Business

Introduction to Big Data and what it stands for?

Introduction to big data

Big Data Stands for the flow of large data. We are talking about structured and no structured data at the same time. Of course, once we deal with big data, we talk about the big volume of data as well as the type of organization such data too. In fact, it is so simple, the ultimate goal of the discipline is to help to make more accurate decisions and to start business and tactics.

Who says big data, says a large amount of data, fast flow, and the coming type if the data.Actually, the traditional processing of the data is difficult and simpler to handle for sure. The process may need many complicated techniques to make it happen. The Big Data discipline gained its legacy due to the analyst Doug Laney for sure. He was able to trigger the definition of the big based on three main pillars which we are going to talk deeply in the next lines.

Volume:

Actually, firms around the world have multiple types of sources when it comes to data. To make the picture clear for you, you can extract data from databases from different companies. You can get them from a word document, excels, no structured data, and many other types of data sources. This is where big data tools come to place. We will deal with them later in our work. The volume point is covered by the Hadoop and cloud storage steady facilities nowadays.

Main Pillars of Big Data:

Velocity:

It stands for the speed of the data which the target database will receive. We can even talk about a giant data center that gathers bigger databases on multiple servers. However, the velocity is handled in a magic timely way. You can get the sensors, smart meters, and all the torrents of the data that comes and go.

Variety:

The variety stands for all types and the formats which the database receives. You can get numeric data, documents, audio, emails, tickers, and any other type of data from the different resources around the globe.

Why Is Big Data crucial nowadays?

If you want to touch the real importance of big data then just imagine the scale of the amount of data that we are dealing with for sure. The big data can make you optimize the cost reduction, the time, and the new product calling too. This can automatically alter great decision making for sure.

The two additional dimensions when it comes to big data:

Veracity:

It refers to the high quality of data that comes from different resources too. It has a hard process to link, transform, or even match the standards within your data.

Variability:

The flow of data is different than any other type of data storage. Business needs to know when something is entering the flow or not. This in addition to how we can manage it and store it in the right way to be retrieved at zero time. Actually, a business that uses big data is much sophisticated, they need accurate data in a very short time of perception.

ELT: Data Integration process as an Introduction to Big Data

This is where we talk about data integration. In another word, we talk about ETL. The acronym stands for Extract, Transform and Load. The three pillars area real must make any big data process come to life. To make the system clear, the data need to be extracted from different types of database resources, then transform it into structured data then load it into targeted data.

Seek the most accurate analytics to boost any kind of business today

Now, decision-makers try to seek the most accurate des ion in the entire world. This is no matter what kind of type business in the world. Big data can handle the best analytics to handle people the best decision making without any small doubt.

In the end, we can confirm that big data and business intelligence are the most need disciplines nowadays. Social media gurus, bank stores, and anything you have in mind is using them in order to rock the world of business and money in our age.

Also Read :

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Rajhu S Goraai

Rajhu S Goraai is a Passionate Stock and Commodity Researcher. Travel addict and Photographer. Co-founder and Editor of Leading Business & Tech Magazines.

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