Data Privacy: Safeguarding Your Data in the Digital Age


The idea that technology carries risks isn’t new. But there’s a problem.

Most people don’t think about how their actions — or lack thereof — impact their risk profiles. In fact, many of us are more than willing to go with whatever’s easiest even when that may be a hazard. Data privacy is one major area where we could stand to improve, and tools like GlassWire make it way simpler to take charge.

What Is Data Privacy?

Data privacy is a subset of data protection. It entails an individual’s right to control what happens with their personal information. This includes how their data is stored, shared, collected, and otherwise used.

Hopefully, you’re thinking this definition sounds familiar. For instance, you’ve probably visited websites that included privacy controls or customizable settings. But data privacy isn’t just about satisfying personal preference. Even though preferences play a big part, information privacy is a matter of security.

Why Is Data Privacy Important?

Data privacy matters because it helps keep people, organizations, and systems safe. Protecting information from bad actors combats unintended victimization, letting everyone benefit from technology.

In some ways, these connections are obvious. For example, a website that lets users choose who gets to see their data might lower their risk of exposure to fraud and identity theft.

The risks of poor data privacy can be subtle yet extremely harmful. For instance, members of marginalized populations who used apps with poor data privacy have been tracked by law enforcement and their employers. Others have been illegally discriminated against by companies that bought their consumer data — a big problem in the age of AI decision-making. Technology-aided suppression and surveillance of political opponents are also common themes in autocratic nations.

It’s important to know that the impacts of poor privacy can impact anyone. You don’t need to be a criminal to be targeted by an oppressive government, and your data may even be used to justify criminalizing you. Hackers don’t care whether you’re a good person or not — they just want to steal your life. It’s critical to improve your odds with tools that detect spyware and other red flags.

Preserving Your Personal Privacy

There are smart moves anyone can take to boost their personal data privacy:

  • Develop better password habits: Don’t use easy-to-guess passwords, and never reuse them across sites. If your passwords get compromised, change them, and consider using a password manager.
  • Don’t use default device passwords: Create a strong Wi-Fi password before enabling your network. The same goes for using security cameras and similar connected devices — keeping the defaults makes life easy for bad actors.
  • Use multi-factor authentication: Having to check your phone every time you log in may seem annoying, but it’s a huge safety win.
  • Stay updated: Software and OS updates ensure you have the latest protection.
  • Don’t just accept the default privacy settings: Privacy settings exist for a reason, and you should use them. In today’s digital marketplaces, your information is a hot commodity. Be sure your favorite sites aren’t exposing you to unnecessary risks.
  • Connect securely: Always look for indicators that you’re connecting securely, like the lock icon in your browser’s address bar. Avoid using public Wi-Fi or regular HTTP connections for things that need to stay secure, like making payments or logging in.
  • Stop sharing everything on social media: Social media isn’t as secure as many platforms would have you believe. After all, the point of sites like Facebook, Twitter, and others is to let people find you. Think carefully about what you’re putting out there!
  • Know and manage your networks: Using network health monitoring tools and firewalls is just as important as installing antivirus software. You don’t have to be a tech genius to stay in control, so it’s worth the minimal effort!

Corporate Data Privacy Pointers

Corporate data privacy overlaps with personal data privacy in many areas. For instance, companies should keep software updated and follow all the other tips covered above. But there are a few extra steps they should take too:

  • Understand your data chain of custody: You should always know where your data travels, who can access it, and how it’s transmitted. Network complexity is no excuse for slacking off!
  • Secure your supply chain: Be certain your vendors match or exceed your own data privacy standards.
  • Create backups: If the worst comes to pass, having a backup will let you recover quicker — and shut hackers out faster.
  • Centralize management: Enact central policies for network oversight and propagate them from the top down instead of relying on individual departments.

Protect Your Privacy With GlassWire

These were just a few pointers on effective data privacy. But there’s a huge difference between knowing what you ought to be doing and following through. Your willingness to get over that hurdle determines whether or not you’ll enjoy the benefits of privacy, so it’s up to you to commit.

GlassWire makes it easy to get started with zero skill or effort. Set up advanced firewall rules, scan your network traffic, and exercise absolute control over what happens on your devices. Start protecting your data by trying GlassWire today.


Decoding Data Management Jargon

data management jargon

In the past, data management was often as simple as a lock and key to prevent access to sensitive files. However, things have moved on a little over the years… Today, data management is a complex environment that can be confusing even for a tech-savvy individual.

In this article, we will decipher data management jargon into simple, easy-to-understand terms, from concatenation to parsing and everything in between. By breaking down this terminology, we aim to outline the data management process and emphasize its importance. 

What Does Data Management Mean Today?

Data management refers to the collection, storage, and use of data in a way that is secure, cost-effective, and efficient. The processes involved ensure businesses and organizations can use data most optimally while still adhering to regulations and policies. By integrating effective data management, organizations can improve their overall decision-making in terms of protecting their data and making it accessible at all times. 

A comprehensive data management strategy is a vital consideration in the modern digital climate where companies need to strive to keep their client’s data safe from cybercriminals. Data is a key asset in any business, and data breaches cost businesses millions of dollars each year. 

To create an effective strategy, organizations must consider the procedures, policies, and practices they adopt concerning daily data handling and usage. Therefore, data management can be very complex, and a strategy must consider the following factors:

  • How data will be created, accessed, and updated across the organization
  • How data will be stored, whether that be on-premises or across multiple cloud networks
  • How to implement effective data security and privacy
  • How to ensure maximum data availability and disaster recovery
  • How data will be integrated with applications, analytics, and algorithmic processes
  • How data will be archived and destroyed under compliance requirements and retention schedules

The Current State of Data Management

In today’s business environment, data management solutions need to be diverse but also unified. To achieve this, data management platforms are required to efficiently manage everything from stand-alone databases to data lakes and even large data warehouses. 

The widespread use of big data and the need for data analytics further emphasize the need for robust management platforms to link everything together. Organizations that have moved towards deploying apps/software onto the cloud must also focus on the finer details, such as enhancing their Kubernetes clusters and encrypting sensitive data. 

Websites and web applications are key targets for cybercriminals looking to gain unauthorized access to data. Popular platforms such as WordPress are considered to post the highest risk due to their many individual components. 43% of all websites still use WordPress as a CMS, even though it comprises 95.62% of all CMS infections, mostly due to outdated core elements. 

Deciphering Data Management Jargon: A-Z

Data management is littered with jargon that can present a challenge for anyone who doesn’t have a degree in data science. In this section, we will provide a simple explanation of a range of data management terms that can sometimes leave people scratching their heads.

Analytical Databases

This database reports on historical information that helps identify trends, monitor customer behaviors, evaluate product performance, and so on. Analytical databases typically do not allow inputs and, instead, process existing data to provide valuable business insights.


This is the action of adding missing data subsets from one or multiple tables to a different database using the programming language SQL. This is commonly used when databases require periodic updates.


A description of the value found in individual fields in a database table. The attribute refers to what the data in the field represents (e.g., a price or customer type), while the value is the actual data contained in the field.


The action of linking consecutive series of field values, strings, or a combination of the two to create a data item or field value. An example of this could be to link the various fields that make up a full mailing address.


Integrating and merging many data sets into a master record, keeping all the relevant information in a single location.

CRM (Customer Relationship Management) Systems

A CRM system is software that organizes and automates a business’s interactions with customers, clients, and prospects in a synchronized way. The key areas CRM systems help to manage are sales activity, marketing, customer service, and technical support.

Data Cleansing

This is the process of standardizing data that has already been inputted. This can include fixing errors such as spelling mistakes, removing duplicates, and adding missing data. This is sometimes referred to as scrubbing.

Data Governance (DG)

The structured processes across an organization that support the overall data strategy to guide all users. Effective DG makes sure businesses adhere to regulatory compliance and data privacy laws without impacting business operations.

Data Migration

The process of moving or copying data from one place to another, for example, an old database to a new one. This often occurs when an organization upgrades to a new data management platform.

Data Profiling

The process of evaluating, analyzing, and reviewing data to gain insight into its quality and relevance. This helps to ensure that data sets are accurate, consistent, and complete.

Database Management System (DBMS)

A DBMS contains several tools and programs that are designed to improve the storage, editing, transformation, accessibility, retrieval, and maintenance of data. This often involves many automated tasks to improve database performance.


Something that is unique and described by a data set. For example, an entity may be a group of attribute values that makes the data set unique from another. This could be a customer name combined with their location.

Extract, Transform, and Load (ETL)

ETL is the standard process for connecting data from different data sources that are based on SQL. ETL maps raw and unorganized data into an organized structure that is attributed and formatted.


The rectangular box where the user inputs data on a database form.

Fuzzy Matching

A data matching technique that is used to calculate probabilities, using algorithms to compare data types for similarities and suggest data combinations that could be useful.


The method of reordering the display of records or rows logically. This is done using keywords to list items based on certain values or attributes, such as a date.


A key is a single field or combination of fields that identifies a record within a table. This record is unique and can be either a primary or secondary field. Keys are often used by software developers to relate a row in one table to a row in a different table, helpful for avoiding duplicates.


This tool is used to compare unique reference data so duplicate rows or records can be identified, useful for standardization purposes.

Master Data Management (MDM)

An enterprise data management architecture that is governed by data quality practices and processes to provide a comprehensive view of data within an organization.


A description of the data contained within a database, helping to identify and create reference data in an MDM system.


A data entry that is undefined and represents an unknown value, potentially impacting the effectiveness of data algorithms.


Parsing is the process of separating field values or data strings into smaller parts, such as breaking down a person’s name into its title, first name, and last name.


The removal of duplicate records from within tables, lists, and files, ensuring the number of redundant fields is minimized.


A database command that quickly retrieves information, generates a list or creates a sub-table.

Single Customer View (SCV)

SCV is where data regarding all an organization’s customers is stored, containing all the relevant master data or core data assets. This provides a single but comprehensive view of a customer or a specific product.


Pronounced ‘Sequel’, Structured Query Language is the standard programming language for database commands, allowing the user to manipulate data and run queries, for example.


A data type that represents a sequence of alphanumeric characters that is fixed in length and remains constant. This data type is typically used for common values such as names, addresses, emails, etc. To use a string, a developer must define its meaning.

Transactional Database

A type of DBMS that is used to handle business operations and transactions. These databases are used for current operations and not historical data like an analytical database.


The action of checking whether a data entity meets data quality standards and regulations. This ensures all data is usable and fit for purpose.


We hope this article has helped to shed some light on database management and some of the confusing terms that go with it. Data is vital for any business, helping to improve current operations, launch sales and marketing campaigns, and much more. 

However, protecting this data and ensuring it meets regulatory compliance can be challenging. By better understanding the individual elements that make up a data management strategy, it becomes much easier to take the necessary actions and implement robust security and safeguarding. 


Cybersecurity Resolutions for 2024

We’re well into the new year, but let’s face it: it’s never too late to start improving.

resolutions for 2024

Today, we’re bringing you some cybersecurity resolutions for 2024, to improve your cybersecurity stance. You don’t have to apply them all, but they’re all worth a look.

1. Start Reading Security Guidances

Learning from others is one of the best ways to dive headfirst into cybersecurity. Bodies like the US National Institute of Standards and Technology (NIST) and the Center for Internet Security (CIS) regularly publish new best practices and security guidance documents. These frameworks cover specific vulnerabilities as well as more general strategies. In other words, studying them is a great way to get your bearings. Here are a few examples to get you started:

2. Implement Comprehensive Cybersecurity Training

You may already conduct cybersecurity training, but are you doing enough? Effective professional education should address different threats and valid responses but also how different facets of an organization relate to cybersecurity.

Remember that cyber safety training isn’t just for your “IT people.” Anyone in your organization can inadvertently contribute to a breach. It’s imperative that everyone who has access to your networks — including IoT devices and non-critical systems — understands their unique role in stopping breaches. They should also know what steps to take when they suspect an incident has occurred and how to use security tools properly.

3. Reassess Your BYOD Policy

Bring your own device (BYOD) policies were necessary long before the COVID-19 pandemic reshaped the modern workforce. But if you think you can simply skate by with what’s worked thus far, think again.

Connected devices aren’t just proliferating in number. They’re also gaining new functionalities and connectivity modes. In a world where hybrid work is the norm and more hardware than ever is online, you should periodically update your BYOD policies. Consider:

  • Are there certain networks that should never allow outside devices to connect?
  • What measures can I use to control how people connect to sensitive systems for hybrid work?
  • When people bring devices like wearables to work, how do I isolate them from secure networks?

4. Fund Stakeholder Certifications

Pay for your team members to get certified in cybersecurity. This does way more than just make their future career paths a bit cushier. Rigorous certifications are grounded in cybersecurity best practices and standards. By subsidizing accredited training, you’ll build a more threat-ready workforce.

Having certified stakeholders on your side is also a smart marketing move. Just look at it from a client’s perspective. Would you want to work with a company that’s certified for its adherence to security standards or blindly trust it to keep your assets safe? Boosting your talent pool with industry-approved credentials makes you far more competitive.

5. Learn Where Your Flaws Lie With an Audit…Then Keep Doing It

Regular auditing helps expose your vulnerabilities in detail. Audits examine your cybersecurity stance from procedural and policy perspectives. They enumerate and explain deficiencies based on your practices, which you can work on right away.

For audits to work, they must be a force of habit. This helps you keep up with the evolving nature of threats, which mutate at lightning speed. Continuous auditing also ensures you won’t fall behind evolving regulations — or fall prey to recently uncovered problems with your IT vendors.

6. Start Vulnerability Scanning — and Not Just on Individual Machines

Most enterprises use some form of cybersecurity tool. But they make a critical mistake by limiting their virus and malware scans to individual computers.

It’s sort of like asking a doctor to look at a potentially cancerous tumor but ignoring whether it might have metastasized. You need to scan for whole-network health, and this means network- and OS-level scanning.

7. Check up on Your Vendors’ Audits and Credentials

Do your vendors satisfy the same lofty security standards you hold yourself to? While this is usually the case when you decide to sign a contract, you shouldn’t take it for granted.

Vendors can and do fail to maintain the cybersecurity quality standards they ought to meet. A quick look at some of IT industry newsletters will reveal countless hacks that came down to third-party deficiencies. Include your vendors in your audits or request their audit data regularly to shore up your defenses.

8. Set up Network Monitoring

Network monitoring is one of the easiest ways to establish your cybersecurity proficiency with minimal investment. Monitoring tools let you watch what’s happening in real-time to stay threat-aware. They help you establish a firm footing in evolving scenarios like hacks and make smarter decisions to limit incidents. Best of all, they do everything in the background so you don’t have to.

Want to learn more about network monitoring and other effective cybersecurity best practices?
Get started with GlassWire.