04/04/2024
In Part 2 of our series exploring dark data, we will delve into why it is a problem for organizations. We'll look at the various challenges associated with dark data and how it can impact a business negatively if not managed properly. Join us as we explore the reasons why dark data should be taken seriously, and how organizations can mitigate its effects.
Dark Data is a growing concern for enterprises. With the exponential growth of data, managing and leveraging it effectively has become a critical challenge but valuable pursuit for organizations. In this series of articles, we will delve into the world of dark data, exploring what they are, challenges, and opportunities. We will also take a deep dive into how to unearth all data hiding in darkness and how to tackle them. Join us as we embark on a journey of discovery, unlocking the potential of dark data in organizations
Although dark data often contains personal, regulated, sensitive, vulnerable, or high-risk information that must be kept out of the wrong hands due to the very nature of dark data, it often remains unnoticed, unanalyzed, and unprotected. This can lead to substantial costs and problems with regulatory bodies, data privacy laws, and a plethora more issues.
Actively, dark data increases security risk by existing in a company's system without the proper safeguards around it. Unknown data also goes without the necessary regulatory processes a company would normally put in place for compliance. This makes the data a prime target for malicious attackers, as it remains unnoticed and unprotected.
Another challenge posed by dark data is the growing regulatory requirements. With the introduction of policies such as GDPR, NYDFS Section 500.13, and California's CCPA, organizations are being forced to rethink how they capture and store content. Failing to properly manage and store data can have serious consequences for organizations, as it can lead to hefty fines and penalties and even destroy a business completely.
One of the key challenges posed by these regulations is the need for organizations to identify and protect personal data within their systems. Dark data are, in the eyes of the law, still data whether organizations are aware of their existence and so not exempted from the regulatory requirements. GDPR, for example, requires companies to protect the personal data of EU citizens, regardless of where the company is based. Failure to comply with these regulations can result in severe penalties, including fines of up to 4% of a company's global annual revenue or €20 million (whichever is greater).
Another challenge is providing transparency and control to individuals over their personal data. The California Consumer Privacy Act (CCPA) gives California residents the right to know what personal information is being collected about them and the right to request that their personal information be deleted. Organizations must be able to locate and manage personal data, including the unstructured and semi-structured data that make up the dark data, to meet these requests.
These regulations also necessitate that organizations implement necessary security measures to secure personal data. This includes encrypting data, implementing access controls, and regularly monitoring for potential breaches. To demonstrate compliance with these regulations, organizations must keep accurate records and frequently evaluate their data management practices, including those related to dark data.
When organizations seek to move forward with new technologies and capabilities, they need to decommission old applications and systems in favor of new ones, such as cloud-native applications, which can drive competitive differentiation.
However, as organizations move to new systems, they must also deal with accumulated data in their legacy systems. This includes dark data, the vast amounts of unstructured and semi-structured data that organizations collect, process, and store. As companies migrate their data to new systems, they must also determine which data is important to keep and which data can be discarded, a process known as data governance.
Data governance becomes even more complex when it comes to dark data, as this data is often unstructured and difficult to classify. Without proper data governance, organizations risk migrating unnecessary data to their new systems, which can increase costs and reduce the effectiveness of their digital transformation efforts. Organizations also risk exposing sensitive data to security breaches and compliance violations if they don't take proper measures to protect it.
Storage costs are also a major concern when it comes to dark data. While storage may have historically been cheap, the rate of growth in stored data volumes is now exceeding the rate of lowering costs. There are some studies indicating that companies spend five digits in storage costs alone just for dark data. All of these factors mean that the more information organizations store, the more their costs increase, even as storage costs decline. Plus, many modern applications store their entire database in active memory, which further drives the need for data optimization.
All things considered, as the creation and capturing of data grow exponentially every year, the challenge and costs related to dark data are rapidly growing. It is time to tackle this problem properly and unearth all dark data to bring them to light.
It's clear that Dark Data presents many challenges for organizations, but by recognizing the problems it creates and taking proactive steps to manage it, organizations can derive valuable insights and maximize the value of their data assets. In Part 3 of our series, we'll shift our focus to finding Dark Data and examine best practices for evaluating and identifying what data has gone "dark" within your organization. Stay tuned!
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