BIG DATA

It is understood by Big Data & nbsp; the treatment of huge data sets that are unviable with traditional methods of storage, access and analysis. There are several definitions of & nbsp; Big Data , but in them it is common for the following characteristics to appear:

• Volume : involves analyzing huge amounts of information, usually from tens of terabytes.
• Speed : reflects the speed at which these data are generated and changed.
• Variety : data is currently in many formats - from traditional databases to hierarchies of folders created by end users, text documents, email, measurements collected by sensors, video, audio, financial indicators recalculated continuously, etc.
• Veracity : collects the reliability and consistency of the source data.

• Structured data . Those that have length and format (for example dates) and that can be stored in tables (such as relational databases). This category includes those that are compiled in population censuses, different types of surveys, banking transaction data, purchases in online stores, etc.
• Unstructured data . They are those that lack a certain format and can not be stored in a table. They can be text type & nbsp; (those generated by forum users, & nbsp; social networks, Word documents), and those of & nbsp; non-text type (any image file, audio, video). Within this category, we can add the & nbsp; Semi-structured Data , which are those that do not belong to relational databases since they are not limited to specific fields, although they have internal organization or markers that facilitate the treatment of its elements; we would be talking about XML documents, HTML or the data stored in NoSQL databases.