With a new century in full swing and predictions showing that in the next five years Global data will increase by around 80 percent, from 33 Zetabytes in 2018 to 175 Zetabytes in 2025, it is more relevant than ever that organizations look at not only how to manage their data in a secure way, but also how to exploit this rich source for potential revenue generation and business advancement.
Big Data technologies such as Hadoop and Teradata are quickly being adopted to help facilitate the storage and access to all this newly created data, enabling enterprises to gather intelligent insights about customers, operations, and competitors through analytics. But, broadly enabling data access carries risks. How safe is your data in light of today’s modern threat landscape?
Among the massive volumes of data captured by enterprises is sensitive information that, if stolen, could result in harmful consequences to the consumers affected and to the business breached. In the age of Big Data, this risk exposure is exponentially more dangerous. With enterprises capturing personal information, intellectual property, health information, and more new classes of sensitive data than ever before, information in a data lake can form toxic combinations that reveal identity. Even data that isn’t apparently sensitive at face value could be combined with other disparate pieces of data to reveal personally identifiable information—and if stolen, could be used for fraud and trigger penalties due to privacy legislation.
Big Data Trends
The Big Data at the heart of the modern enterprise is growing massively each day. Gartner expects that we will reach 20 billion devices in 2020 and through these devices, users are generating so much digital content that the entire digital universe is doubling every two years.
At the same time, Big Data is becoming a major priority for Chief Information Security Officers (CISOs). In a recent IDG survey, CISOs voted “Big Data” the number one target for increased security expenditures to prevent data breaches. But the increased security scrutiny is also having unintended consequences. Forrester reported that one of every two employees that request access to Big Data are denied for security reasons, hurting a company’s ability to gain competitive insights from the data.
Traditional IT Security Can’t Protect Big Data
As data flows throughout the enterprise, from the edge of the network where it is created (through thousands of applications and systems) all the way to storage in the cloud or on-premises systems, data must be protected—at-rest, in-motion, and in-use. But traditional system and perimeter IT security can’t achieve this, except in silos, leaving security gaps in the modern hybrid enterprise.
Luckily, data-centric security gives enterprises an effective option for protecting data within a Big Data environment. Key features of data-centric security include:
- Protection for data everywhere it goes
- Protection that scales with Hadoop
- Protection enabling data usability for analytics
- Protection for sharing data with third parties
That means data is always protected (in motion, in-use, or at-rest) and security policy travels with the data. What’s more, Format Preserving Encryption and Tokenization preserve the usability of data for analytics, applications, and business processes—unlocking the potential of your Big Data!
To learn more, visit our Voltage SecureData Enterprise website or see us at the Chief Data Officer Exchange in London, 24–25 March 2020.
1: The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things, IDC
2: “Gartner Says 8.4 Billion Connected “Things” Will Be in Use in 2017, Up 31 Percent From 2016”, Gartner, Feb. 2017
3: 2017 Security Priorities, survey of Chief Security Officers, IDG, 2017
4: Open Your Analytics Architecture To Keep Up With The Speed Of Business, Forrester and HPE, Aug. 2016
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