FDPIC – Expl­ana­ti­ons on Big Data

Big Data offers new oppor­tu­ni­ties for social or sci­en­ti­fic insights and a chan­ged form of value crea­ti­on for com­pa­nies. Howe­ver, Big Data can also threa­ten pri­va­cy if, for exam­p­le, the pro­ce­s­sed data has not been anony­mi­zed or has been insuf­fi­ci­ent­ly anony­mi­zed. If per­so­nal data is invol­ved, the right to pri­va­cy and the pro­tec­tion of per­so­nal data must be safe­guard­ed. The focus must be on a data pro­tec­tion-fri­end­ly design of the tech­no­lo­gy and pro­ce­s­ses of Big Data. Data pro­tec­tion must be taken into account as ear­ly as the con­cep­tu­al pha­se and data secu­ri­ty must be gua­ran­teed. In addi­ti­on, high trans­pa­ren­cy and pro­ce­du­ral requi­re­ments must be pla­ced on big data. Per­son-rela­ted Big Data is in ten­si­on with the basic prin­ci­ples of the Data Pro­tec­tion Act, name­ly pur­po­se limi­ta­ti­on and data eco­no­my. It is the­r­e­fo­re obvious that it poses major chal­lenges to cur­rent data pro­tec­tion con­cepts. This is becau­se the use of Big Data has begun, and as a result, fun­da­men­tal pro­vi­si­ons of the Data Pro­tec­tion Act (DPA) are being cal­led into que­sti­on. The­r­e­fo­re, the­re is a need for a fun­da­men­tal review of the DPA on how the core prin­ci­ples of pur­po­se limi­ta­ti­on, con­sent and trans­pa­ren­cy can be adhered to in the use of Big Data.

Source: FDPIC – Expl­ana­ti­ons on Big Data

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