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Tag: data drift

Three Critical Factors to Consider When Preparing Data for Generative AI

Thanks in part to the excitement around breakthrough generative artificial intelligence (AI) tools like ChatGPT, industry analysts are projecting rapid growth of business investment in AI and machine learning (ML) techno Read more…

Solving for Data Drift from Class Imbalance with Model Monitoring

The amount of data created within the next five years will total twice the amount ever produced, according to IDC. Not only will this data hold a wealth of knowledge and insights that businesses can leverage to enhance d Read more…

Can Retailers Trust Their Machine Learning Models?

As we inch closer to Black Friday and the start of the holiday buying extravaganza, retailers are putting the final touches on the demand forecasts they’re using to predict the mix of goods they’ll carry this winter. Read more…

Building Continuous Data Observability at the Infrastructure Layer

Data is the lifeblood of business today, but getting it where it needs to go is hard, especially as data volumes grow. Data pipelines become the repeatable method for moving this digital crude, but monitoring the flows f Read more…

Algorithmia, Datadog Team on MLOps

Tools continue to be introduced to allow machine learning developers to monitor model and application performance as well as anomalies like model and data drift—a trend one market tracker dubs “ModelOps.” The la Read more…

Staying On Top of ML Model and Data Drift

A lot of things can go wrong when developing machine learning models. You can use poor quality data, mistake correlation for causation, or overfit your model to the training data, just to name a few. But there are also a Read more…

Streamsets Gets $35M for DataOps

StreamSets, which bills itself as the "air traffic control" tasked with preventing collisions from occurring with big data, today announced that it raised $35 million, which it will use to continue building its data oper Read more…

Keeping on Top of Data Drift

Data is often thought to be constant and immutable. A given piece of data is defined by 1s and 0s, and it never changes. But there's an emerging school of thought in the big data world that sees data as constantly drifti Read more…

Finding a Single Version of Truth Within Big Data

There seems to be an implicit promise associated with the rise of big data analytics: By taking more measurements and calculations, that we can deliver deeper insights atop source data, and do so at quicker intervals tha Read more…

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