By the year 2025, an estimated 463 exabytes will be created daily. For reference, one exabyte is 8,000,000,000,000,000,000 bits. That’s a lot of data. And even though cyber-attacks will increase as the attack surface expands, with cybercrime costing the world $10.5 trillion annually by 2025, data will remain the most valuable resource for today’s global enterprise.
Much of the available data will fuel innovation across the enterprise, from sales and marketing to IT and HR, allowing the C-suite to make decisions based on tangible information. While data is ubiquitous across all enterprises, some industries that rely most heavily on data and data analytics include:
- Financial: Banks, FinTech, and Private Equity Firms
- Healthcare: Pharmaceuticals, health insurance and specialized care
- Retail: Grocers, supermarkets, and wholesalers
To unlock the true value of data and enable real-time decision-making, organizations must ensure their data is protected across the enterprise, regardless of industry.
What Is Enterprise Data Security?
Enterprise data security is the processes and tools used to protect an organization’s information from unauthorized access and ensure its digital integrity. The main goal of enterprise data security is to protect data, with special consideration given to sensitive data like Personally Identifiable Information (PII), Payment Card Industry (PCI) Information, Personal Health Information (PHI), and Intellectual Property (IP), and enable data accessibility for authorized users.
Existing data protection methods include firewalls, multi-factor authentication, encryption, data masking, tokenization, anonymization, pseudonymization, hardware-based security, and role-based access controls. Data can also be backed up or deleted as needed.
Unsurprisingly, the industries that rely most heavily on data are also some of the industries most in need of data protection due to the nature of the data collected and industry data regulations.
- Financial: Attackers are particularly interested in account and credit data. Several financial data compliance regulations exist, including the Payment Card Industry Data Security Standard (PCI DSS), Nacha, and SWIFT Customer Security Program (CSP) requirements.
- Healthcare: Hospitals and insurance providers store extensive PII and PHI on patients. They must also maintain compliance with the Health Insurance Portability and Accountability Act (HIPAA).
- Government: Government entities have sensitive data related to extensive citizen information and state to federal-level intelligence. This information is particularly appealing to state-sponsored and international attackers.
What Makes Enterprise Data Security So Critical?
Revenue Loss
While data is extremely valuable to global business, data loss can cost an organization millions of dollars. IBM’s 2022 Cost of a Data breach report underscores phishing, emails, or other message sent by an attacker that appears to come from a reputable source. This remains one of the top causes of global data breaches and the most costly cause, costing $4.91 million per breach. It was also the number one cybercrime reported to the FBI’s Internal Crime Complaint Center (IC3) in 2021.
Disrupted Business Operations
Beyond the financial implications, a security breach can disrupt business operations, leading to downtime and lost productivity.
Reputation Loss: Customer Loyalty & Trust
Customers also expect their data to be kept safe. As a result, a data breach can damage your customer relationships and your business’s reputation.
Non-Compliance Fines
Enterprise data security can also help prevent data privacy regulation violations, which can be costly and result in legal sanctions. For example, severe infringements of Europe’s General Data Protection Regulation (GDPR) could result in a fine of up to €20 million, or 4% of the company’s annual revenue – whichever is higher.
Falling Behind in Industry Markets
When data is lost to a breach or when organizations are slapped with a hefty non-compliance fine or lawsuit, a corporation is at the highest risk of falling behind in their markets. That means they can no longer compete or will often have a harder time recovering, taking years to be a serious competitor in their industry again.
A comprehensive enterprise data security architecture can help prevent data breaches and data loss, regardless of the cause, making it a critical component of your cybersecurity infrastructure.
Creating An Enterprise Data Protection Strategy
Enterprise data security is a critical component of a cybersecurity defense-in-depth strategy. It’s essential to understand your data environment so you can create a data protection strategy based on your organization’s needs. Here are some steps and questions you can ask yourself to help you build a comprehensive enterprise data protection strategy.
- Where are our existing vulnerabilities?
Identify your users, your devices, and your databases; do an audit of any gaps in
your current security to see where the potential for data loss exists.
- What kind of data do we have?
Classify which data is sensitive, which data is public, and where your data travels and stored.
- Who can access sensitive data?
Review access levels and ensure data is accessible to those who need it and protected from those who don’t. According to the EU General Court, pseudonymized data transferred to authorized parties that cannot re-identify data subjects is an acceptable method to protect your data while allowing improved access and usability for authorized parties.
What is Pseudonymization?
Pseudonymization is a reversible method of data protection that hides the identity of the subject by replacing information fields with artificial identifiers, or pseudonyms. Only the real information can be accessed by authorized parties. Pseudonymization can be done through tokenization or encryption
- Are we migrating to the cloud?
Cloud security presents new challenges. Whether on-prem, in the cloud, or in a hybrid environment, your data protection efforts must reflect that. Ensuring data protection across your data lakes and app integrations is crucial when it comes to migrating to the cloud.
- What is your disaster recovery plan?
A breach could happen at any time, which is why having a disaster recovery plan to ensure the security of your data is crucial. When developing your plan, consider the following:
- Do we have backups of our data?
- Are we able to delete breached data?
- Will we pay ransom to retrieve data?
Answering these questions can help build a foundation for an extensive disaster recovery plan and allow your organization to fill any gaps in their data protection processes.
- With what data compliance laws must we comply?
Determining what compliance requirements are relevant to your business is hinged on a few factors. Does your company transfer data among counties, states, and international lines? Where is your data stored? What does your industry require to be compliant? Having a compliance officer can ensure your systems and data are in line with regulatory requirements, preventing hefty fines should any systems be non-compliant.
Finding the Right Enterprise Data Security Solutions For You
Securing the perimeter is no longer enough. Once you have an enterprise data security strategy, you should clearly understand your organization’s data protection needs. To help you implement that strategy, look for a platform that offers visibility into data. This transparency should enable you to easily discover and classify your sensitive data, whether you’re on-premises, in the cloud, or somewhere in between.
The Protegrity Data Protection Platform offers data protection across your apps and integrations, whether on-premise or in the cloud. You can choose the best protection methods for your data, including:
- Pseudonymization: A reversible method that swaps out sensitive data for pseudonyms
- Dynamic and static data masking: Methods used to cover, or mask sensitive data without changing the data itself
- Encryption: A method of converting sensitive data into code
- Data tokenization: Replacing sensitive data with tokens
- Anonymization: An irreversible method used to remove direct identifiers in the data and generalizes the information such as race, birthdate, and gender
With a variety of data protection methods at your fingertips and the transparency to assign protection to specific fields, files, dashboards, organizations are empowered to advance their protection while scaling in revenue and competition.
Learn why data protection platforms are essential in preventing data loss here. Or you can contact us today for more specific information.
Fewer Barriers, Better Protection