What is Big Data?
Big data is a term that describes the sheer volume of data - structured and unstructured - that floods a company every day. But it's not the amount of data that matters. What matters is what organizations do with the data.
Big Data analytics is a revolution within information technology. It is useful for companies because it provides answers to many questions that some of them are unaware of, making it possible to identify customer problems.
Benefits of Big Data
Organization
Analysis for decision making
Intelligent business
Data architecture
Big Data FAQ
Improved decision making. Having a large volume of structured data that can be interpreted helps organizations to make a decision.
Big Data not only allows you to store or process a large amount of data, but also makes it easier to receive it and have that information available more quickly. It is very agile and allows you to know the status of a launch or the result of a strategy immediately. Present and future technology.
Big Data is the management and analysis of massive data at an affordable cost: a set of structured, semi-structured and unstructured data, of large volume, complex and of different types that require a series of specific and specific software applications for their processing and use.
- Search and find valuable data.
- Instant market research. - Cost reduction. - New products and services. - Anticipate trends. - Real estate value tracking.Based on the origin of the data we can make five major categorizations that are common to all analytics: web and social media data, Big Transaction Data, biometric data, human-generated data and M2M data.
The most important characteristics of Big Data can be perfectly classified in four magnitudes, better known as the four Vs of Big Data, related to volume, variety, velocity and veracity. To these four V's, we can add three more, such as Viability and Visualization. But if we talk about Vs in Big Data, we cannot overlook the main characteristic of data analysis, which is the V of Data Value. Thus, in recent articles we are beginning to talk, no longer of the traditional four Vs of Big Data, but of the 7 "Vs" of Big Data: Volume Velocity Data Variety Data veracity Feasibility Data visualization Data value