UnBiasIt Data Stack
Your Comprehensive Solution for Bias-Free Data Lifecycle Management
Effective Data Lifecycle Management [DLM] is essential for ensuring data quality, compliance, and security throughout the data's lifecycle. It helps organizations make informed decisions based on accurate and trustworthy data.
Solving Ai Data Challenges with Bias-Free DLM
UnBiasIt is a complete data lifecycle management solution that utilizes proprietary data management and compliance solutions to eliminate inherent bias and misconduct throughout an organization. Our approach transforms disorganized data into a resource that can be easily and accurately utilized for critical information governance. As the global market for Ai and machine learning grows, our solution is positioned to solve the growing bias problem in these technologies.
UnBiasIt provides unified and bias-free data by exposing inherent risk in data compromised by bias.
In the information age, data is king, but it has now increased beyond an organization’s capacity to manage or harness its inherent power and value. Much of this data is considered dark data, meaning that an organization does not know the nature or sensitivity of this content. An organization’s current and legacy data pose significant risk associated with compliance and social challenges, especially bias.
The Overwhelming Data Problem
In addition to being a vital competitive resource, an organization’s data is now also essential for government compliance, industry standards, litigation, and social response. A survey of 1300 technology executives commissioned by Splunk reported that more than 75% of the executives believed 60% or more of their data was dark. This unknown data puts an organization at enormous risk, and this distended data is metastasizing throughout an organization’s applications and hemorrhaging in its data centers.
The Bias Problem
“Biases are an uncomfortable truth. No one wants to think that they’re potentially discriminating against someone else. But as a business problem, bias is very real, and so are the consequences.”
- Jeff Caitlin, Forbes
Organizations often don’t recognize that instances of bias exist in their current communications and historical data stores, and more importantly, don’t recognize how damaging this unidentified bias could be … lawsuits, damaging PR, sanctions, boycotts, sabotage, fines, staff demoralization, recruiting issues …
Bias in Machine Learning
Machine learning applications are susceptible to bias, resulting in poor decision-making and unethical Ai. Biased algorithms can perpetuate and amplify existing societal biases, such as gender and racial stereotypes, leading to discriminatory practices.
Detect and clean unstructured and dark data from virtually any repository.
With Ai Data Detect, UnBiasIt delivers a purpose-built solution to interrogate petabyte-scale unstructured data volumes to identify instances of bias. UnBiasIt Ai Data Detect profiles data to identify several sensitive data, including (but not limited to) race, ethnicity, gender, and other forms of PII, PHI, and PCI. Not only will this enable enterprises to identify potential dark data risks, but the built-in workflows facilitate the movement of data to secure repositories, preservation in an archive, upstream review platforms, and much more.
How It Works
Data Connect delivers universal data interoperability and allows you to bring all of your corporate data online through a powerful modular data access and transformation framework, lighting up accessibility and visibility to data siloed within all of your platforms, storage infrastructure, and enterprise applications. It can be used for cloud migrations, data transformation, or as an instrument for application retirement.
AI Data Detect
AI Data Detect delivers cutting-edge data analytics and deep insight across all of the data held within the entire corporate data estate. Built on a powerful analytics engine, a super scalable architecture, and a rich, intuitive interface, it provides democratized, self-service analytics tooling that almost anyone can use within an organization. It builds on the absolute connectivity provided by Connect to allow any data source, no matter how large or complex, to be mapped, modeled, and controlled.
New! The UnBiasIt AI Data Detect Calculator
With the UnBiasIt AI Data Detect Calculator, you can unlock cost savings and improve the fairness of your data analysis. By inputting your storage costs and data across different tiers, the calculator can demonstrate the reduction in total cost of ownership by utilizing different phases of AI Data Detect. Additionally, the AI Data Detect technology can identify possible instances of bias in the data, allowing for more accurate and fair analysis.
The Calculator also utilizes ChatGPT to prepare executive summaries and reports tailored to your organization's needs, providing suggested next steps to optimize your data management strategy. Don't let hidden biases and high storage costs hold you back, try the UnBiasIt AI Data Detect Calculator today.
The Advanced Archive™
The Advanced Archive™ capabilities allow all regulated, litigated or business-critical data, communications, or documents to be preserved in a highly compliant enterprise-scale data archiving platform. This can be deployed to any infrastructure or cloud platform, including hybrid deployment, and provides a powerful suite of end-user access and search tools as well as an advanced e-discovery application for rapid case-driven enterprise search or litigation support.
Unified Data Optic
The Unified Data Optic is a data governance solution that enables organizations to create a unified map of their data, automate and manage metadata from hybrid sources, classify data using built-in and custom classifiers and sensitivity labels, label sensitive data consistently across different systems, easily integrate all data catalogs and systems, improve data quality, and mitigate risks.
The Missing Method in M&A:
Due Diligence Solutions
Powered by UnBiasIt’s Data Stack, UnBiasIt delivers the industry-leading Data Due Diligence Toolkit to implement formal procedures for data diligence to provide a complete picture of a company’s data and data-related capabilities while also exposing inherent risk in the data compromised by bias.