The Classify360 Approach: Identify
Identify, normalize, and organize sensitive data, uncovering opportunities to accelerate desired business outcomes.
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Identify
Classify360 identifies and collects all data from integrated on-premises and cloud sources across the business.
Solid Data Governance Foundations
GAIN IMMEDIATE INSIGHT
Classify360 gives deep insight into structured and unstructured data that is produced daily. Uncover hidden opportunities to yield bigger business wins more quickly.
A SCALABLE SOLUTION
Classify360 can be utilized with any amount of data from gigabytes to petabytes. To put it into perspective: 1 petabyte is equal to 20 million four-drawer filing cabinets filled with text.
COMPREHENSIVE NORMALIZATION AND ORGANIZATION
Run all enterprise data, residing within on-prem legacy & new systems and cloud-based & hybrid storage, regardless of file type or origin. Easily analyze data across all business units, departments, and locations.
Data Normalization
Classify360 processes all data types, using database organization to create a level playing field for the analysis of all file types at once.
Quick Dashboard View
Leverage the dashboard for a complete snapshot of data repositories across the entire enterprise.
Prioritize the Risk
Uncovering various types of data gives a better understanding of what files your organization is hoarding and can dispose of. Prioritize high-risk data for immediate action.
Content-Level Scan Without Copies
Classify360 combines an inverted index and a relational database to enable Boolean searches, models, and supervises analysis of unclassified data. The inverted index provides fast, enterprise-level search while the relational database provides secure storage of key metadata to provide quick user experiences, e.g. file name or size.
Inverted Index
A traditional index might link an ordered set of items to the terms they contain, often words or other meaningful character patterns, like a serial number. An inverted index structures data as an ordered set of terms first, then links them to the items in which they are found.
An advantage of using an inverted index for compliance purposes is the inherent security it provides. Classify360’s inverted index maps terms to items; Classify360 never stores text as a field. It does not make a copy. This eliminates the possibility of malicious reproduction, maintains a secure chain of custody, and eliminates the risk and cost associated with duplicative data.
Frequently Asked Questions
Data governance is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage. Effective data governance ensures that data is consistent and trustworthy and doesn’t get misused.
Data normalization is the organization of data to appear similar across all records and fields (so you can compare apples to apples, not apples to oranges). The data normalization process structures a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity.
An effective data governance strategy protects both your data and your organization throughout the entire data lifecycle by identifying, addressing, and continuously mitigating data risk. Data breaches are a matter of “if” and not “when,” and data privacy regulations are now a common practice worldwide. Relying on accurate, up-to-date data analytics enables organizations to optimize operations and drive intelligent decision making practices.
An inverted index is a database index storing a mapping from content, such as words or numbers, to its locations in a table, or in a document or a set of documents. An inverted index structures data as an ordered set of terms first, then links them to the items in which they are found.
Yes! Classify360’s inverted index maps terms to items, meaning the software is never storing text as a field. This eliminates the possibility that someone with malicious intent could reproduce a file’s content from the information in the index.
