What’s new in MOSTLY AI

Due to some incorrect assignments of foreign keys in specific cases, we disabled the auto-assignment of foreign keys when you upload subject and linked table files.

MOSTLY AI now discards rows with duplicate primary keys if you have such in your dataset.

Fixed the issue where the Save button remained inactive after you edited a column with a Smart select relationship.

Fixed the issue that kept the Delete button inactive in the Catalogs tab.

Fixed the issue that job fails due to too few samples being provided by the User.

Fixed the issue of having Nulls in a Text column.

Generates synthetic data strictly within the business rules captured in the data.

Generates synthetic data that adheres less strictly to the business rules captured in the data.

Generates synthetic data skewed toward the outliers of the detected distributions.

PK and FK relationships are not correctly set for file based jobs.

Fixed the issue that catalogs with multiple context foreign keys may not complete synthetic data generation.

Fixed the issue that batch sizes greater than 4096 crashes synthetic data generation.

Fixed the issue that in database synthesization jobs, tables whose names start with an _ fail to be read.

Fixed the issue of misalignment of data partitions occurring when the subject table is big and the linked table is small.

For Ad hoc jobs, the default rare category protection method is now constant instead of sample.

Fixed the issue that tables with multiple foreign keys may crash when the relationships have been edited in the data catalog.

Fixed the issue that users cannot upload tables that are partitioned over multiple files.

Fixed the issue that free version users see Local Server as a data connector option while unavailable to them.

Fixed this issue that Mock is selectable as an encoding type.

Fixed the issue that the encoding type is not saved when a linked table column is set to ITT.

Fixed the issue that in Ad Hoc jobs, column settings are not persisted after saving when switching tabs.

In Ad hoc jobs and Cloud storage data catalogs, the Edit relationships drawer is automatically shown to the user if the foreign key is not found.

Certain database relationships result in two context foreign keys to the same referenced table, resulting in an error during synthesization.

When creating a data connector, the schema field is marked as mandatory for databases that don’t require it.

For Ad hoc jobs and cloud storage catalogs, the linked table’s first column is automatically selected as the foreign key.

When a table has an unexpected character, the error message doesn’t mention the issue as such, nor does it state where it occurs.

If there is only one referring table, it doesn’t show up in the Primary key and referring tables section.

The column settings drawer shows the incorrect generation method for Smart Select and context foreign keys.

For users of the free version, Local storage is no longer an option when creating data catalogs.

Missing values in the numerical columns of Parquet files are not correctly read.

The Smart Select algorithm throws an error if the referring table is empty.

The database data connector throws an error if there are empty tables.

Tables are not shown in alphabetical order in the 'Database contents' section of the database table selection step.

The job settings' column details of uploaded Parquet files show Auto-detect instead of encoding types.

Parquet files cannot be used as a seed for the Generate more data feature.

When starting an Ad hoc job, users can upload 2 different files as a subject table.

Reference tables' primary keys are not copied but generated.

QA report generation fails when analyzing database datetime columns that contain values in an unknown format.

Sequence lengths are incorrectly calculated in an edge case scenario.

When creating or modifying a data connector, the Test connection button doesn’t check whether the specified schema can be accessed.

Whitespaces in the header row of CSV files cause issues during synthesization.

QA report generation fails when synthesizing Parquet files.

Incorrect processing of scientific notation in CSV files.

Certain datetime ranges are incorrectly processed as strings.

Restrictive rules causing the QA report to fail in certain edge cases.

Long warning messages within the app’s architecture causes it to crash.

QA report fails when a column is configured as 'mock data'.

Incremental timestamps in time-series data may generate inconsistent synthetic data when configured as ITT.

QA report fails when a numerical column is completely empty.

Synthesization fails if the linked table’s entries are not linked to the subjects in the subject table.

When synthesizing databases, the data types of the original schema are now respected, regardless of encoding type.

Fixed the issue that catalogs with multiple context foreign keys may not complete synthetic data generation.

Fixed the issue that batch sizes greater than 4096 crashes synthetic data generation.

Fixed the issue that in database synthesization jobs, tables whose names start with an _ fail to be read.

Fixed the issue of misalignment of data partitions occurring when the subject table is big and the linked table is small.

For Ad hoc jobs, the default rare category protection method is now constant instead of sample.

Fixed the issue that tables with multiple foreign keys may crash when the relationships have been edited in the data catalog.

Fixed the issue that users cannot upload tables that are partitioned over multiple files.

Fixed the issue that free version users see Local Server as a data connector option while unavailable to them.

Fixed this issue that Mock is selectable as an encoding type.

Fixed the issue that the encoding type is not saved when a linked table column is set to ITT.

Fixed the issue that in Ad Hoc jobs, column settings are not persisted after saving when switching tabs.

In Ad hoc jobs and Cloud storage data catalogs, the Edit relationships drawer is automatically shown to the user if the foreign key is not found.

When running a job, the View training logs is now visible by epoch 1 and shows a spinner to indicate that the training is being canceled.

The QA report for linked tables no longer displays the linked table name along with the context table name.

When adding new foreign keys with the relationships drawer, if there are more than 1 parent tables without primary keys, the error message shows all these tables instead of only the first one.

Certain database relationships result in two context foreign keys to the same referenced table, resulting in an error during synthesization.

When creating a data connector, the schema field is marked as mandatory for databases that don’t require it.

For Ad hoc jobs and cloud storage catalogs, the linked table’s first column is automatically selected as the foreign key.

When a table has an unexpected character, the error message doesn’t mention the issue as such, nor does it state where it occurs.

If there is only one referring table, it doesn’t show up in the Primary key and referring tables section.

The column settings drawer shows the incorrect generation method for Smart Select and context foreign keys.

For users of the free version, Local storage is no longer an option when creating data catalogs.

Missing values in the numerical columns of Parquet files are not correctly read.

The Smart Select algorithm throws an error if the referring table is empty.

The database data connector throws an error if there are empty tables.

Tables are not shown in alphabetical order in the 'Database contents' section of the database table selection step.

The job settings' column details of uploaded Parquet files show Auto-detect instead of encoding types.

Parquet files cannot be used as a seed for the Generate more data feature.

When starting an Ad hoc job, users can upload 2 different files as a subject table.

Reference tables' primary keys are not copied but generated.

QA report generation fails when analyzing database datetime columns that contain values in an unknown format.

Sequence lengths are incorrectly calculated in an edge case scenario.

When creating or modifying a data connector, the Test connection button doesn’t check whether the specified schema can be accessed.

Whitespaces in the header row of CSV files cause issues during synthesization.

QA report generation fails when synthesizing Parquet files.

Incorrect processing of scientific notation in CSV files.

Certain datetime ranges are incorrectly processed as strings.

Restrictive rules causing the QA report to fail in certain edge cases.

Long warning messages within the app’s architecture causes it to crash.

QA report fails when a column is configured as 'mock data'.

Incremental timestamps in time-series data may generate inconsistent synthetic data when configured as ITT.

QA report fails when a numerical column is completely empty.

Synthesization fails if the linked table’s entries are not linked to the subjects in the subject table.

When the ‘number of generated subjects’ is left blank, the number of training subjects is used if defined, instead of the number of subjects in the subject table.

Incorrect number of columns reported in the QA report.

‘Cancel training’ and ‘Cancel generation’ buttons are not working when synthesizing data.

UI issues when creating an Oracle database data connector.

Incorrect handling of SID and SERVICE_NAME connections to Oracle databases.

The QA report of certain datasets have an Incorrect placement of labels in the correlation matrix.

Numerical columns may generate a casting exception during generation causing a job failure.

License renewal issues.

QA report generation crashes when a CSV file contains \n symbols.

Out of memory issues when synthesizing subject table-linked table datasets.

The trained AI model is lost when the training crashes.

In rare cases, numerical values are incorrectly detected as boolean values.

License issues due to restarted VMs.

The data connector details view doesn’t show the database name.

The AI server crashes when there’s an issue with assigning foreign keys using Smart Select.

Generation crashed if the precision is specified for columns with floating point numbers.

Job cancellation hangs when using AWS ECR.

Job won’t start if the String pattern of the Custom string mock data type is not defined.

The Generate more data feature crashes with some of the supported datetime formats.

Jobs may crash if they process very wide tables.

AI model training crashes when consistency correction and GPU acceleration are both active.