When we speak of big data, we refer to data or combinations of data sets with a volume, complexity and speed that make it difficult to capture, manage, process or analyze them using conventional technologies and tools, such as relational databases and visualization packages. , within the time necessary for them to be useful.

If you think about the size used to determine if a data set is considered Big Data, it would not be easily defined since it continues to change over time, most analysts and professionals currently refer to a data set ranging from 30 -50 Terabytes to several Petabytes.

The nature of Big Data is mainly due to the unstructured nature of much of the data generated by modern technologies, such as weblogs, radio frequency identification (RFID), sensors embedded in devices, machinery, vehicles, Internet searches, social media like Facebook, laptops, smartphones and other mobile phones, GPS devices, and call center logs.

WHY IS BIG DATA IMPORTANT?

Big Data analysis will help organizations take advantage of their data and use it to identify new opportunities. That, in turn, helps smarter business moves, more efficient operations, higher profits, and more satisfied customers.

With the help of Big data, the information handled by companies will be reflected more clearly and easily, so that the company benefits and does not get bigger problems than it can handle and one of its objectives is to extract value of data, useful information for business decisions.

BIG DATA QUALITY CHALLENGES

The main characteristics of Big Data make your data quality face multiple challenges. These are known as 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, high-quality data from such massive, changing and complicated data sets. And that is where problems arise that companies are sometimes not specialized to handle.

HOW DOES BIG DATA WORK?

The main idea of Big data is that the more you know about something, the better you understand it and it helps you make a decision or find a solution. In many cases, this process is fully automated; It has very advanced tools that create millions of simulations to give the best possible result.

But to achieve this with the help of analytical tools, machine learning or even artificial intelligence, you have to know how Big Data works and configure everything correctly. The need to manage so much data requires a stable and well-structured infrastructure. You will need to process large volumes and different types of data quickly, and this can overload a single server or cluster. That is why you must have a well thought out system to manage Big Data.

Depending on the capacity of the system, all processes must be considered. And in the case of large companies, thousands of servers may be required. This can lead to expensive costs. You must know how Big Data works and thus companies will obtain correct and useful information.