Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we define what data sprawl is and how organizations can cope with it effectively.
Data sprawl—defined as the proliferation of data into endpoints, servers, applications, BYODs, operating systems, network environments, and even other geo-servers—can be a challenge to monitor and control. To avoid working in chaotic data environments, organizations need to efficiently manage data sprawl.
When it comes to devices that have access to company data, security becomes a major concern. Cyber risks are on the rise, but a lesser-known and equally dangerous threat is the malicious insider; data sprawl puts companies at a higher risk of falling victim to attacks like data theft or data compromise carried out by employees. Worse yet, many organizations fail to combat these attacks simply because they aren’t aware of them.
Further, with regulations like the GDPR in full swing, mishandling customer and sales data can result in hefty fines for breaching compliance. Your business may even end up losing customers in the process.
Now that we know about the problems related to data sprawl, how do we tackle them? To start, indexing data makes it easily accessible even when hidden; using efficient search techniques makes content discovery much easier. Additionally, enforcing multi-factor authentication (MFA) and single sign-on (SSO) along with properly training employees on data risks and related safety measures will go a long way in preventing data loss. Lastly, deploying a data loss prevention (DLP) tool to analyze sensitive data can help prevent the risks associated with data sprawl.
Here are some noteworthy reads detailing more ways to safeguard your data against data sprawl.
The core cause of data sprawl is the gradual shift to the cloud. To avoid data leaks, some organizations utilize VPNs to encrypt data in transit, but the best solution for data sprawl is establishing a comprehensive set of guidelines for governing data.
Data governance is important, even for data that’s unseen. Business should develop and employ a risk framework that utilizes a number of elements, including automated retention, risk management, compliance, and disposition.
As businesses grow, so does the use of cloud services, ultimately resulting in data decentralization. This can lead to poor visibility of data and data privacy breaches, which can hinder the development of your enterprise. To help mitigate this, organizations should consider cloud disaster recovery services.
Duplication of data can lead to excess utilization of resources like storage and memory, resulting in performance lag. To be more agile, maintaining a single directory of all the data (which can include repositories and backups) with tags and signatures, along with setting the right governance policies, will do the trick.
Data theft, employee negligence, and security gaps can all cause substantial data sprawl. A hyper-converged virtual desktop interface (VDI) can be useful in this situation; since VDIs are stateless, no data is stored in them, reducing the chance of data loss.
Although data sprawl has been around for a while, it persists as a challenge for IT teams. We can’t stop data from being generated, but it’s important to curb this phenomenon before it leads to a data leak. It’s high time that your enterprise evaluates your data environment and chooses the right method to combat data sprawl, before it’s too late.