NEWS: Congruity360 Pioneers Risk-Free “Smart Data,” Lowers Enterprise Storage & Backup Costs While Mitigating Risk Exposure

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29 Minutes to Actionable ‘Instant Insights’ on your Data

A 29-minute call is the first step to getting an actionable view into the makeup of your unstructured, dark data highlighting areas for prioritization like:

Stale and Aged data outside of retention requirements

Exposed Sensitive data that is creating risk for the organization

Redundant and Trivial data that holds no business value

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Evidence Uncovered by Instant Insights on Unstructured Data Sets

Graphic showing 54% Data Aged Past Retention

Data Aged Past Retention

54% of the data analyzed in a data set was aged and fell outside of the organization’s defined retention policies. Automation of remediation actions was recommended such as deletion or moving to lower tier storage or archive.

Graphic showing 839k pieces of Data with Risk Indicators

Data with Risk Indicators

839,000 files within a data set contained risk indicators – many of these files had permissions set to “everyone”. Full content-level analysis and review was recommended as a next step which typically reveals 5-10x more risk and a true understanding of the full risk profile.

Graphic showing 19% Redundant Data

Redundant Data

1.2 million files, 19% of a data set, were redundant and an additional 105,000 files were identified as trivial. These files add unnecessary cost and risk to the business and provide no business value. ROT remediation was recommended to remove this non-business critical data.

See How These Clients Leveraged Data Insights to Make their Business Stronger

Unstructured Data Insights Informed Priorities for CIO

Instant Insights delivers an evidence package to a CIO shedding light on the organization’s unstructured, dark data and pinpointing areas to prioritize for cost savings and risk exposure remediation.

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Enterprise Client Reduced Risk and Storage Costs

Following a breach, this Congruity360 client leveraged advanced data insights and classification to clean up historical data, remediate risk, and launch an ongoing, automated data management strategy.

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