Big data technology is becoming an increasingly important tool for businesses to help them gain insights and make better decisions. As the amount of data being collected increases, it’s essential that organizations also pay attention to their big data security protocols. Implementing active directory management tools is one great way to ensure your big data remains secure.
Active directory solutions provide a centralized platform from which administrators can manage user access across different applications and databases. Administrators can use the platform for identity management, authorization and authentication, as well as reporting and auditing functions. This means tight control over who has access to sensitive information within the organization’s network, providing greater protection against malicious attacks or unauthorized access. It also allows for easy monitoring of changes made in the system so that any suspicious activity can be quickly identified and addressed before any damage is done.
Big data is not just a passing trend or a boardroom buzzword anymore. It’s here to stay, and the benefits can be significant and far-reaching.
However, with the collection of all of this data comes the need to store and protect it. Such large repositories of data, especially when it contains sensitive information about customers and your business, are attractive targets for cyber-criminals, and the results of a major breach devastating on a number of levels.
And breaches are becoming all too common, to the point where it’s not so much a question of if a company will experience a breach, but when there will be a breach and how devastating it will be.
Because the risk of a data breach is so high, and the potential fallout is so significant, it’s time for companies to get serious about big data security.
Challenges to Data Security
For many companies, the issue isn’t necessarily that they need to secure their big data, but that they face some major challenges in doing so. Among the challenges that many companies face in securing data include:
Skills gaps. Cybersecurity, in general, is experiencing a shortage of skilled workers, and the gap for those with experience in managing big data is even wider. Many businesses do not have data scientists or analysts on staff, and thus have difficulties identifying and correcting all of the security holes and weaknesses.
Access controls aren’t always managed well. For many companies, it’s all but impossible to parse out big data to ensure security and confidentiality among all levels of the company. In addition, data encryption protocols for big data can become outdated quickly, creating issues with access.
Audit limitations. Auditing the data collected for security risks is difficult or impossible due to the amount of data being collected and limitations to the technology.
Current security protocols weren’t designed for big data. Many of the platforms that companies use to work with big data were not designed to secure that data, and thus do not offer built-in security features like encryption. Companies are then forced to build their own security features into applications, something that can be expensive, time consuming, or impossible due to skill limitations.
Big data is diverse. Big data often means collecting information from a wide variety of sources, all of which require their own security protocols.
These are just a few of the challenges that businesses face when it comes to securing big data. However, just because there are challenges doesn’t mean that it’s impossible.
Improving Your Big Data Security
Given the challenges that are inherent in securing big data, it’s imperative that you develop a plan and invest in advanced tools for data security. As big data becomes a vital part of doing business, you can no longer afford to sit back and rely on the same security measures you have always used.
Big data security relies on developing a strategy that recognizes that this data is different than your other data, and thus needs different protection. Some of the tactics being put to use include:
Focusing on application security rather than endpoint security. As previously mentioned, most big data technologies weren’t originally designed with an eye toward security. Be sure that you are using secure versions of all software, particularly open source software.
Consistently maintaining, monitoring, and analyzing audit logs. Upgrading audit logging technologies to better manage big data is a must. Security engineers should be charged with examining and monitoring logs, and that this task is handled consistently across the entire organization.
Establishing stronger access controls. Access to big data must be granted via managed accounts that follow password best practices and deactivate inactive accounts. Monitor who has access to the data and when they access it. If someone does not need access to a data cluster, they should not have it.
Securing hardware and software. Manage all servers used for big data to ensure their security. Install updates and patches as needed and limit administrator privileges to only those who need it.
The most important point to remember when it comes to protecting big data is that it needs to be handled differently and that you need to invest resources in protection or risk serious consequences. Criminals are not going to stop attacking your business, so you need to be on the defensive and proactively protect your data.