Synthesized is the all in-one DataOps platform enabling secure data sharing and collaboration across internal groups, remote teams and external partners.
Quantity doesn’t always mean quality when it comes to data. With our data profiling tool, you can evaluate the quality of your data and determine how much data is needed to achieve your project aims. Monitor your data changes over time and get alerted of sudden changes to your data streams.
When data is expensive and time consuming to collect, projects are in an early stage or you simply do not have sufficient data to test, you risk building Data Science projects with small datasets, lacking generalization and producing overfit on training datasets.
Synthesized is able to learn from small datasets, and generate new datasets to augment them. You get instant access to high volumes of representative data for training and analysis—simplifying data procurement and letting you charge ahead at full speed on your data projects.
Typically some attributes in a production dataset may have underrepresented classes—for instance, fraudsters and delinquents in credit data. Scenarios like these can lead to unexpected outcomes, such as underperforming classifiers and reduced testing coverage.
With Synthesized, you can alter marginal distributions as desired, and rebalance datasets by generating realistic samples for the underrepresented classes. With Data Rebalancing, improve performance in unbalanced datasets and ensure proper behaviour across all datasets.
Using production databases (or replicas) for testing requires stringent permissions management and data obfuscation without the guarantee of your data fully covering your test cases.
Our Database Generation tool allows you to generate a privacy compliant version of your database with increased coverage—in minutes.
Detect potentially sensitive groups within your datasets — across attributes such as age, gender, race — and quantify how different the target variable distribution is for each of these sensitive groups with respect to the rest of the population.
Manipulate the dataset by generating new samples and undersampling, so that the sensitive groups’ target distribution is similar to the overall dataset.
Synthesized outperforms traditional privacy compliance methods, while maintaining high data quality. Most data platforms redact PII, but Synthesized is different. By design, the platform satisfies all legal and compliance constraints—ensuring you are not falling afoul of regulatory restrictions or risking damage to your brand reputation.
Generate multiple privacy preserving and diverse data scenarios to evaluate the performance of a system in a broad range of applications. Create an unlimited number of high-quality data points that do not have the typical problems of original data (missing values, outliers, biases) and don’t contain sensitive information—allowing easy sharing and utilization of sensitive data.
Sharing data with third-parties creates data leakage and governance risks. Synthesized Data Clean Rooms empower secure data sharing and collaboration across internal groups, remote teams and partners to increase productivity. Data Clean Rooms are pristine isolated environments ready for use within minutes without the risk. Risk-free of any security breaches and without any delays.
The platform supports all popular data-sources, including both relational data sources (Postgres, MySQL, Oracle, DB2, SAP-Hana, etc) and non-relational (MongoDB, HDFS, S3, etc). No more building integration tools for each datasource.
Many teams store their datasets in CSV files or different data-sources and have to tailor permissions for each data consumer on a case by case basis. Synthesized organizes all data projects in one place, regardless of the source and use case, improving productivity and efficiency. User permissions, data sharing, and audits can be easily managed within the platform.