Automatically correct your data
Thanks to its embedded artificial intelligence engine, Tale of Data has a hundred or so functionalities to improve data quality.
To correct your data effortlessly, without writing code, you can use :
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ready-to-use functions for automatic error correction,
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fuzzy logic, to create bridges between similar data and make your information more reliable,
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repositories to complete your information,
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transformations to normalize or deduplicate your data,
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business rules in natural language to apply your standards.
Use ready-to-use functions
Tale of Data has a large number of ready-to-use functions that can be used by simply dragging and dropping.
Among these functions, the ones that are most used by our customers :
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deduplication with confidence index,
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automatic detection of the nature of standardized fields: telephone number, SIRET, ISO code (country ...), NIR code, ....,
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the suggestion of correction
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fuzzy logic to reconcile "almost" identical textual data.
Automatically correct your "close" data
With fuzzy logic, or Fuzzy Maching, Tale of Data detects approximate data.
The power of fuzzy logic functionalities allows to match identical or similar elements written with different spellings.
Choose the strategy that corresponds to the data to be corrected.
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phonetics: to compare different spellings of the same sound (o, au, water, etc.),
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Consonants first: this technique is based on the principle that consonants are more important. These letters are therefore weighted more heavily and examined first to detect duplicates,
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vowels first: same idea, but on vowels,
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N-gram: this technique divides strings into smaller sub-strings, called "n-grams", which are then used to detect similarities.
Enrich your panel of preset corrections
Use the repositories to correct your data
Even if the main reason for using repositories is related to data enrichment, this feature of Tale of Data is also used to correct your data. Indeed, you can compare your data with reference data to correct them in a few clicks.
Correct your data with your own business rules
Adding your own rules, in natural language* (drag and drop), ensures that your data is compliant with corporate rules and standards.
Example of a business rule: IF the product is of category "C" AND the order contains at least 5 items THEN apply a 4% discount
