With digitization continuing to impact business enterprises and make them more competitive, there is a looming specter of data security challenges as well. Executives cutting across domains are faced with the challenging job of protecting the data of their respective organizations. However, this needs to be done without degrading their ability to innovate and add value from technology upgrades. They need to constantly think about protecting their digital assets by assessing threats and meeting stringent regulatory and customer expectations. With Agile and DevOps being the operative words, they need to navigate disruptions caused by cybersecurity threat vectors consistently, possibly by leveraging data engineering and insights.

According to Statista, the year 2022 saw massive spending of $71.68 billion by business enterprises to shore up their IT security infrastructure. Cisco reported that around 50% of large enterprises spend $1 million or more on cybersecurity annually. This underscores the magnitude of threats faced by them and the need to be vigilant to overcome data security challenges.

Data security has become a critical concern for businesses of all sizes and across domains. However, digital-native companies find themselves increasingly vulnerable to data breaches and cyber-attacks, given their reliance on digital technologies and the sheer volume of data they generate and process in real time. Such companies can be defined as those born in the digital age that has since grown into becoming leaders in their respective niches, such as Google, Amazon, and Facebook, among others. However, it is the smaller companies, startups, and SMBs that find themselves staring down the barrel of cybersecurity threats. Such companies need to build a robust IT infrastructure where they can leverage data engineering and insights to make informed decisions and ensure data security.

With the growing menace of cybercrime threatening their existence, such companies need to leverage data engineering services to build robust data repositories at scale and save sensitive business and customer information. Digital-native companies need to develop innovative data security solutions and strategies to ensure the security of their data. In this article, we explore how digital-native companies can overcome data security challenges, including charting a data engineering roadmap.

How Can Digital-Native Companies Overcome Data Security Challenges?

With business enterprises relying on data to conduct critical operations, necessitated by their shift to a hybrid work culture, data security has become critical. The various ways in which digital-native companies can overcome data security challenges are as follows:

Use of Advanced Authentication Technologies: Digital-native companies can hire data engineering services to build advanced and secure data repositories at scale. With such repositories, they can use advanced authentication technologies, such as biometric identification and multi-factor authentication, to protect their systems and data. Biometric identification, such as facial recognition or fingerprint scanning, is an effective way of ensuring that only authorized individuals can access sensitive data. Additionally, multi-factor authentication requires users to provide two or more forms of identification, such as a password and a fingerprint, making it more difficult for hackers to gain access to the system.

Continuous Monitoring and Analysis of Data: Digital-native companies must continuously monitor and analyze their data for any suspicious activity or potential threats. They should use advanced analytics tools, state-of-the-art data engineering solutions, and machine learning algorithms to detect anomalies and potential security breaches in real time. These will enable them to quickly identify and respond to any security threats before they can cause significant damage.

Cloud Security: Today, business enterprises rely heavily on cloud computing platforms to store and process their data. They use advanced cloud security technologies, such as encryption, to protect their data from unauthorized access. Encryption ensures that data is unreadable without the appropriate decryption key, making it more difficult for hackers to access sensitive information. This is where enterprises can seek data engineering consulting to secure data while using it at scale.

Collaborative Security: Ensuring data security in an omnichannel environment needs to be a collective effort involving the efforts put in by the entire organization. They should conduct training and awareness programs for employees and encourage them to take an active role in upholding data security. They also need to collaborate with external security experts, such as data engineering experts, to share information and develop best practices for data security.

Proactive Risk Management: Businesses need to take a proactive approach to risk management, including hiring data engineering consulting. They need to conduct risk assessments regularly to identify potential vulnerabilities and threats to their systems and data. This will enable them to develop strategies and implement measures to mitigate those risks before they can cause significant damage.

DevSecOps: Business enterprises, especially digital-native companies, need to embrace DevSecOps. It is a software development approach that integrates security into every stage of the development process. DevSecOps, which may include enterprise data engineering, ensures security as a concept is built into the software framework from the very beginning. It helps reduce the risk of vulnerabilities and potential security breaches.

Compliance with Data Protection Regulations: Digital-native companies, or for that matter, any company operating in today’s highly competitive digital era, need to comply with data protection regulations. These may include GDPR, HIPAA, PCI DSS, and CCPA, among others. By complying with such industry regulatory standards, they can achieve data access controls. Moreover, compliance with regulations can help them ringfence their IT infrastructure from cybersecurity threats and help gain customer trust and acceptability. They can even protect themselves from being penalized in the unfortunate event of data breaches.

Conclusion

Digital-native companies face significant data security challenges from an increasingly sophisticated threat environment. However, they need to develop innovative solutions, including data engineering solutions, to protect their sensitive business and customer data. The measures mentioned above are a few effective strategies that businesses can use to overcome data security challenges. With these measures, they can ensure the security of their data, prevent incidences of data breaches, and maintain a competitive edge in the market.