Big Data

The term Big Data is a general term used to describe large amounts of unstructured and semi-structured data. Companies from the Internet, communications, the financial industry, energy industry, healthcare, and transport produce daily.

The English term Big Data means a large amount of data, which is from the areas such as the Internet and mobile communications, the financial industry, energy industry, health care, and transport, and sources of intelligent agents, social media, credit, and customer cards, Smart metering systems, assistance devices, surveillance cameras, as well as aircraft and vehicles. With specific solutions, these data volumes are processed, evaluated, and stored.

Big Data Goals

One of the most important goals of big data is the discovery and analysis of reproducible business patterns. It is generally accepted that unstructured data in text files make up at least 80 percent of corporate data. If these remain unprocessed, the whole amount of unstructured data that a company produces daily alone means a considerable cost factor for storage capacities. Unprocessed data can also be a reason for liability if information cannot be found in the event of a compliance check or legal action.

Big data is also being used with cloud computing connected since real-time analysis involves a large amount of data. A framework is required, as is possible with MapReduce and Hadoop, for example. These programs focus on a large amount of data distribution.

The Importance Of Big Data In Business And Science

The economy hopes that Big Data will provide new insights into prospects and customers, their risk potential, and their buying behavior, and generate user-based profiles, behind which phenomena such as small data can also appear. It tries to optimize and flexible production for Industry 4.0, innovations, and preliminary calculations to create a more effective positioning on the market.

In this way, science examines climate change, the occurrence of earthquakes and epidemics, as well as (mass) phenomena such as shit storms, population movements, and traffic jams. With the help of computers, extensive data analysis examines both atomic bombs and meteorite flights and impacts. The authorities and secret services find discrepancies and anomalies in the vast amount of data to track down criminals and terrorists more quickly and create similarities, groupings, and delimitations with them.

The Criticism And The Outlook On Big Data

The constant accumulation of data is often criticized in public and represents a challenge for data protection and personal rights. Often those affected do not agree with the use of the data collected and cannot identify them and control them.

The connection of non-problematic information can also lead to problematic findings. One immediately belongs to a circle of suspects, and the statistics appear to be unworthy of credit and risky. The reasons here are that the place of residence is in the wrong part of the city, specific means of transport are used, and certain books are read.

Information ethics, for example, raises questions about the moral implications of big data concerning digital paternalism and big data, which can also be derived from Orson Wells’ term “Big Brother” in “1984”. So nowadays, business ethics and legal ethics are necessary to prevent excesses with the help of data protection laws and institutions and ensure the protection of consumers protection.


Big data analyzes are also used in road traffic, for example, and are an advantage for avoiding traffic jams. The networking of cars and roads will be tackled with the help of big data analytics. The respective sensors monitor traffic volume, and the traffic jam detectors react to this in real-time. Alternative routes are created and sent directly to a navigation device.



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