Data is one of the key elements of making decisions in a company. The data could come in various forms like an employee’s profile, financial statements and so on. You may say data is one of the most valuable assets a business can hold. However, data is consumed by a wide range of applications and operating systems and stored on a variety of endpoints and servers. You may store it locally or on various cloud storage platforms. Having such a complex and distributed I.T environment leads to “data sprawl”. This poses a huge risk to the data and company respectively.
Data Sprawl: An Overview
Data Sprawl occurs when an organization collects, processes and stores large amounts of data and it becomes difficult to keep track of what data they have, it’s location and who has access to it. To understand the concept better, you can liken it to a situation where an organization keeps their files in cabinets and drawers. These cabinets and drawers may be scattered around different floors of the building. For a worker to have access to such files, he/she will have to go to a different floor each time. Stressful, right?
In the same way, data files are stored across various cloud storage platforms, laptops, desktops, tablets and so on. Because of this, it becomes increasingly harder to monitor and control data stored on diverse systems. It also makes it difficult for employees to retrieve the data they want, thereby resulting in loss of productivity.
Additionally, business enterprises make use of these data to make important decisions that affect its growth. It becomes significantly challenging when they store across multiple environments. This calls for urgent attention because many businesses have fallen as a result of data sprawl.
What Causes Data Sprawl?
Many businesses in this age rely on a wide range of devices, applications and operating systems to create and store data. Too many data sources contribute to data sprawl posing a risk to the organization. Below are some of the causes of data sprawl:
- Company files located across many different storage systems and cloud storage platforms.
- Making use of different operating systems such as Windows, Linux and macOS which utilizes different file types.
- Lack of training and discipline amongst the workforce. This is with regards to how they create, use and house mission-critical information.
- Having multiple copies and versions of the same files existing on those various file storage systems network-wide.
Dangers of Data Sprawl
Bits of information on the same subject could scatter across different devices, making cross referencing data a real problem. For instance, when creating a full consumer profile, you may need their project data, contact number and payment information but they are located in different places. You may not even have access to some of them.
Every system that has access to sensitive data is a potential for cyber attacks. Without knowing all the locations your sensitive data is located in, you can’t implement the right security measures for your infrastructure, your data and your employees.
Companies perform analytics on their data in order to make important business decisions. When they store data across multiple applications, it becomes difficult to access them. This leads to incomplete and unreliable information that you cannot use to evaluate a company’s true financial position.
Probably, the greatest danger to a company originating from sprawling data is old data. Unused files that have been in their system for a long time may pose a data security risk because they might not be aware that they contain sensitive information. If an employee inadvertently gives someone access to that file, they may create a security risk for the company.
What Is The Way Forward In Managing Data Sprawl?
Perhaps, the first step may be to determine what security training is needed and for whom. Gain visibility into all the locations your sensitive data is stored in and all users who are accessing it. This is so you can make a decision around what type of security tools and processes to put in place. Once you discover all risky destinations your IP is going to, such as unapproved cloud apps, external and personal email, personal cloud storage, external devices and more – you can start to determine how to reduce and mitigate risk.
As I’ve mentioned earlier, organizations store a lot of data that is either duplicated or redundant. It is a good idea to remove this data as soon as possible to ensure that the repositories you are working with are lean and clean. There are data deduplication tools available that are primarily used for backup and restore operations. However, you can use them to remove duplicate data from your repositories. Apart from that, classifying your data will make the process of removing duplicate data much easier. This is because the duplicate files will be classified under the same label.
In a nutshell, companies can manage data sprawl through the following ways:
- Keeping track of your compliance regulated data and the systems it originates from. Once you export data from those systems, keep track of all the destinations it is getting to and all the people accessing it.
- Take control of your data (old and new) by moving it to the cloud. No matter how many devices your employees use to create data, it’s fine as long as it all ends up in the same place. Plus, cloud data is much easier to access since you don’t have to physically use a different device.
- Employees need to know which services they should harness. They should also know which devices they should use for fulfilling their daily duties. This is to reduce fragmentation in this area.
- Finally, implementing a proper content lifecycle management is a very good idea in combating data sprawl. Simply put, the files that you are working on currently should be accessible to anyone working on them. Then, after the project is complete, keep the files for several months in case of future use. After a few months, you can safely archive them to a cold storage system.
Data Sprawl poses as a real risk to many businesses(startups and already existing ones). It makes management of data ineffective. However, employing the right techniques for managing data sprawl can help save you valuable time and money.
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