In the rapidly expanding landscape of Internet-based data analytic services, companies across all industries with a significant online presence have faced or will face a data breach resulting from their collection and use of Big Data. As more consumer information is digitized and collected by companies for data analytics, the potential for cyberattacks also increases. While businesses often find Big Data analytics valuable for research and marketing, most organizations do not have the security assets needed to keep such data safe. As can be imagined, large quantities of consolidated data can be extremely tempting for cybercriminals, especially when such data may contain a company’s proprietary information or customers’ personal and/or financial information. Big Data security breaches can result in serious legal consequences and reputational damage for companies, often more severe than those caused by breaches of traditional data.
Big Data Has Big Security Challenges
Big Data has several unique security challenges, of which companies unfamiliar with the complexities of Big Data analytics may not be aware. Variety, volume and velocity are the three primary terms used to characterize Big Data, and each individually contributes to the security challenges native to Big Data analytics and must be considered equally.
The first term, variety, defines the multiple classes or data types captured across a company’s given enterprise. Variety is quickly becoming the single biggest driver of investments in Big Data. At any given time, a company may be collecting and/or storing data from multiple business areas (e.g., customer data, employee personal information, intellectual property) in a variety of formats. To adequately combat threat actors targeting valuable Big Data repositories, companies must fully understand all data types collected and used in their business before engaging in or contracting for Big Data service. Companies must also balance their desire to rapidly extract and analyze Big Data with the need to adequately secure such data. Continue Reading