Protection with Performance
Don’t let your protection methods impact performance. From dynamic data masking, to format-preserving encryption, to Vaultless Tokenization or a combination of each, Protegrity solutions are highly scalable, flexible and powerful protection methods for structured and semi-structured data.
All the protection, none of the performance drawbacks.
The 4 Vs of Data
Data has little value for your organization without parameters to characterize the quality of what you have. Four qualities — volume, variety, veracity and velocity — have been determined as necessary guidance for obtaining results from Big Data and improving business performance. Balancing these characteristics are keys to big data management.
01
VOLUME
Within the context of Big Data, the amount of data in any given collection exceeds terabytes and is measured in petabytes. This characteristic is considered the first, or base, characteristic in big data. As technology expands, the amount of volume is expected to grow along with it. The typical enterprise is now dealing with an eye-watering amount of sensitive data — PII, PHI, and more.
02
VELOCITY
Velocity is a two-part characteristic of big data. It refers to the speed at which data is generated, as well as how quickly that data moves. An organization using big data will have not only a large volume of data, but a continuous flow from multiple sources, whether it is generated or consumed via migration. Whatever the source, the data must be consumed and analyzed with speed, sometimes in real time.
03
VARIETY
Variety refers to the diversity of data types. A big data collection will typically consume data from a number of different sources, whether the data is internal or external. The challenge with big data variety is determining how to standardize or distribute this data. It will not all fit neatly into one container when first consumed, but all of it is necessary to obtain the layers of multiplicity that will be useful.
04
VERACITY
Veracity refers to the completeness, quality, or accuracy of the data. Is the data clean? Will it promote business performance? More specifically, when it comes to the accuracy of big data, it’s not just the quality of the data itself but how trustworthy the data source, type, and processing of it is. This is confirmed via sampling and tracing the data back to the source of origin. Removing factors such as abnormalities or inconsistencies, duplication, and volatility are just a few aspects that factor into improving the accuracy of big data.
Accelerating Threat Detection
Ensuring the authorized parties are accessing the right data at the right time. The Protegrity Platform supplements data protection with comprehensive audit logging, allowing businesses to monitor who has accessed the data, what data, where, and when. Evidence-based audit logging provided through the Protegrity platform protects your enterprise and allows your data functions to meet regulatory compliance requirements, thereby improving business performance. Protegrity provides security analytics that can alert and highlight suspect behavior for incident response.
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