Enterprise Data Security
What is Data Security?
Data Security (sometimes referred to as Information Security) is a set of processes, standards and technologies used to ensure that (1) data is being accessed and used by authorized parties for authorized uses and (2) data integrity is maintained throughout its lifecycle. While data security is applied to all types of data, a specific emphasis is placed on sensitive data such as personal information or intellectual property.
A few examples of risks that data security frameworks aim to mitigate include:
- Data breaches
- Data leaks
- Privacy violations
- Unauthorized access to data
- Non-compliance with security standards
- Data loss
- Data corruption
Data security may include a wide range of processes, activities and technologies such as data access control, encryption, data reduction and breach detection.
Why is Data Security Important?
In the digital world, data is critical to the viability of a business. Intellectual property, key performance indicators, consumer information and financial planning are just a small number of important functions to running a business that rely on data at their core. Implementing the right controls and technologies to protect data is directly related to a business’ survival. Moreover, it is fundamental to a company’s ability to innovate, succeed and grow.
However, this means that data is valuable to business rivals and malicious entities as well, given that it can be used by competitors to gain competitive advantages or monetized by hackers selling it on the black market. Malicious parties pose a variety of threats that businesses’ must proactively address and mitigate, including breach of data protection laws, reputational damage and financial loss.
Types of Data Security
There are many types of data security processes, standards and technologies used by organizations. Before we discuss them, it is important to understand the fundamental building blocks of a data security program.
Data security, or information security, focuses on three main areas of data protection:
- Confidentiality: Ensuring that data is only accessed by authorized entities.
- Integrity: Ensuring that data remains accurate and complete throughout its lifecycle.
- Availability: Ensuring that data is available for use and processing when needed.
This framework, also referred to as the CIA triad, has inspired different types of data security processes, standards and technologies. Among them are:
- Data access control
- Data backup and restore
- Encryption and tokenization
- Breach detection and response
- Data loss prevention
How do you Ensure Data Security?
Given data’s importance to enterprise success, the market has no shortage of dedicated data protection solutions. Though they vary in strategy and effectiveness, we have found that the following factors play determining roles in how well they they succeed:
- Executive sponsorship: You would be hard-pressed to find a company stakeholder uninterested in protecting a valuable company asset like data. However, aligning on strategy and resource allocation for the task usually requires a healthy amount of persuasion. Organizations that have all of their key stakeholders (technology, security and legal) on the same page are much more likely to implement an effective program.
- Data-centric approaches: As previously mentioned, there are many tools available to address the myriad threats to data security. However, few of them are comprehensive, leading many organizations to address each application of data individually. In such cases, this enormous and resource-intensive undertaking creates a bottleneck for innovation meant to drive a business further. To avoid this and improve security without slowing down business, It is in the interest of organizations to focus on protecting the data itself by placing safeguards around it.
- Continuous monitoring for constant improvement: Information is moving faster than ever before. Technologies, processes and procedures that do not adjust and scale quickly enough to keep up are destined to become obsolete. This requires the focused and proactive implementation of solutions that allow you to monitor, measure and improve data-leveraging over time as well as keep it safe.