DataStax Focuses on AI Feature Engineering with Acquisition of Kaskada

DataStax, a leading contributor to the open-source Apache Cassandra database, has announced that it is acquiring AI vendor Kaskada to expand its data platform and power AI and machine learning applications. This move is part of DataStax’s goal to help organizations use operational data to improve business outcomes.

Organizations need good data, typically stored in a database for querying, to effectively use machine learning and artificial intelligence. However, many AI use cases also require real-time streaming data sources. DataStax has been building out its data platform since 2010 and in 2021 acquired Apache Pulsar vendor Kesque and launched a streaming data service.

Kaskada’s feature engineering platform can help organizations use data for AI applications. Kaskada has developed a concise description language that enables a data engineer to simply describe what is needed from a dataset in order to feed an AI model. The technology is also able to operate at the high throughput that’s necessary for real-time applications.

DataStax’s aim is to fit into an ML workflow, providing the data foundation and feature engineering that can be used to power inference engines for AI. The flow of data is bi-directional, such that predictions and outcomes from AI inference can then be loaded back into Cassandra, where the result can be served to application users.

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