The world is full of data, from text messages to video clips to credit card numbers. And the amount of data is constantly growing. In today’s tech-driven information age, companies rely on and produce massive amounts of data every day — most of it (almost 80%) is unstructured. But regardless of the industry, this observation often leads to a common question: what is unstructured data?
Unstructured data is data that’s difficult for computers and systems to search systematically. This class of data is usually created by humans and can include social media posts, audio files, and video content. It is often spread throughout a company because it exists anywhere users access or create content. Unstructured data is qualitative and includes sensitive and personal data that, if leaked, can be detrimental to a company. It’s often stored in applications, data lakes, and non-relational databases.
The qualitative nature of unstructured data can be problematic, to say the least. Disorganized and subjective by nature, it is extremely difficult to search, which explains why 13% of working hours are spent each year looking for data. But how prevalent is this problem? To say that it’s a global challenge would be an understatement. About 90% of the world’s data is unstructured and siloed, and 96% of the data created goes unused. As unfortunate as these statistics are, recent trends suggest that the problem isn’t going away. In fact, only 1% of productivity growth has occurred over the last 20 years.
There’s clearly a lot of work to do. Thankfully, organizations can start taking steps to remedy this problem. If unstructured data is made compliant, secure, and visible, businesses can make better use of their data and employees’ time — and improve their bottom lines as a result.
Achieving Data Compliance
Data compliance refers to the formal standards and practices that protect sensitive data. These standards define what type of data needs to be protected, what processes need to be implemented to protect that data, and what penalties will be used if companies are not compliant. Since companies are responsible for large amounts of data, from customer to employee data, these guidelines are critical. All parties involved with a company generate highly sensitive data, commonly referred to as personally identifiable information (PII). This information can include credit card and cardholder information, health information, annual revenue, and other financial details.
Data compliance aims to protect company and customer data from loss, theft, corruption, and misuse. The standards also specify a company’s regulations about how its data is organized, managed, and stored. Some examples of data compliance requirements include:
Data Inventory - By taking regular inventory of their data, companies can ensure their data is organized and tagged so that they can take the proper security measures.
Auditing Access to Data - Companies should keep track of what data is being stored, where it’s being stored, what the data is used for, and how it will get destroyed upon request.
Managing Data Access - Companies should monitor who has access to sensitive information and regularly report on user access.
Let’s be clear: data compliance is not the same as data security. While both aim to protect data and prevent breaches, data compliance simply ensures the minimum legal requirements are met. However, data compliance is a vital step toward data security that can improve a company’s security posture and ensure that a company doesn’t lose money to fines related to data breaches and compliance violations.
Data compliance also helps build customer trust, which is critical to a company’s success. Regardless of their cause, data breaches cause a loss of trust and loyalty from customers. According to a Varonis analysis, 80% of customers will defect if a company has compromised their data. Additionally, 52% said they would pay the same amount for products or services from a different company that offers better security.
One of the most widely used data compliance standards is General Data Protection Regulation (GDPR). Created by the European Union, GDPR gives consumers easier access to the data companies hold about them and the ability to request the deletion of their data from a company’s database. For the reasons detailed above, unstructured data poses a significant risk to GDPR compliance. The first step to achieving GDPR compliance is locating all PII so a company can know where data is stored, why it’s being processed, and who has access to it. Unstructured data can be challenging to search and organize without the proper software, making it difficult for companies to stay GDPR compliant.
Securing Unstructured Data
Data security takes data compliance a step further. Due to its constantly changing nature, data generally can be difficult to secure — unsecured data even more so. There are several steps companies can take to help protect their data against unauthorized access.
They should start by identifying unstructured data at the point of creation. When data is exported from a database into a shared document or stored on a thumb drive, there is less control over access and monitoring. This security risk can be mitigated using secure data environments that store unstructured data files and keep track of them upon creation.
Next, the organizations should classify their data. Only some unstructured data is sensitive, so only some things need to be tightly secured. Sensitive data includes files that should be protected for legal or regulatory reasons, proprietary data such as intellectual property, banking details, customer lists, and PII of customers and employees. By classifying this data, companies can better focus their security efforts on the most sensitive data.
Once this sensitive data is identified, companies should assign an owner to it. This owner will become responsible for the data’s security and be charged with tracking who has access to unstructured data and reporting any activity on those files. To enhance their effectiveness, these owners should also be able to restrict, manage, and monitor all access.
Naming a data security owner is a great start, but maximizing overall protection and compliance requires companies to consider several factors. For starters, a global namespace allows data to be easily accessible and visible to users no matter where it lives. It also removes the hassle of sifting through per-site storage islands. Another critical factor is the ability to provide local-feeling performance. Data will be most useful if companies use a file system that maximizes remote speeds to deliver local-like performance that lets them fully utilize their data, no matter where it’s stored. Block-based and object-based storage enable high performance by making data more available, durable, and adaptable to their changing needs.
While all these steps are critical, they can feel overwhelming for any business looking to enhance its data compliance and security. This is where bat365 shines. Leveraging the power of our patented cloud data solutions, we help companies do all of this while keeping their unstructured data tightly secure and eliminating inefficient data silos.
Breaking Down Data Silos
A data silo is a collection of data held by one group in a company that is isolated from other groups in that same company. In most instances, these silos are unintentional. Different teams create and access specific sets of data that they store separately, creating silos. Data silos can also form when companies have missing or inaccessible information, too many data sources, ineffective organizational structures, or flawed company culture.
While seemingly harmless, data silos pose a major threat to companies. The dangers extend far beyond internal confusion that comes from disorganization. Data silos harm productivity. They discourage collaboration. They complicate business management. They slow down data-driven decision-making. They reduce data quality. All of these challenges have a financial impact on the company, which means data silos can damage the company’s bottom line. Breaking down these silos is the only solution.
Companies can start this process by consolidating their data. They should identify data silos and find ways to consolidate systems. Next, they should take a careful look at their company culture. Strange as it may seem, a company’s ability to prioritize trust and accountability within its teams directly affects data sharing and the setting of appropriate permissions. Companies should make breaking down silos a core part of their strategy and prioritize it as much as possible.
Without silos, teams can find answers and get help quickly, allowing them to make more informed decisions and deliver better results. Individuals experience improved collaboration as different people can work on a common set of data in real time. Knowledge sharing gets easier as teams can share data and best practices across the company for essential projects. Company-wide benefits also become apparent. Efficiency increases as breaking up data silos clears IT roadblocks that prevent productivity and resource utilization. Additionally, companies routinely notice an overall increase in productivity, delivery, and profitability. Studies have shown that connected teams demonstrate a 30% increase in productivity and a 21% increase in profitability. Regardless of the business or industry, those are powerful improvements.
Unstructured data not only comprises a majority of organizational data but is also integral to their success. Ensuring that this data remains compliant, secure, and visible is always worth the time, effort, and financial investment — for the company and its customers. Reach out to a bat365 representative today and find out how our cloud data solutions set a new industry standard for securing and managing unstructured data.