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Security and Privacy in The Era of Big Data and Data Integration


security in big data
Image source: Flickr | Security and Privacy in The Era of Big Data and Data Integration

Big Data is the term we use to designate data that, due to its large volume, high complexity, and high frequency, cannot be processed using traditional methods. To carry out this task, specialized software and computing algorithms are used, capable of filtering and extracting useful insights even when faced with a huge amount of information.


The advancement of Big Data in recent years is no surprise. After all, thanks to it it is possible to make assertive decisions and solve problems that, until then, seemed insoluble. And the pace should continue at an accelerated pace: according to an estimate by Fortune Business Insights, Big Data should present an annual growth rate of almost 15% until 2028 and generate, in 2028 alone, US$549.7 billion.


A number of factors have driven this growth, such as the development and democratization of technology, the accessibility of cloud computing, artificial intelligence, machine learning, and the Internet of Things, as well as concerns about security and privacy – reflecting the new way in which we handle and perceive data. Along with this, we also noticed a huge demand for data integration.


And why is data integration so important? Because, combined with Big Data, it allows a holistic view of the business, operational efficiency, quick response to changes, improvement in the quality of information, cost reduction, and, finally, preparation for the much talked about digital transformation.



One Caveat: Security


Data integration, although extremely valuable, requires care, especially about information security. It becomes even more important since data from different sources ends up being centralized in a common infrastructure – in order to process, filter, and analyze it.


Security, well thought out and well implemented, must take three pillars into account:


Confidentiality: This pillar refers to the protection of sensitive information against unauthorized access. Ensuring confidentiality means ensuring that only authorized people have access to critical data. Measures such as encryption, access control, and clear policies contribute to keeping confidentiality intact.


Integrity: Integrity is about ensuring that information is not altered, corrupted, or compromised in an unauthorized manner. Maintaining data integrity is essential to preserving its accuracy and reliability. Techniques such as digital signatures, version control, and checksums are essential.


Availability: The pillar of availability involves ensuring that information and systems are accessible when needed, without undue interruptions. This includes preventing and mitigating attacks that seek to make services unavailable, as well as implementing backup and disaster recovery practices to maintain continuity of operations.


As can be seen, even though data integration enables a holistic view and extraction of indicators for decision-making, there must be a segregation of roles and functions so that only authorized and competent managers access or share the information that is entrusted to them.


To guarantee confidentiality, it is also necessary to implement secure authentication mechanisms, such as the adoption of Multiple Factor Authentication (MFA) and the use of strong passwords, and ensure that the base allows encryption of data at rest and that, in transit, they use secure protocols, such as TLS 1.2.


Finally, it is necessary to invest in infrastructure so that it can support the large volume of data expected, including failure recovery and redundancy mechanisms. I'm not just referring to hardware, as the use of the cloud is, today, an almost inevitable aspect. It needs to be well protected, with up-to-date security protocols, and must adhere to international information security, data privacy, and business continuity standards, such as ISO 27001, ISO 27701, and ISO 22301, respectively.


In summary


Big Data, more than a trend, is a reality. When associated with data integration, it enables faster and more accurate business decisions and favors cost reduction and operational improvement. Good implementation, however, requires respect for the three pillars of security and privacy – confidentiality, integrity, and availability – in order to guarantee the protection of data from suppliers, customers, partners, and the organization itself.

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