The mountain of data available on the Internet and in companies – this fact is known as big data – is getting bigger, more confusing and difficult to process. Ever more technologically sophisticated tools and programs are intended to tame the flood of data (source Big data insider ).
The flood of data is getting bigger and bigger and presents companies with the challenge of saving, preserving and, above all, evaluating them. That’s what it says Big Data Insider magazine continue: On the one hand, he describes the increasingly rapidly growing amounts of data; On the other hand, however, it is also about new and explicitly powerful IT solutions and systems with which companies can advantageously process the flood of information.
But many readers still wonder: what is big data? Is it just having a large Excel or a large amount of paper documents? Is that big data or if not: what is big data? I would like to get to the bottom of this question in the article.

What is big data

If you enter the search term on Google, you will find the following definition of ReserachEnterpriseSoftware : Big data is a general term used to describe the large amounts of unstructured and semi-structured data that companies produce on a daily basis. This data takes a lot of time and money to load into a relational database for analysis.
That too Gabler Business Lexicon provides a definition: “Big Data” refers to large amounts of data from areas such as the Internet and mobile communications, the financial industry, energy industry, health care and transport and from sources such as intelligent agents, social media, credit and customer cards, and smart metering -Systems, assistance devices, surveillance cameras as well as aircraft and vehicles originate and which are stored, processed and evaluated with special solutions.
A great explanation can also be found at chip :

  • A large amount of data is referred to as big data if the volume is too large or too complex is to process them by hand. This is especially true for data that is constantly changing.
  • Big data can be harmless data from climate research. However, data about people are also collected: communication behavior, consumer behavior or surfing behavior of Internet users. You can see the effects of big data analysis every day on the Internet . A typical example is personalized advertising.

In conclusion, one can say that big data is initially large amounts of data that are unstructured and cannot be evaluated by hand.

Big data – pros and cons

Large amounts of data offer our society a number of new possibilities, at least if we are able to evaluate them. So I have at dice found some great examples which I would like to show.
Crimes can also be fought better on the one hand. As Dice says, it may not be quite like the movie Minority Report, which shows a society where police officers successfully arrest individuals for crimes they did not commit. But in fact, massive amounts of data are already helping regional and local authorities identify difficulties before they can become a major problem.
Furthermore, diseases can be predicted. As dice says: Predicting events based on existing data could offer individual medical care for each patient. By analyzing digitally recorded medical data and similar disease courses from patients, personal disease risk profiles can be created. Doctors could then prescribe preventative treatments or review related symptoms.
Another great example is Netflix. At dice, for example, the following can be found: For Netflix, the visualization of data is of the utmost importance in order to be able to continue its success story. Netflix can use data calculations to determine what viewers want to see and how they would like the content to be presented.
So there are numerous great examples. For more you can just click dice Continue reading. In the following, however, big data may not always be a success factor, which is why I would also like to present the downsides.
So says the magazine CIO, the criticism of big data “is probably due to the “algorithm weakness” widespread among machines, i.e. the inability to draw the right conclusions from a lot of collected information. That being said, there are two main reasons why companies do not benefit, or not enough, from big data. The first: With the help of data analysis, you will come to results that you could have had with less big data. “
The second: Big Data produces results and ideas that, for whatever reason, cannot be implemented in practice. A large US retailer had found in a model test that sales increase if you put a special offer product on the shelves a while before it is cheaper and leave it there when the offer price is no longer valid ( CIO ).
In this paragraph we have now seen some good examples of big data, but also some that may not be quite as meaningful. So, as always, it is up to us that we use big data correctly and not just do it because it is just hype.

AI, deep learning and machine learning

One potential that the mastery of large amounts of data brings with it is the ability to give machines an intelligence, i.e. artificial intelligence. A machine could evaluate the controlling report itself and initiate measures, right?
On the one hand, you can find the term artificial intelligence. So says t3n : All technologies used in connection with the provision of intelligence services that were previously reserved for humans can be found under the generic term AI.
There is also the possibility of machine learning: machine learning describes mathematical techniques that enable a system, i.e. a machine, to independently generate knowledge from experience ( t3n ). However, deep learning goes one step further: “Deep Learning” with artificial neural networks is a particularly efficient method of permanent machine learning based on statistical analysis of large amounts of data (big data) and the most important future technology within AI ( t3n ).

Conclusion: what is big data?

Big data is a lot of unstructured data that we cannot evaluate by hand. Mastering such amounts of data can lead to great potential, but it can also “backfire”. The potential of this data mastery are new methods such as artificial intelligence, which can offer an enormous market advantage. I hope to have given an insight into the topic with this article and I am looking forward to my first article on this topic myself.

LEARN MORE ABOUT: What is Big Data

If you would like to find out more about the question: What is Big Data, please contact the Round tables participate and discuss relevant topics with myself and other experts. Or write in the comments how you are dealing with this trend. Also read my article to big data.
Tip: Book suggestions too Big data

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Dr. Dominic Lindner

I blog about the influence of digitalization on our working world. For this purpose, I provide content from science in a practical way and show helpful tips from my everyday professional life. I am an executive in an SME and I wrote my doctoral thesis at the University of Erlangen-Nuremberg at the Chair of IT Management.

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