The Importance of Data Privacy and Security in the Age of Big Data

What is Data Privacy and Security?

What is Data Privacy and Security

Data privacy refers to the way businesses collect, store, process and share data of the customers. Data Privacy provides individuals control over their data before the data is collected, and processed. It also refers to the ethical, responsible, and transparent use of data by organizations.

If organizations are data-privacy compliant, then the organizations take consent from the individuals before collecting the data, inform them about the purpose of data collection, and also provide the authority to withdraw their consent at any time through the opt-out mechanism.

On the other hand, data security refers to the ways to secure data using different methods, technologies, and protocols. Implementing data security measures protects the data from breaches, cyber-attacks, unauthorized access, and other threats.

Some of the ways to achieve data security include encryption, access controls, firewalls, vulnerability management, incident response plans, and regular security assessments.

What is Big Data? 

What is Big Data

Big data is huge and complex data that is collected continuously and rapidly from various resources and cannot be accessed with the help of traditional technologies.

Big data and big data analytics are usually defined by 3 major characteristics and the 3 Vs of big data analytics are:

  • Volume: 

In big data, volume refers to a huge amount of data collected from various resources. Big data is collected from social media interactions, e-commerce transactions, IoT devices, data from particular platforms, etc.

For instance, Instagram handles massive amounts of data in the form of images, and videos. Twitter handles the data in the form of tweets and approximately collects 12 terabytes of data every 24 hours.

  • Velocity

Velocity refers to the speed at which big data is collected, generated, and processed. Big data is collected at unprecedented rates with high amounts of data and requires real-time or near real-time time processing.

Comparatively traditional way of collecting and processing data is slow and does not match the speed of big data technologies in rapid ingestion and analysis of the data.

  • Variety

The big data is collected in a variety of formats and resources. Big data is collected in the form of structured, unstructured, and semi-structured formats from companies whose core of the business is data.

Big data encompasses data from various sources and formats like social media posts, images, videos, tweets, e-commerce purchases and transactions, emails, messages, sensor readings, and more.

Importance of Data Privacy and Security in the Age of Big Data

Importance of Data Privacy and Security

As we read above, all of the data is being collected and processed at greater speed and it is important to secure data. Below are some of the facts that justify the importance of data privacy and security.

  1. Vast Data Collection Process

The main characteristic of big data is that it collects vast amounts of data that includes everything from transactions to financial records, health information, and more. So it is crucial to implement data privacy policies that safeguard data from unauthorized access or misuse of the data.

  1. Risk of Data Breaches and Unethical Practices

A data breach is where cyber criminals access confidential information through unethical practices and unauthorized access. Data breaching affects companies through supply chain disruption and loss of information resulting in loss of trust from their customers, financial crisis, etc. Hence, it is crucial for organizations to secure and protect their data.

  1. Legal and Regulatory Compliance

If organizations do not implement data privacy policies like GDPR (and other privacy laws depending upon the region, and countries), it results in misuse of the collected data. If in case, data privacy policies are not secured by the companies, and data gets theft, then organizations have to pay huge penalties and face blacklisting.

  1. Infringes Privacy and Erodes Public Trust

Every business process of small to giant companies relies on data. High-profile data violations and misuse of data without proper and informed consent can damage an organization’s reputation and erode public trust.

If businesses need to gain the trust of customers and aim to sustain for the long term, it is important to maintain a positive public image and maintain transparency in the processing of data by saving the customer’s data from unauthorized access.

  1. Lack of Control Over Data 

As discussed above, big data is collected from various resources and in various formats. There is no control over how the data is processed and it is leveraged for multiple purposes.

If businesses do not protect their data from unethical data collection, and data breaching, individual lose control over their data, and questions accountability and transparency in data handling.

Best Practices to Protect and Safeguard Data in the Age of Big Data 

  1. Data Encryption 

Use data encryption to secure confidential data. Data encryption is one of the preferred ways to secure data when at rest and during transit. Implement end-to-end encryption and strong algorithms, so that even if the data is intercepted in-between, it remains unreadable without the authentic decryption keys.

  1. Using Access Controls

Leverage role-based access controls (RCP) so that only authorized persons can get access to sensitive data. Implement least-privilege principles to limit access to what is necessary for each user’s role.

  1. Avoiding Over-collection of Data 

Follow the process of data minimization and collect the data that is necessary for certain business purposes and avoid over-collection of sensitive data. Implement data retention policies and frequently delete the data that no longer is needed.

By minimizing the amount of sensitive data, you can reduce the potential impact of data breaches.

  1. Conduct Frequent Vulnerability Assessments 

Keep your systems and databases updated and invest in frequent vulnerability assessments, regularly review audit logs, and monitor data access and activities using security information and event management systems (SIEM).

  1. Implement Strong Incident Response Plans (IRP)

Use strong incident response plans that clearly define the roles and responsibilities of every individual during the incident response. Develop a comprehensive IRP that addresses all kinds of data malpractices.


Implementing strong Data privacy and security measures in the age of big data is the most essential and crucial component for businesses to protect individual data, avoid unethical practices, build trust and transparency, and uphold ethical standards.

Additional Read:  4 Ways to Make Big Data a Part of Your Marketing Strategy

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