Big Data and Privacy: What Companies Need to Know to Ensure Trusted Data
In recent years, there have been many headlines about privacy breaches resulting from data leaks. It may seem like big data is a threat to data privacy. The truth, however, is that the data itself is not the issue. The problem is poorly managed data.
Proper management of data of data is essential for organizations who would like to protect both their big data and privacy.
Big data and privacy is a crucial conversation
Big data is only a privacy risk if it’s managed poorly. If an organization stops using data because of the fear that it’ll lead to security breaches, they’ll be making a big mistake. Without big data, organizations have a difficult time understanding customers and making smart, data-driven decisions.
Since data is often hosted on the cloud, rather than on a physical computer or network, a carefully planned data management strategy is crucial for ensuring that data moves around on the cloud with minimal risk.
Top 3 big data privacy risks
While big data offers a variety of benefits to organizations of all shapes and sizes, it also comes with several noteworthy privacy risks including:
- Data breaches: Data breaches occur when information is accessed without authorization. In most cases, data breaches are the result of out-of-date software, weak passwords, and targeted malware attacks. Unfortunately, they can cost an organization a damaged reputation and a great deal of money. Keeping software up-to-date, changing passwords often, and educating employees on best security practices can all help prevent data breaches.
- Data brokerage: The sale of unprotected and incorrect data is considered data brokerage. Some companies gather and sell customer profiles, which contain false information that leads to flawed algorithms. Before buying data, organizations should do their research and make sure they are receiving data from a reputable provider that offers accurate data.
- Data discrimination: Since data can consist of customer demographic information, organizations may develop algorithms that penalize individuals based on age, gender, or ethnicity. Organizations should always have a thorough and accurate representation of customers, account for biases, and put fairness above analytics.
Data privacy best practices for big data
There are certain strategies organizations can use to protect big data. Several of the best practices for maintaining the privacy of big data include:
Employ real-time monitoring
Since a privacy issue can happen at any moment, organizations should find a solution that monitors data in real-time. This way, they’ll be aware of a problem as soon as it happens and can take appropriate steps to resolve it right away.
Implement homomorphic encryption
Homomorphic encryption is a form of encryption that allows users to compute data without decrypting it first. This form of encryption should be implemented to store and process information in the cloud to prevent organizations from revealing private information to outside vendors.
Avoid collecting too much data
Only the data that is absolutely necessary should be collected. An organization may not need the Social Security numbers of their customers; customer login usernames and passwords may only be necessary. Organizations should consider deleting any personal information that is not needed to best protect customer data privacy.
Prevent internal threats
Organizations are also exposed to internal privacy risks from angry or simply uninformed employees. Therefore, it’s essential to educate all employees on best practices for ensuring data privacy like changing passwords frequently and logging off unused computers.
Big data privacy tools: What to look for
When shopping around for big data privacy tool, here are some features and capabilities organizations should look for:
- Cloud-compatible: It’s essential for a big data privacy tool to be compatible with the cloud. If it only works on a physical server or computer, it’s likely an out-of-date solution that cannot keep up with today’s big data privacy challenges.
- User-friendly design: If an organization has to spend a lot of time learning how to use a tool, it’s probably not a great fit. A tool should offer an intuitive design that various employees can use with confidence.
- Automation: Most organizations don’t have the time to manually protect their data from privacy threats. Therefore, organizations should opt for a tool that allows them to automate the process. Automation can free up companies so they can focus on running their business and meeting goals.
Getting started with big data privacy
Data breaches, data brokerage, and data discrimination can occur if big data privacy isn’t taken seriously. For this reason, data governance and integration are vital for proper compliance and privacy management. If your organization is searching for a big data privacy solution, Talend Data Fabric collects, governs, transforms, and shares data with internal stakeholders while ensuring data privacy. Try Talend Data Fabric today to reduce the risk of privacy issues often associated with big data and ensure your company has data it can trust.
Ready to get started with Talend?
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