The digital age has seen the creation and explosion of a major new market: personal data. Today, this drives incredible swathes of modern commerce, and companies have rapidly pivoted toward data-focused transformations. However, despite the commercial benefits presented by widespread data collection, there are significant downsides that too often go overlooked. Data discovery and classification is now a vital tool for battling database sprawl.
Contents
The More the Messier: How Data Came to Rule the World
The reams of data collected by companies are mind-boggling. Purely on a personal level, there are scripts and channels that aim to collect, parse and analyze personally identifiable information (PII) such as gender, age and social security number. These statistics mean businesses can get ever closer to their audience, while non-personal information shows what device and cookies you may own and have. This links to the second major category of personal data: engagement.
Outside of you as a person, companies like to know how you interact with their products, services, and online presence. Emails, social media posts, marketing campaigns; they all fall into the company’s broader scope of how consumers travel down the purchase funnel, and engage with the brand. The other side of this engagement coin is behavioral data, covering purchase histories and how you use the product or service. Finally, attitudinal data allows for the quantitative measurement of customer satisfaction, pointing a business toward particular likes and dislikes.
All of these reels of personal data occur throughout each individual customer’s journey. The goal is to take this data and feed it back into each business process. Complicating the mix even further is the demand for this information to be as up to date as possible, leading to continuously-changing streams of incoming data. Take location-based advertising: tracking technologies such as IP addresses of your device and those it connects with helps build a data profile that accurately tracks where you’re based. This geospatial data enrichment process allows for hyper-personalized advertisement, indicating that consumer databases are more than the sum of their parts. On the other side of the sales funnel, customer service records are fed directly back into the sales and support departments, incorporating widespread feedback throughout the relevant areas of a business.
Big Data has become so profitable that entire industries have popped up surrounding the collection and reselling of personal data to third-party sources. After all, data now inherently holds value – and that’s just describing the more well-known field of consumer data. One of the largest areas of growth within data collection at the moment is actually within operation metrics. Driven largely by Internet of Things (IoT) devices, industry giants are focusing with increasing drive on infrastructural time series data. The collection of huge amounts of varying data over time is further being enabled by industry-specific databases, as traditional data storage and plotting is simply not built for the scale and requirements of modern data collection.
Whether the data you’re collecting is for marketing and sales, or for streamlining industrial processes, the fact remains that even scalable cloud-based databases are straining at the seams. Companies are losing track of the data they own, and placing consumers themselves at risk of data breaches.
What You Don’t Know Can Hurt You
Forrester Reacher reported in 2022 that 58% of data security incidents occur thanks to insider threats. Whether that’s a hijacked account, or an employee mistakenly causing a data breach, the outside attacker turns into an internal problem. These attacks see legitimate and suitably authorized user accounts – assigned to internal employees – become leveraged by an attacker. Most of these attacks are opportunistic, with malicious actors simply breaking in and grabbing any data within immediate reach. More sophisticated attacks, however, will remain on the system far longer than anticipated, regularly returning and siphoning off the info they’re looking for.
The primary way in for these threat actors is via credentials. Whether gleaned from advanced phishing attacks, or simply brute-forced by dumb bots, credential management is a major component of database security. Furthermore, the statistics surrounding data theft are concerning: almost three quarters of stolen data is highly sensitive, personally identifiable data. Put this into the wider context of 54% of companies not knowing where their data is stored, and 65% claiming that they’ve simply collected too much to categorize and analyze it – and it’s clear that many companies have chosen data greed over customer protection.
Even outside the context of user protection, the limited data visibility plaguing industries also hinders the company’s ability to take data-driven opportunities. Every component of analytics and security requires companies to
How To Break Away From Breach-Ready Databases
Sprawling databases are ready to be set ablaze by malicious actors. Instead of waiting to see flames, there are numerous actions to take now to protect both employees and customers.
Firstly, the identification of sensitive data within a database needs to be top priority. In massive databases, this requires an automated and highly precise process. With a top-notch data identification and classification provider, it becomes possible to categorize even large scale databases. From there, the IAM systems become a lot easier to manage, with access monitored throughout just the sensitive data. By tailoring every account to the principle of least privilege, users are limited only to the data required for their area of work. This needs to be a constant process as employees change roles and leave organizations entirely. Identifying who precisely has access to what can greatly help prevent – and reduce the impact of – data breaches.
The most critical time period surrounding a potential breach is the time between when an attacker enters – and when it’s detected. The shorter this time period, the more data can be protected. Reducing this turnaround time makes you a far less appealing target – and drastically cuts the amount the company may need to pay in damages. The best data security solutions allow for the detection and termination of policy-violating behavior before the attacker can even exfiltrate it. For instance, by monitoring where your data is, you can also identify behaviors that attempt to access hundreds of files in a short period of time – and those that are trying to move those files elsewhere. Context-rich alert systems identify potential attackers, detect threats, and intelligently alert your security team to concerning behavior.
