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A Quick Overview of the Technology Behind Big Data

The information technologies have led to the development of Big Data and helped it grow at a large scale. Big data offers a number of promising benefits in your company. Likewise, it allows you to understand some of the processes and elements that are driving the new digital revolution. You must understand that data is everywhere and it is growing a rapid pace. There are about 2.5 zettabytes of data in existence. Moreover, it is growing at an accelerated rate.

All this amount of information requires cutting-edge technology to make it useful for your organization. Images, videos and even your finances can be used to make better decisions with the use of big data. In addition, you can extract ideas from this data to improve your company’s productivity and profitability. Therefore, processes that use Big Data to obtain useful information require certain technologies to achieve success.

Role of New Information Technologies in Database Models

New breakthroughs in information technologies help programming languages query data. Moreover, they are easy to use. Likewise, they provide simple processing that other hierarchy or network-based models cannot offer. The storage model is simple; data is stored in rows and columns, which in turn are stored in tables.

You can take advantage of non-relational databases or NoSQL to make the most of big data. These new platforms allow to manage databases under another paradigm different from SQL databases. NoSQL databases do not need a grouping of fixed columns. They also do not require joins and allow horizontal scaling. That is, this type of scaling allows data to be distributed across multiple servers.

One of the advantages of this new paradigm is its enormous scalability, which allows parallel execution of systems. In addition, it allows a better distribution of data on a greater number of nodes.

Dedicated servers for Big Data


These type of servers must handle a massive amount of data. You can get an idea of the massive amounts that they can handle when you see that they are measured in, terabytes, petabytes and many more. As for the new paradigm of information technologies dedicated to Big Data, a server cannot be expected to store such an immense amount of data and information.

Since the need to store large amounts of data and also to process it at high speed is so important, direct storage of Big Data must be taken into account. How can this be achieved? To begin with, the units that are destined to store the information must be solid state drives (SSD) and also DAS. What is DAS? They are direct storage units or Data Attached Storage, for its acronym in English.

Better Big Data processing


The techniques used to process Big Data have to analyze terabytes and petabytes (so far) of data. This translates into an almost infinite amount. Therefore, if we talk about information technologies, batch processing of offline data should be on a large scale and at full power.

Likewise, real-time stream processing is done on the most recent data. This is to obtain a more specific profile. This type of processing is also used to find outliers, to detect fraudulent transactions and for security monitoring.

However, the problem of doing these processes in a fast or low-latency way for a complete Big Data cluster remains latent. This means that advanced systems must process terabytes and, in some cases petabytes in a matter of seconds. When this level of processing is achieved, it is when there are the most parallel executions.

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