Careful handling of the data El Dorado

In the age of digitalization, data is considered the new gold of companies. The ubiquitous networking of machines and people has created completely new possibilities for generating data and using this collected information to add value. As a basis for business decisions, these almost unmanageable data stocks are to replace pure empirical values and contribute to increasing profits. The preciousness of this treasure can be deduced from the value creation potential for organizations. But the road to exploiting the data El Dorado is long and rocky, and fraught with danger. 

Because what is precious requires particularly prudent handling. Companies are therefore faced not only with the question of what kind of data is mined, but also how this information is handled after (and in some cases already before) collection.

When data is collected, both sides of the coin must always be considered - where does the data originate and what happens to it afterwards? The vast majority of end users are aware of the value of their data and accordingly want to decide for themselves what information about their consumer behavior they want to disclose. Data protection must therefore relate to the internal handling of sensitive customer data, but also include the external factors involved in protecting this data. Not only personal customer data, but also sensitive internal company information must be protected from prying eyes and unauthorized access.

And here, driven by digitization, an almost inexhaustible reservoir of new data streams is emerging every day, with which IT departments are struggling. The desire to make these values work for companies through analytics encounters fears about the right way to handle the data. Companies are faced with the dilemma of how to process their data lakes without putting their security at risk. It is not uncommon for third-party providers to need access to the data in order to perform appropriate analyses as a basis for setting business decisions. A classification of the data stocks according to their security requirements is necessary in order to implement appropriate protective measures.