A holistic view of privacy and data protection will incorporate data security. It is important to understand that protection and privacy starts with data discovery. To achieve this, a business must know its data, protect what matters most to the organization, and use data securely.
Modern data discovery platforms use artificial intelligence to quickly identify risks, which in turn provides the information needed to act effectively and efficiently. The goal today is data protection everywhere, in analytics and applications.
Data security is the process of protecting data against unauthorized access and data corruption throughout its lifecycle. The term encompasses data encryption, hashing, tokenization, and key management practices that protect data across all applications and platforms.
Before you throw your hands up in industry jargon, arm yourself with information that will explain why companies should invest in data security.
To protect critical assets, organizations around the world are investing heavily in cybersecurity. Whether a business needs to protect a brand, intellectual capital, customer information, or provide controls for critical infrastructure, the means of incident detection and response to protecting organizational interests have three common elements: people , processes and technology.
Data security is a major issue today in a world where global data creation is expected to reach over 180 zettabytes by 2025.
Companies are increasingly under pressure to be agile and flexible. Top-notch customer service is the name of the game for any business and the ability to quickly meet consumer expectations is crucial in an unforgiving climate where the power of supplier choice puts the customer in the driver’s seat.
Most enterprises now use multiple cloud providers, which complicates efforts to protect sensitive data flowing through hybrid IT.
These challenges are also driving cloud adoption for many enterprises due to the increasing cost and complexity of maintaining on-premises data center hardware and software.
Companies that need increased capacity for growth or experience seasonal peaks in activity have realized that it is more cost-effective to leverage the elastic capacity of the cloud when needed, rather than to acquire, manage and maintain data center hardware and software.
Enterprise security and risk professionals responding to research on cloud data security confirm that more than 40% of their enterprise data in the cloud is sensitive in nature and insufficiently secure.
Adding further complexity to the problem, the Ponemon Institute found that, on average, companies today use 27 different software-as-a-service, infrastructure-as-a-service, and platform-as-a-service solutions. service to run their business.
Traditional security controls built into all existing IT infrastructure are proving increasingly ineffective as data has become more ubiquitous, mobile and cross-functional.
Most businesses now use multiple cloud providers, which of course complicates efforts to protect sensitive data flowing through hybrid IT.
With the increasing number and complexity of privacy regulations, such as the GDPR and in South Africa, POPIA, there is an increasing trend in the number, scope and scale of data breaches. This in turn drives the need for more effective measures to protect sensitive data wherever it flows, whether on-premises, in cloud infrastructure and applications, or on analytics platforms.
The combination of these powerful business engines and ineffective security controls has unfortunately already led to sensitive data being migrated to the cloud before the organization is ready to secure it.
Large-scale data breaches—typically associated with missing, ineffective, or misconfigured cloud-native data security capabilities—are increasing, as are fines imposed for non-compliance with data privacy regulations.
Businesses need to focus on protecting sensitive data across multicloud, hybrid, and on-premises environments. Data-centric security should be integrated across hybrid IT, reducing risk to sensitive data and accelerating secure migration to cloud environments.
It is necessary to apply security solutions that allow applications, data and data stores to interact with on-premises and cloud services; it’s the only way to achieve end-to-end protection throughout the data lifecycle.
The first prize is for companies that implement data-centric, platform-independent security measures that aim to keep data usable. The goal is to deploy solutions that are flexible to implement and provide protection for a virtually unlimited number of structured data types in any language and any region, with proven performance and scalability. .
Organizations must be able to identify sensitive information in a way that neutralizes the effects of a data breach, but also enables continued use of data in its protected state in applications and on analytics platforms .
It is critical to retain the context and meaning of the data, such as its referential relationships, logic, and business intent, in its protected form, while ensuring that the business can minimize decryption requirements.
Preserving referential integrity also allows protected data to be reliably referenced and joined for cross-cloud analysis, providing key information via identifiers, such as phone numbers or user IDs, common to disparate data sets.
In my next article, I will provide a data protection roadmap for businesses using payment card data on-premises or in the cloud.