecasting, data analysis, fast search in a large data set, intelligent data conversion algorithms, calculations.
All that you have accumulated as the system logs, artifacts in the form of some tables, invoices, other information of any kind, can be used for business-friendly purposes.
A thoughtful work with Big Data is an opportunity to benefit right now. At openGeeksLab, we know how to use the advantages of Big Data analysis to drive your business. Just drop us a line to get custom Big Data solutions.
If you have any further questions, please don’t hesitate to contact us.
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