The update, which is available to all users Wednesday, also adds machine learning capabilities to Tidemark's cloud, which uses the Apache Spark framework for data analytics.
Traditional machine learning methods like regression analysis and neural networks struggle with incorporating the trove of information that big data has brought to the enterprise, said Gheorghe.
"The problem with them is when data comes in faster and faster, it's harder to learn," he said.
Tidemark's computational cloud can handle the data influx so customers get a more accurate and timely forecasts. Customers can note if the forecasts meet or exceed finance and budget parameters, providing the machine learning algorithm with immediate feedback, said Gheorghe. Standard machine learning methods can't process information as quickly, he added.
"It's just something we could never do in the past because you have to train them to run the data again. It's late by that time and the data source has changed," said Gheorghe.
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