Big data has become a keen topic of the three major reasons

Undoubtedly, the management of big data is now a hot topic in the enterprise development community. But why the discussion of big data has become a popular phenomenon will appear so late? Why has big data processing been not part of an enterprise toolset for so long? Does this mean that today's information technology ecosystem makes big data solutions as smart as they are today?

One of the key reasons why big data management is so hot nowadays is that most organizations have to manage the growing volume of data that they handle. From Internet search engines to searches with a huge amount of information to research projects in the genetics or atmospheric sciences, the amount of data that people are interested in and trying to make is getting bigger and bigger. The once-megabyte data was already astonishingly expected, but it was too pale compared to the terabytes it now organizes.

Processing power is the key. On the one hand it has the ability to store huge amounts of data; on the other hand it has to be able to handle it. After all, if it can not be tapped, what is the data used to store it? When it comes to data mining, we speak about processing data faster than mining. If we can not find meaningful information from the data in a reasonable amount of time, then it is useless.

Nowadays, managing big data is very viable because of the affordable processing power. In the past, Fortune 500 companies needed to dilute their shares and issue more common stock, in order to be able to buy multivariate processors, which would be able to store terabytes of data. But now a primary school student, with his pocket money you can buy a processor with equivalent processing power.

Plus, there really is not the same demand as it used to be, going out and buying big hardware and impressive workstations from companies like Oracle and IBM. And a smart IT department can easily buy hundreds of motherboards and multi-core processors from the Web and ship it directly from Taiwan at the lowest prices in the history. Diversion Open source software can be used to group a wide variety of motherboards and processors, while domestic processing power can swallow unstructured data in gigabytes.

With the processing power, free software also has the ability to strengthen the big data movement. Tools such as HBase can store big data in a single database table, or in massive database tables, which can scale billions of rows and millions of columns. From there, if you are interested in mining your HBase data, Hadoop can help you deal with those massive datasets and understand their accumulated information.

"If you want something special you can access and you have access to HBase data; but if you want to get some data on analytics, say you want to find the average age of a planet in billions of records , Then you can use Hadoop, "says James Gosling, the father of Java. "It will eventually be very fast and very efficient."

The large pool of data, the affordability of processing power, and the availability of specialized software not only make Big Data a keen topic on the Internet, but also become a viable way to manage information. Combining cheap processing power with free downloads, enterprise architects have newer and more efficient tools to handle big data with open source software solutions like Hadoop and HBase. As more and more companies gather more information from a different set of accesses, the big data processing capabilities hit an unprecedented peak.