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What is Big Data?
Big Data is a relatively new concept in the business world. Through its translation we can deduce that this great concept "Big Data" is nothing more than a set of tools and technologies whose function is to allow us to work with a massive amount of data.
If we do a search on the internet to define it in a formal context, we will obtain a wide variety of results. That is why I am going to mention one of the first definitions that helps to understand this great term formulated by Gartner (a consulting and research company of information technologies based in Stamford, Connecticut, United States) in 2001 and is still used today as a reference in the explanation and understanding of Big Data "Big Data is data that contains a greater variety and that is presented in increasing volumes and at a higher speed".
One of the big questions we can ask ourselves is why did the development of big data begin; but the answer is very simple today in the 21st century. It emerged to respond to a reality that did not exist before: how to collect, store and process large amounts of messy data that are generated at very high speed, not forgetting that they are in continuous growth.
The 5 Vs of Big Data
As we have already mentioned, Gartner's definition tells us about the essential characteristics that differentiate the different Big Data environments: Volume, Velocity and Variety; so well known as the 3 Vs of Big Data.
As we know, the world in which we live is in constant evolution at a business and technological level... that is why the Gartner definition (and the vast majority of them) has remained a little incomplete and the technology community has decided to add two very important characteristics that we can not fail to take into account: Veracity and value.
VOLUME: As we have explained above, when we talk about big data we always refer to large amounts of data in a massive way, so we can say that volume is the main characteristic most associated with this great term.
VELOCITY: This set of data has a very short life cycle, which means that there must be a high response and processing velocity to prevent this data from becoming outdated or obsolete. The key to this process is to generate a rapid response for greater optimisation and profitability.
VARIETY: In most cases we work with structured data, such as data stored in database systems. We can also find unstructured data, such as text documents, e-mails, images, audios, etc... Although in general the wide majority of data that is generated is not structured, which makes it very difficult to extract information from it and at a management level.
VERACITY: Due to the large volumes of data from multiple and diverse sources that are received at very high speed, we must question the veracity of the data we receive. This is a great challenge for organisations and companies as it is essential to ensure that this information is truthful and correct. This is due to the fact that it is very common to receive erroneous, incorrect and incomplete data, which, depending on the data, can cause great damage when it comes to analysing it.
Therefore, we must carry out an exhaustive cleaning to determine which data should be eliminated and which should not.
VALUE: Value includes the rest of the four characteristics, so we could say that it is the most important factor of Big Data. Once we have processed and converted the data into information, if it does not offer value for the company, the whole process will have been of no use, as we will have achieved nothing. We cannot forget that the fundamental objective of Big Data is to provide value to the organisation, generating information that helps to optimise decision-making within the company, improve internal management and the implementation of new strategies to optimise and obtain the greatest profitability for our business, organisation, etc.
Within the area of the company, this massive collection of data and consequently the extraction of trends provided by the data, allow companies to move faster and more efficiently. In addition, it allows the company to deal with various problems or events such as the elimination of the most problematic areas that could damage the reputation of the company itself.
One of the main benefits of data analytics within organisations is that it helps companies to get more value from their data and use it to identify new opportunities. In turn, it drives smarter business models that include more efficient operations, generate higher profits and as a result have a positive impact on our customers.
Big Data generates numerous advantages for companies and organisations, because data becomes their best partner when it comes to meeting the needs of our customers when it comes to offering a service or product.
Another of its main benefits that it provides us with, is the increase in sales: by extracting key information from our customers that help us to make a series of marketing decisions that more accurately meet their desires and needs.
To conclude the issue discussed: Big Data and the business world, I attach the link to a news item "The Amazing Ways Coca Cola Uses Artificial Intelligence and Big Data to Drive Success'' for a better understanding of this great concept and what better way to understand it than based on a real example of Big data in which machine learning, data mining, artificial intelligence ... through specific software such as Hadoop or Apache is used.
BIG DATA REAL EXAMPLE; ”The Amazing Ways Coca Cola Uses Artificial Intelligence and Big Data to Drive Success''
References:
https://www.powerdata.es/big-data
Comentarios
Nowadays it is said that data is liquid gold, so it must be treated in the right way. Therefore, as the text says, value is the most important factor. We must have extracted information with sufficient value to be useful for the company, otherwise all the work done will have been for nothing.
This tool seems very interesting to me, especially for marketing experts, since Big Data can be used perfectly to plan future campaigns on social networks and in this way, know about your potential customers and get closer to them. This will make it easier to show only those ads that are of interest to consumers, making them a non-intrusive experience.
The essential characteristics that show the different Big Data environments help to comprehend this term in greater depth, which for many is difficult to understand.