How to Manage Data Risk in Your Organization
As organizations increasingly move to digital, the data in your data warehouse becomes a critical asset needed to drive various business operations. The mass adoption of emerging technologies such as cloud computing, IoT, and Data analytics has seen organizations leverage data for decision-making. Even so, some data types are more sensitive than others meaning they could easily be exploited if they fall into the wrong hands.
With that in mind, businesses have become more cautious about data governance, from how their data is collected, stored, and used. Depending on the type and nature of your business, you want to understand the various data risks and how you can protect your enterprise from the looming data threats.
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Types of Data Risks
Data risk is defined as the potential for a loss related to the management, governance, and security of data. Before we look at the different types or examples of data risks, it’s worth noting that data can be classified broadly into three, i.e., high risk, moderate risk, and low-risk data. High-risk data comprises personal information that poses identity risks and shouldn’t be shared publicly. Examples of high-risk data include social security numbers, credit card numbers, driver’s licenses, and bank account numbers.
Moderate-risk data comprises any information that’s not classified as high-risk and is not readily available to the public. On the other hand, low-risk data is data intended for public disclosure. The loss of confidentiality, availability, or integrity of low-risk data has no adverse impact on the business’ safety, reputation, or finances.
Common examples of data risks include:
- Data Corruption – occurs when data becomes unreadable, unusable, or inaccessible to an application or user. Corrupt data means it cannot be trusted; hence it’s not important to the organization. Data corruption is often caused by hardware problems such as hard drive failures, faulty RAM, etc.
- Data Loss – Occurs when vital data is accidentally or intentionally deleted or rendered useless. Formatting errors, viruses, and physical damage are the common causes of data loss. Power failures and malware attacks are the other incidents that can result in data loss.
- Data Breach – This is an incident in which critical information is taken or stolen from a system without the authorization or knowledge of the system’s owner. There are three types of data breaches, namely, physical breach, electronic breach, and skimming. Based on the sensitivity and type of the data breached, the consequences may include theft of IP, leaking of confidential information, corruption of databases, etc.
- Data Remanence and Compliance Issues – data remanence refers to a situation where a computer memory retains previously stored information even after attempts to erase the data. Risk occurs when a firm disposes of a computer or hard disk without checking for data remanence issues or failing to properly degauss or wipe its memory. On the other hand, data compliance occurs when a company accidentally or intentionally provides customer/employee details to a third party violating local or international data privacy regulations.
How to Mitigate Data Risks
The data risks identified above are but a few of the many data privacy and security concerns that organizations face. To successfully protect your data from these risks, you want to deploy an effective data management strategy to mitigate common and emerging data risks. Below is how you can better manage your sensitive data.
Centralize Your Data
An easier way to manage, analyze and track your data is to keep them in one place. In other words, you should not keep data on a desktop or third-party data management software. You also want to avoid redundancies or creating unnecessary copies of your data. Where possible, have a centralized enterprise data storage and analytics solution where all your sensitive data resides. However, this doesn’t mean you should not have a data backup plan.
Rethink Data Access Control
Another critical step to mitigating data risks is to ensure only the right people have access to the information they should have access to. Implementing a principle of least privilege ensures that a user is allowed the minimum level of access or permission. This minimizes misuse of privileges and reduces risk exposure to sensitive enterprise data. Other ways to limit unauthorized access to data are by implementing row-level security and zero-trust network access.
Establish Clear Data Governance Rules
Last but not least is to have clear rules on what constitutes data risks and the role of employees, managers, customers, and all the other stakeholders in upholding data security and data privacy best practices. The rules and regulations governing data collection, storage, access, and use should be consistent and applicable throughout the organization.
A rule of thumb is to invest in a comprehensive risk and compliance solution that protects your business from not only data risks but also market risks, cyber threats, and various compliance issues.
Every modern-day business understands the critical role of data in driving innovation and organizational growth. The data you collect from customers, employees, and the broader market is valuable not only to you but also to the other entities outside your niche or industry. That means everyone is hungry for your data, and failing to keep up with data privacy and security guidelines could lead to data breaches and data loss. Take action today by centralizing your data, rethinking data access control, and establishing clear data governance rules.