Are social media platforms really free to use

What just happened?

More and more people are becoming aware that if they aren't being sold something, their data is the product. When you use services like Facebook for free, you may think, "what is the cost?". The answer is Big Data.

What does this mean?

Big Data is the term used for extremely large datasets that seem unmanageable. It can be subdivided into three categories: Structured, Unstructured and Semi-Structured data sets which are all different in their own way but all big when it comes to volume.

In Big Data, there is something called predictive analytics is a method for obtaining a forecast from historical data. It is used to provide insights into future trends and proactively identify opportunities for better decision making. In contrast, descriptive analytics provides an analysis of what has already happened.

Big data can be used to understand trends and patterns in customer behaviour. This information can be aggregated over vast numbers of customers, which helps businesses make better decisions about their products and services. Data mining makes it possible to uncover hidden relationships among large datasets by analysing patterns in the information or uncovering new correlations that were not previously noticed.

The EPIC highlighted the data security risks and significant student privacy risks that exist in the current regulatory environment for big data and asked the administration to implement the Good Information Practices (FIP) first established in 1973. In response to suggestions from EPIC and other consumer privacy groups, the Science and Technology Policy Office published a request for information that allows the public to comment on the Podesta Big Data Review. (1)

What makes the idea of data ownership so complicated in terms of an organization's right to collect and use consumer data gathered for. Big Data analytics purposes are that currently, no jurisdiction has comprehensive legal principles regarding individual data. Data ownership depends on the nature of the data, how it was generated and collected, where the data came from (state, international law) and whether it pertains to a person or machine or something else. (2)

How does this impact the legal sector?

In any case, as the legal framework of big data evolves, the ability of organizations to obtain and analyze personal information without explicitly asking permission and determining how such data may be used or sold will be seriously questioned. Increasingly, diverse rights to protection and access to information will be discussed in both the public forum and in conference rooms. (3)

However, the emergence of big data presents some challenges for these privacy principles, particularly as it is becoming easier to re-identify personal information from anonymous datasets and predictive models. Many privacy concepts rely on informed consent for the disclosure and use of personal information. For example, the processing of non-sensitive personal data can result in the generation of data that discloses sensitive information about an individual. (4)

Based on the privacy legal framework, taking into account big data and examples from different parts of the world, we can identify a number of potential controls for the confidential processing of big data. In practice, this requires organizations to consider privacy and data protection issues at the design stage and throughout the life cycle of any system, service, product or process. Problem-solving includes ensuring that all Big Data activities are carried out within a complex and often misunderstood legal framework that regulates the privacy and security of health information. (5)

While most of the data collection and storage solutions have become plentiful and affordable, they allow users across all industries to control the size, speed and complexity of big data. Although its full potential in the health sector has not been realized due to financing, interoperability and legal issues relating to privacy and information security. Understanding this structure and the different uses of information will enable the outpatient care managers to focus on maximizing the potential big data has to improve healthcare delivery while avoiding common misconceptions associated with complex health privacy and health information security concepts. (6)

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¹https://epic.org/privacy/big-data/ and https://www.techrepublic.com/article/big-data-six-critical-areas-of-legal-risk/

²https://www.yellowfinbi.com/blog/2014/07/yfcommunitynews-do-you-have-any-rights-in-the-age-of-big-data-analytics-168013 and https://www.techrepublic.com/article/big-data-six-critical-areas-of-legal-risk/

³https://journals.lww.com/ambulatorycaremanagement/Fulltext/2015/01000/Big_Data_and_Ambulatory_Care__Breaking_Down_Legal.7.aspx and https://www.yellowfinbi.com/blog/2014/07/yfcommunitynews-do-you-have-any-rights-in-the-age-of-big-data-analytics-168013

⁴https://epic.org/privacy/big-data/, https://www.twobirds.com/en/news/articles/2019/global/big-data-and-issues-and-opportunities-privacy-and-data-protection and https://www.compact.nl/en/articles/big-data-analytics-privacy-how-to-resolve-this-paradox/.

⁵https://journals.lww.com/ambulatorycaremanagement/Fulltext/2015/01000/Big_Data_and_Ambulatory_Care__Breaking_Down_Legal.7.aspx, https://www.twobirds.com/en/news/articles/2019/global/big-data-and-issues-and-opportunities-privacy-and-data-protection and https://www.compact.nl/en/articles/big-data-analytics-privacy-how-to-resolve-this-paradox/

⁶https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4315864/ and https://journals.lww.com/ambulatorycaremanagement/Fulltext/2015/01000/Big_Data_and_Ambulatory_Care__Breaking_Down_Legal.7.aspx