In today’s hyper-connected digital universe, safeguarding data has become an indispensable priority for organizations worldwide. Your data is your most valuable asset, and protecting it should be a top priority. But how can you protect what you don’t know exists? Adopting a “Shift Left” mindset in your data discovery platform is the answer. Let’s delve deeper into this concept and understand how it can help enhance your data security.
The concept of “Shift Left” in data security involves bringing security considerations earlier into the data lifecycle instead of waiting until later stages. By shifting security left, you are integrating it into the initial stages of data creation, ingestion, and collection. This proactive approach significantly enhances data security, as risks can be identified and mitigated before they become serious threats.
You Can’t Protect What You Don’t Know Exists
Projected to grow at a CAGR of 24.3% from 2021 to 2028, the data classification market size is expected to reach USD 4544.30 million by 2028, highlighting the importance of gaining insight into your data as the initial step towards enhancing data security. Most organizations today have a massive amount of data, much of which lives in different places and formats, and is accessed and used in different ways. However, organizations often don’t have complete visibility into everything they have, or even a fraction of it.
Unknown data can’t be protected and creates a significant security risk. It’s like owning a treasure chest but not knowing where it is, which makes it prone to theft. Therefore, the first step in implementing a “Shift Left” approach in data security is to gain complete visibility of your data.
You gain several benefits by integrating data security measures and practices at the beginning stages of software development. First, you can detect and fix vulnerabilities early, reducing the risk of data breaches. Second, it allows you to build security into your data from the outset rather than trying to bolt it on later. Finally, it ensures that security is considered at every stage of the data lifecycle, making it an integral part of your data strategy rather than an afterthought.
Enhancing Data Security Through Early Classification
Once you have visibility of your data, the next step is classification. This involves categorizing your data based on its sensitivity and value to the organization. Accurate recognition of confidential information can facilitate the implementation of suitable security measures to safeguard sensitive data.
It also helps in regulatory compliance, as many regulations require businesses to protect specific data types. By classifying data at the point of creation, ingestion, or collection, you can ensure that sensitive data is adequately protected from the beginning.
The data classification process can serve as a cornerstone for an effective data security strategy, enabling organizations to distinguish between public, confidential, or sensitive data. This categorization is crucial for developing a layered security approach, wherein data of higher sensitivity is accorded more robust protective measures.
Furthermore, data classification aids in managing risks and ensuring legal discovery. It eliminates the chance of redundant data storage, enhancing efficiency and cost-effectiveness. With the rise of data breaches, early and precise data classification can act as a proactive shield, securing the organization’s most valued digital assets. Hence, prioritizing data classification can significantly bolster an organization’s data protection efforts, ensuring a safe and secure digital environment.
Finding and Classifying Data at Scale
To fully implement a “Shift Left” strategy in data security, you need to be able to find and classify data at scale. This is a significant challenge, given the volume of data that most organizations deal with.
A data discovery platform can help organizations find, track, classify, and manage their data. Such platforms use advanced technologies like machine learning and artificial intelligence to discover and organize data automatically. They can analyze large volumes of data quickly and accurately, making them an essential tool for implementing a “Shift Left” strategy in data security.
Implementing a “Shift Left” strategy for improved data security involves several steps:
- Identify and Classify Data: Understanding the nature of your data is the first step. By identifying and classifying data from the point of creation, you ensure that sensitive and critical information gets the right level of protection from the start.
- Implement Security Measures Early: Rather than adding security controls as an afterthought, they should be incorporated during the initial stages of the data lifecycle. This early adoption of security measures helps prevent data breaches and minimize potential risks.
- Foster a Security-First Culture: Creating a security-first culture within the organization is crucial for a shift left strategy. This involves training all staff members about the importance of data security and promoting practices that prioritize data protection.
- Use Automated Security Tools: Leveraging automated security tools for data protection can help identify vulnerabilities and threats in real-time. These tools can be configured to monitor data activity and alert you to suspicious behavior, allowing you to take immediate action.
- Regularly Review and Update Security Policies: Security requirements evolve with time and technology, hence, it’s essential to review and update your security policies periodically. This ongoing evaluation ensures that your data protection measures align with current threats and regulatory requirements.
- Conduct Regular Security Audits: Regular security audits are vital in identifying any weaknesses in your data protection strategy. These audits provide an opportunity to assess the effectiveness of your security measures and make necessary adjustments to enhance data security.
Adopting a “Shift Left” approach in data security can substantially reinforce your organization’s defense mechanisms. This strategy involves a clear understanding of your data, early classification, and integrating security measures throughout the data lifecycle, all of which help safeguard your most precious resource – your data.
It’s important to remember that data security isn’t a one-off project but a continuous undertaking. Hence, reviewing and updating your data security strategies regularly is critical to stay ahead of the ever-changing threat environment.
Working as a cyber security solutions architect, Alisa focuses on application and network security. Before joining us she held a cyber security researcher positions within a variety of cyber security start-ups. She also experience in different industry domains like finance, healthcare and consumer products.
