Workspace default settings
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The Workspace default settings menu allows to configure default parameters for workspaces. These settings ensure consistent behavior for data processing, privacy protection, and synthetic data generation. Below is a detailed explanation of the available options.
Note that user should be an Owner or Editor to access Workspace Default Settings.
Create or open the workspace.
Get the workspace ID
Workspace ID can be i.e.
Go to , which in this example is
Access the Workspace default settings menu.
Modify the required values directly.
Save changes to apply them to the workspace.
Below is an overview of the default settings and their functionalities:
Parameter
Default
Possible Values
Description
seed_value
42
Any integer (e.g., 0, 42, 1234)
use_seed
false
true
or false
(Boolean)
Specifies the natural language processing (NLP) models for PII detection and mockers.
Example:
Parameter
Default
Possible Values
Description
nlp_engine_name
"spacy"
"spacy"
or any other supported NLP engine name
Determines which NLP engine is used for PII scanning and detection.
models
N/A
A list of dictionaries with "lang_code"
and "model_name"
. E.g.:
[{ "lang_code": "en", "model_name": "en_core_web_md" }]
Each item defines a specific language and its associated model for PII detection.
gpu
false
true
or false
(Boolean)
Toggles GPU acceleration. When true
, models that support GPU will run faster but require a compatible GPU setup.
Parameter
Default
Possible Values
Description
initialization_mode
"SCRATCH"
"SCRATCH"
, "APPEND"
, or "READ_ONLY"
key_generation_method
"duplicate"
"generate"
, "duplicate"
, "hash"
n_parallel_pipeline_processes
1
Any integer (e.g., 1, 2, -1 for all CPUs)
Controls the number of column-processing jobs (fitting, transforming, inverse-transforming) that run in parallel. Higher values can speed up processing but use more system resources.
default_n_training_rows
100000
Any positive integer (e.g., 10, 1000, 100000)
Parameter
Default
Possible Values
Description
default_sample_noise_ratio
0.0001
Any positive numeric value (float).
• 0 < ratio ≤ 1
: relative noise
• > 1
: absolute std. dev.
Specifies the level of noise added to synthetic data. • Between 0 and 1: noise is added as a relative ratio. • Above 1: noise is treated as an absolute standard deviation.
default_min_sample_size
5
Any positive integer value
Minimum sample size used for model training
default_cardinality_threshold
10
Any integer ≥ 1 (e.g., 5, 10, 20)
default_rare_category_replacement
"*"
Any string (e.g., "*"
or "other"
)
default_clip_threshold
0
Any numeric value (integer or float).
• 0
: no clipping
• Positive number: outlier limit
Parameter
Default
Possible Values
Description
default_text_processor_model_settings
No single value
Same format as pii_model_settings
(language models, engine, GPU)
Specifies NLP models for advanced text processing tasks (non-PII or general text analytics).
default_textpii_parallel_jobs
2
Any integer ≥ 1; -1
to use all available processors
Defines how many parallel jobs are used when scanning text for PII. Increasing the number of jobs speeds up scanning but uses more CPU resources.
default_textpii_scan_batch_size
1000
Any integer ≥ 1 (e.g., 100, 1000, 5000)
Batch size for PII detection in text columns. Larger batches can be faster but may consume more memory.
Parameter
Default
Possible Values
Description
default_max_sequence_length
10000
Any integer ≥ 1 (e.g., 100, 1000, 10000)
default_end_of_sequence_token
-123456789.98765433
Any numeric token unlikely to appear in real data
A special marker denoting the end of a sequence, ensuring it is not confused with real data values.
default_long_sequence_threshold
10
Any integer ≥ 1 (e.g., 10, 100)
Defines a limit for the length of data sequences used in training, adjusting the longest sequences to the length of the Nth sequence. This helps prevent large sequences from overwhelming memory or computational resources.
Parameter
Default
Possible Values
Description
default_ray_memory_optimization
true
true
or false
(Boolean)
When true
, the system explicitly releases idle Ray workers between jobs, reducing memory usage. When false
, workers remain alive, reducing overhead for frequent runs.
default_fast_executemany
false
true
or false
(Boolean)
default_drop_indexes
false
true
or false
(Boolean)
Temporarily drops indexes before inserting synthetic data and re-creates them afterward. Often speeds up inserts but re-building indexes can be time-consuming for large tables.
Parameter
Default
Possible Values
Description
default_locale
"en"
Supports various locales, including: "en"
, "nl"
, "de"
, "ja"
Sets the default locale for language-based processing, such as date parsing or random text generation.
default_order_by_nr_columns
[3, 1]
A list of integers (e.g., [3, 1]
, [1, 2, 3]
)
default_max_pending_tasks
5
Any positive integer
Defines the number of tables that can be processed in parallel when using ranked scheduling. Increasing the value can improve performance through greater concurrency, but also increases memory usage. It's recommended to adjust this setting gradually, start with the default, monitor system performance, and tune based on available memory and database connection limits to ensure a balanced and stable operation.
used by generators with consistent mapping enabled or inherently consistent (e.g., hash) generators.
Consistent Mapping: When use_seed
is true
, changing seed_value
will rotate the mapping so the same input maps to a different output, allowing you to periodically change synthetic outputs for security.
If true
, all generators that support consistent mapping (mock, mask, hash) will use your specified seed_value
. If false
, the system does not use any for consistent mapping, meaning changes to seed_value
have no effect on the mapping scheme.
: "en"
with model name "en_core_web_md"
.
: English, Dutch, German, Japanese.
For more information please see .
Defines how the .
• "SCRATCH"
starts an empty workspace.
• "APPEND"
adds data to existing tables.
• "READ_ONLY"
prevents any modifications.
Determines the method for .
• "generate"
creates new keys.
• "duplicate"
copies source keys.
• "hash"
applies a hash function.
Sets the default used to train synthetic data models. If the input dataset exceeds this number, only the specified number of rows is used for training (unless otherwise configured).
Any category in a categorical column with occurrences below this threshold is considered “” and gets replaced.
for rare categories to preserve privacy.
Limits extreme outliers in numeric columns by “” values above/below a certain threshold.
Specifies the for sequential data generation or processing.
Enables for bulk inserts.
Defines the order in which columns are processed or modeled, which can be relevant for preserving data order in AI-powered generation or for .