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8 Best Practices of Data Privacy for your Business

Chandan Gaur | 02 April 2023

Eight Best Practices of Data Privacy for your Business

What is Data Privacy?

Data privacy is the discipline of protecting data from illegitimate access, theft, or loss. Applying dependable data security rules enhances an organization's credibility and inspires trust. 

Even if we aren't conversant with the technical specifics, we are all aware of the necessity for security as technology users. We experience various levels of security in the actual world. For example, a building's first-floor windows may have bars, but the second and third floors may not. While an adversary might still break in, it would take a lot more effort, such as using a ladder or something similar; hence the probability or likelihood would be substantially lowered.

[Related Topic: Complete guide to Data Privacy]

Our digital devices are somewhat secure but will never be completely secure. An adversary will be able to break in if they have enough resources, so we need to increase the bar so that it takes a lot of effort. 

Data Privacy vs. Data quality vs. Data Governance

Data Privacy

Without a doubt, a company's most valuable asset is its data. We live in a data economy where companies place a premium on obtaining, sharing, and analyzing data on their customers and users. Transparency in how businesses gain consent to store personal data, follow their privacy policies, and manage the data they've collected is crucial in building trust with customers who see privacy as a fundamental human right. 

Customers are less inclined to trust you in using your products or services if they can't trust you with their personal information. Data management for regulatory compliance is, without a doubt, far more critical. Non-compliance with legislation such as the GDPR or the CCPA could result in hefty fines. A corporation may be forced to meet legal responsibilities for collecting, keeping, and processing personal data. If the organization is hacked or ransomware is employed, the consequences of lost revenue and customer trust are severe. 

Data Quality

Data quality is a metric that determines how well a data set fits an organization's needs. For reliable judgments, high-quality data is essential. Data quality can be expressed in terms of these measures : 

    • Accuracy: Data must, without a doubt, be accurate to be beneficial.
    • Completeness: A data set with too many loopholes won't be able to provide answers.
    • Timeliness: Data that isn't up to date isn't going to be helpful for a company.
    • Accessibility: If data will be used, it needs to be accessible reasonably. 

Data Governance 

Data governance is a system of processes, responsibilities, policies, standards, and metrics that ensures data is used effectively and efficiently to help an organization achieve its goals. It establishes the methods and responsibilities for assuring the quality and security of data used by a business or organization. Data governance determines who can make decisions based on what data, under what conditions, and using what methods.

Data privacy has become a crucial aspect for companies and customers as well.Click to get A complete guide to Data Privacy

Eight Best Practices for achieving Data Privacy 

Here is the list of the top eight best data privacy practices to ensure your enterprise achieves increased trust and credibility.

  • Collect data as per need
  • Categorize your data
  • Use a proper endpoint security system
  • Protect data from internal attacks as well
  • Beware of phishing attempts
  • Use encryption algorithm and tool
  • PII Data Detection and Protection using data catalog and Data Governance
  • Read and Write protected APIs and protect the data platform from third-party or cross-site access.

Collect data as per need

Data is extensively found everywhere, so it is the best practice to collect the data as per requirement and store it in a better place like a data lake. We don't store every data in the data lake; the data stored in the data lake should be well categorized and organized; otherwise, our data lake will turn into a data swamp.

Categorize your data

Data categorizing is organizing your data into different categories, so it may be used and protected more efficiently. The categorization process of data makes it easy to locate and retrieve.

Use a proper endpoint security system

Endpoint security is the practice of securing entry points of end-user devices, such as desktops, laptops, mobile phones, etc. Below are the ways in which entry points can be protected. 

  • Antivirus software: Antivirus software is a program designed to detect and remove viruses and other kinds of malicious software. For this reason, keeping antivirus software in your system is recommended.
  • Pop-up blockers: Pop-up blockers automatically prevent pop-up windows from interfering with your web browsing. Most pop-ups are just a nuisance and can be malware or redirecting to a website with phishing or another malicious page.
  • Firewalls: A firewall helps your system and data by managing your network traffic. It does this by blocking unwanted incoming network traffic. A firewall validates incoming traffic for anything malicious, like hackers and malware that could affect your data.

Protect data from internal attacks as well

By utilizing the principle of "Least Privilege," an organization can limit insider attacks. Organizations can also track the behavior of a user through Behavior Analytics Software. If the data is more critical, the organization can limit the user for transferring data. 

Beware of phishing attempts

A phishing attack is a practice of sending malicious links that appear to be coming from reputable organizations. It is done through email or chat platforms. The goal is to steal sensitive information like passwords, credit card numbers, login information, etc. You can protect yourself by blocking pop-ups, using security software, two-factor or multi-factor authentication, etc. 

Use encryption algorithm and tool

Encryption Algorithm: The encryption algorithm is the method to convert data into cipher text. An encryption algorithm changes data in such a format that it is unreadable. It can only be turned into its original format when we apply to decrypt the key on it. Some of the most popular encryption algorithms are :

  1. RSA Encryption: RSA is a public key cryptography algorithm founded by Ron Rivest, Adi Shamir, and Leonard Adleman. In this algorithm, the public key is shared publicly, and the private key is kept secret. Having both public and private keys is essential to decrypt the message. 
  2. DES Encryption: Data Encryption Algorithm is developed by IBM. This takes the plain text in 64-bit blocks and converts it into ciphertext using 48-bit encryption.

Encryption Tools -  There are also some tools that can help individuals and organizations in securing data.

  1. Folder Lock: Encrypted folder protects files and folders and helps secure online backup. And also help in protecting against insider attack.
  2. AxCrypt: Axcrypt is a kind of software that helps easily encrypt files and folders. It is essential when you share your system with multiple users and want to protect some files from them.
  3. Windows BitLocker: Windows BitLocker generates a recovery key for the hard drive. So every time you start your computer, a specific pin is needed to access the system. By default, it uses the AES encryption algorithm.

PII Data Detection and Protection using data catalog and Data Governance

PII(Personal Identifiable Information) data detection feature helps recognize sensitive information in unstructured text like mobile numbers, email, credit card numbers, CVV, etc. "Amazon Comprehend" is one of the tools to detect PII in text. 

Data-Catalog helps in hiding data and provides only metadata information to help organizations manage their data; it also helps organizations collect, organize & access data. It also supports data discovery and data governance. 

Data Governance helps organizations manage their data in a limited way. They can't share a user's personal information like a user's credit card number, CVV, address, and mobile number. So governments and organizations make some rules or laws to protect users' data - the European Union has a General Data Protection Regulation (GDPR), and The Constitution of India provides The Right to Privacy as a fundamental right so that the privacy of everyone is protected.

Read and Write protected APIs and the protecting the data platform from third-party or cross-site access.

All APIs and services should use HTTPS rather than using HTTP. HTTPS is far more secure than HTTP; HTTPS uses TLS (SSL) encryption to secure data. 

The CSRF (Cross-Site Request Forgery) attack causes authenticated users to send a request to a Web application to which they have previously been granted access. CSRF attacks take advantage of a logged-in user's trust in a Web application. To protect against third-party or cross-site access to a form, Django uses a csrf_token to protect a user from any cross-site attack. In Django, the code to use csrf in the jinja templating language is as :


Nowadays, these encryption techniques are not enough; people use Blockchain and Hash graph technologies to protect their data. However, these are the basic encryption and security which helps people in protecting their data from malicious attack. Also, some organization uses Hashing to secure their data; as in encryption, if one gets a private key, then he can get the original data; however, in hashing, there is a different hash for different passwords, so it is meant to be better than encryption.

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