Synthetic data for
advanced analytics
Are you tired of your most valuable behavioral data assets being locked away by privacy regulations? Put all your data to work for data-driven decision support and trend predictions while fully complying with GDPR and CCPA!
Challenges
- Data is a critical business asset empowering companies to stay competitive.
- According to McKinsey, 86% of executives say their organizations have been at best only somewhat effective at meeting the primary objective of their data and analytics programs.
- Timely access to high-quality data across departments and subsidiaries is a major reason behind an organization’s inability to turn on data-driven capabilities.
- Only 15-20% of customers consent to using their data for analytics, the rest of data and the insights contained are locked away.
- Due to privacy reasons, sensitive data is often off-limits both for in-house data science teams and for external analytics vendors. Their contributions are crucial for driving innovation and customer-centricity further.
Solution
Synthetic data is exempt from privacy regulations, enabling data scientists to see the big picture by accessing privacy-compliant, statistically identical synthetic repositories seamlessly. Using MOSTLY AI’s synthetic data platform, you can quickly and easily generate granular, accurate, as-good-as-real synthetic copies of your raw data. Make use of all of your data assets, and share synthetic copies with external analytics providers, train accurate AI models with large batches of realistic synthetic data, and use sophisticated analytic tools to gain brand new insights.
Why MOSTLY AI?
- MOSTLY AI offers unparalleled data accuracy and privacy protection.
- Our algorithm learns your sensitive datasets’ statistical properties, preserving their insights and trends.
- Easy to integrate into existing enterprise environments.
- Flexibly upload various data types, including behavioral data and transactional tables.
- The resulting synthetic datasets come with automated QA reports, including quality and privacy checks.
- You can quickly and safely boost the accuracy of your machine learning and other analytics models with fully anonymous synthetic data generated with a trusted, third-party validated approach.
Proof
A large multinational telecom provider conducted an HR analysis of more than 90,000 employees using synthetic data. Due to legal regulations, operating companies couldn’t touch employees’ sensitive, raw data. Using the synthetic version of the data, they could identify patterns leading to employee churn, optimize HR processes, and improve talent acquisition and retention rates.
