Big data analyzes usually require a large amount of data in order to capture and collect all information in its raw state. This data storage resembles a real sea in size, which is why the technical term “data lake” has been established for it. You can find out exactly what this is all about in this article.


As a large data store, the data lake manages the entire mass of data in its original form, i.e. in its raw format. He makes use of the collection of information from a wide variety of sources. It makes no difference to the data lake whether the data has a structure or not. This large data store also does not require any prior validation or reformatting of the data. However, a data lake cannot manage number or text-based data. In addition, it can also save information from the media area, such as images and videos.

What appears to be a chaotic collection of data, however, follows a system. Because even if the data lake receives all information in its individual raw states, it structures it as soon as the data is required. Then, if necessary, he also initiates a restructuring of the data.

Use of a data lake

The many different ways of using and applying the information collected by a data lake, such as flexible analyzes, make the large data store extremely attractive. However, the application requires some requirements in order to be able to use the system optimally.

The most important basic function of the data lake is primarily to be able to collect and manage data from a wide variety of sources. By grouping all data in one place, data silos can be avoided and information is available more quickly. However, given the large amount of data, even a single storage space does not guarantee problem-free data management. Therefore, data lakes require common frameworks as well as the creation of protocols of the contained databases in order to bring more structure into the mass of information.

In the course of security and data protection requirements, additional access controls must be implemented and information encryption must be ensured. At the same time, data lakes should always enable a function of backing up and restoring data.

Advantages and disadvantages

The use of a data lake is particularly useful when large amounts of data are repeatedly generated that have to be managed. At the same time, however, such a large collection of information can also pose a number of hurdles.


  • fast and uncomplicated data storage in raw format
  • low requirements with regard to the required computing power
  • provides the basis for detailed and content-rich analyzes
  • many possibilities for the evaluation of data, since all data is collected without prior sorting
  • Big data analytics can be a competitive advantage


  • High requirements in terms of data protection and security
  • Need for a complex data protection system
  • Requirement of prior implementation of access rights and regular user controls


As you can see, a data lake is a real asset, especially for companies with large volumes. This is because, when used optimally, real competitive advantages can be achieved thanks to in-depth Big Data analyzes. At the same time, however, sufficient data protection must be ensured with regard to the amount of data. However, this sometimes makes the use of a data lake very complex.

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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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