Big Data consists of a process that analyzes and interprets large volumes of data, both structured and unstructured. Big Data is used so that data stored remotely can be used by companies as a basis for their decision making.

We can use applications that use Big Data in basically any sector, since data analysis, especially with the arrival of the IoT (Internet of Things), can provide very valuable information, both in the private and public spheres.

When we talk about Big Data we refer to combinations of data sets whose size (volume), complexity (variability) and growth rate (speed) make it difficult to capture, manage, process or analyze them using conventional technologies and tools, such as databases. conventional relational and statistical or visualization packages, within the time needed to make them useful.

We’ve mentioned loT before; The complex form of Big Data is mainly due to the unstructured nature of much of the data generated by modern technologies, such as web logs, radio frequency identification (RFID), sensors embedded in devices, machinery, etc. vehicles, Internet searches, social media, laptops, smartphones and other mobile phones, GPS devices, and call center records.

It is understood? Almost better we are going to put examples of the application of Big Data in different sectors to better explain this concept:

• Tourism: Keeping customers happy is key to the tourism industry, but customer satisfaction can be difficult to measure, especially at the right time. Resorts and casinos, for example, only have a slim chance of turning around a bad customer experience. Big data analytics gives these companies the ability to collect customer data, apply analytics, and immediately identify potential issues before it’s too late.
• Health care: Big Data appears in large quantities in the health industry. Patient records, health plans, insurance information and other types of information can be difficult to manage, but they are full of key information once the analytics are applied. That’s why data analytics technology is so important to healthcare. By analyzing large amounts of information, both structured and unstructured, quickly, diagnoses or treatment options can be provided almost immediately.
• Administration: The administration is faced with a great challenge, maintaining quality and productivity with tight budgets. This is particularly problematic when it comes to justice. The technology streamlines operations while giving management a more holistic view of business.
• Retail: Customer service has evolved in recent years as savvy shoppers expect retailers to understand exactly what they need, when they need it. Big Data helps retailers meet those demands. Armed with endless amounts of data from customer loyalty programs, shopping habits, and other sources, retailers not only have a deep understanding of their customers, but are also able to predict trends, recommend new products, and increase profitability.
• Manufacturing companies: These deploy sensors in their products to receive telemetry data. Sometimes this is used to offer communications, security and navigation services. This telemetry also reveals usage patterns, failure rates, and other product improvement opportunities that can reduce development and assembly costs.
• Advertising: The proliferation of smartphones and other GPS devices offers advertisers the opportunity to target consumers when they are near a store, cafe or restaurant. This opens up new revenue for service providers and offers many companies the opportunity to acquire new prospects.
• Other examples of the effective use of Big Data exist in the following areas:
  • Use of IT log records to improve problem resolution, as well as the detection of security violations, speed, efficiency and prevention of future events.
  • Use of the voluminous historical information of a Call Center quickly, in order to improve the interaction with the client and increase their satisfaction.
  • Use of social media content to improve and more quickly understand customer sentiment and improve products, services and customer interaction.
  • Detection and prevention of fraud in any industry that processes financial transactions online, such as shopping, banking, investing, insurance, and healthcare.
  • Use of financial market transaction information to more quickly assess risk and take corrective action.

The special characteristics of Big Data make its data quality face multiple challenges. These are known as the 5 Vs: Volume, Speed, Variety, Veracity and Value, which define the problem of Big Data.

These 5 characteristics of Big Data cause companies to have problems extracting real and high-quality data from such massive, changing and complicated data sets.

What’s your opinion about it, can you think of other ways of using Big Data?