June 11, 2023

Unlocking the Power of a Data Catalog for Your Business

The importance of data quality & profiling for the success of Machine Learning In today's world, businesses around the globe are generating a vast amount of data. To be able to adopt a data-driven initiative, organizations must manage data...

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Unlocking the Power of a Data Catalog for Your Business
Text data; synthetic text data; generative ai; large language models

Synthetic data to solve challenges in training and fine tuning LLMs

As machine learning continues to evolve, the use of Large Language Models (LLMs) has become increasingly prevalent, particularly in complex tasks requiring deep understanding and generation of human-like text. Retrieval-Augmented...

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fake data; dummy data; quality assurance; synthetic data generation;

Enhancing Data Management Solutions with data bootstrap

Synthetic data bootstrap In the dynamic landscape of organizations high-quality data is a requirement for the development of many solutions - from software testing and validation all the way to Artificial Intelligence (AI) initiatives. In...

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How to evaluate the re-identification risk in Synthetic Data?

While allowing for meaningful data behavior, it is crucial that synthetic data safeguards individual privacy. Therefore, ensuring the efficacy of synthetic data applications also requires a strong assessment of re-identification risks....

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How is diversity preserved while ensuring privacy in synthetic data?

One of the most valuable and unique characteristics of synthetic data is that it keeps the properties and behavior of original data without a one-to-one link with the real events, thus fostering data privacy and enabling secure data...

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open-source community; advent of code; pandas profiling; ydata-profiling; exploratory data analysis

Contribute to ydata-profiling in this Advent

A merry data analysis for all As the holiday season approaches, it's not just about decorating trees and sharing gifts; it's also a time to give back to the community and spread joy. This year, why not celebrate the season of giving by...

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synthetic data generation, synthetic data, open-source, pandas

Synthetic Data Generation in your stocking

An Advent to explore Generative AI and Synthetic Data Holidays are approaching and you are feeling like you want to explore something new - synthetic data might just be it! Options are always great, and data profiling is always a good...

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Synthetic data in Retail; Data profiling in Retail; Machine Learning in Retail

How to successfully adopt AI in Retail

The Power of Data Quality, Orchestration, Profiling, and Synthetic Data Retail is not only a fast-paced but also a highly competitive landscape, demanding from the players to be always ahead of the competition. The adoption of AI and...

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How to Validate the Predictive Performance of Synthetic Data?

One of the most important applications of synthetic data is its use in developing machine learning solutions – to train and test machine learning models – when real data is hard to collect or sensitive to share. For that reason, it is...

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How good is my Synthetic Data for Analytics?

Synthetic data, designed to mimic real-world datasets, must be able to provide the same answers as real data to be valuable. For instance, when determining the average of customers that buy certain products, the result returned by the...

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How to validate the quality of the relations in Synthetic Data?

As organizations increasingly rely on synthetic data to improve their machine learning models, ensuring that the relations like pairwise distributions and correlations are kept in synthetic data is part of the fidelity assessment whenever...

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Synthetic Data vs Real Data: How to measure the column's similarity?

When generating synthetic data, it is key that new data mimics the distribution of the original data to ensure that the synthetic dataset is a realistic representation of real-world data. In that sense, evaluating how the synthetic data...

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How to Visually Evaluate Your Synthetic Data Quality?

As Synthetic Data becomes a must-have for the future of AI, guaranteeing its quality becomes indispensable. Fidelity, one of the main pillars of synthetic data evaluation, is crucial in ensuring that synthetic datasets accurately represent...

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