Data Ecosystem Evolution Platform (DEEP): Automated Solution for Data Security

According to the very recent update by, ”T-Mobile breach hits 53 million customers”. T-Mobile is reported to have been charged with two class-action lawsuits filed by its customers, accusing the company of violating the California Consumer Privacy Act.

The data breach is believed to include names, addresses, dates of births, phone numbers, social security numbers, and driver’s licenses, even though T-Mobile has denied the claims that the breach included information on SSN and driver’s license. T-Mobile has also denied any breach of financial information like credit or debit card details. Regardless of what the company admits to, that number, $53 million, is so astronomical that it compels us to highlight the importance of the foundational components for detecting and keeping private data protected.

Every day data is being used for various purposes. It is being copied, transformed, and stored in multiple locations across the organization. Without an automated solution, it is challenging and sometimes impossible to locate where sensitive data exists. Data protection is not just about solving the problem of having access to data, the complications get worse when we don’t even know where all the sensitive data exists within a file or database. So how can we protect something if we don’t know where to find it?

An Automated Solution Inclusive of Data Classification and Metadata Management: According to IDC, International Data Corporation, (as published by, data creation will swell to a total of 163 zettabytes (ZB) by 2025 – a ten-fold increase in today’s numbers, according to a new whitepaper from IDC. And that means individuals and organizations have to be prepared with the necessary tools to prevent or tackle the upsurge in a data breach.

Metadata Management is managing information about data. Businesses need to record data movements through metadata discovery on a regular basis. With the fast-growing impacts of data in various business areas, especially risk and finance divisions, business stakeholders have acknowledged the need for metadata management with a dynamic approach. Metadata is the summary of your data that is used to classify, assemble, label, and understand data, making it easily searchable. Metadata Management provides vital details about an organization’s data assets:

  • What is the source of the data?
  • What type of data, is it sensitive or confidential?
  • Why is it relevant?
  • Where is it located?
  • How is the data being changed or modified?
  • Who has access to the data?

According to 2019 data breach predictions by SecurityMetrics, “the number of victims in each reported breach is not cumulative, these are each individual incidences, bringing the total between these three breaches to upwards of 1.4 billion victims.”

Data Classification can optimize data security and data protection programs. Data has to be classified based on its susceptibility and the impacts on an organization if that data is compromised. Data classification not only empowers you in securing your organization’s information but also provides you with the opportunity to fully understand how relevant is your data and who has access to it.

The Global IDs Data Ecosystem Evolution Platform (DEEP) automates data governance by building a comprehensive knowledge of where data is, what it is, and how it flows, gaining control of the data from the bottom up. The DEEP software includes metadata management and data classification, that provides an enterprise-level platform to create a solid foundation to protect your data:

  • Finding the Relevant Data
  • Accurate Logical Classification at Scale with Machine Learning
  • A Searchable Business Data Map for the Enterprise

The growth of enterprise data, rising regulatory pressures, and the requirement to obtain more value from data have made metadata indispensable for data management, compliance, and business intelligence. Global IDs DEEP platform helps to identify relevant data. Its metadata organizes and classifies data and makes its value attainable.

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