Goldman’s invention introduces “managed data services” on cloud platforms, simplifying data organization and analysis for cleaning. Real-time, granular data processing gives firms meaningful insights for better decision-making and operations.

The financial institution is attempting to patent a method for “managed data services” on cloud platforms, which would support Kondo’s decluttering efforts. The goal of Goldman ‘s technology, which is described in this file in full, is to capture, clean, and organize data in real-time and to give actionable analysis with little to no labor on the client’s behalf.

This patent primarily focuses on “timeseries data,” which is data that is constantly recorded over time and “often at high rates of ingestion,” such as price variations of a substance or stock price data.

Essentially, information is replicated across the “nodes” of this system, each of which manages a “microservice.” These microservices could include anything from data entry to customer assistance. Due to the fact that each node consistently has access to all the data it requires to perform its specific function, all of these little services work together to process requests with low latency, even during periods of high traffic. According to Goldman, this system can be installed on a business‘ own custom cloud platform or one that they are renting (also known as AWS, Azure, etc.).

While all of this may seem abstract, the end result is clear, easily accessible data that can be utilized for a variety of business operations, such as answering inquiries, producing reports, and providing analysis that is “presented in real-time, down to nanosecond granularity,” which can help with decision-making.

Market data is in high demand among investment banks and other financial institutions, but it is also expensive

Over the past few years, the demand for financial data has exploded, with the LSE Group’s acquisition of Refinitiv for $27 billion in 2019 serving as an early indicator of an uprising. Since then, it’s just gotten worse: In 2022, global spending on financial data will reach a record $37.3 billion, according to a Burton-Taylor International Consulting report from April.

But Goldman claimed in its petition that actually using this expensive store of data takes time. An excessive amount of time is frequently spent by businesses acquiring, organizing, and maintaining data streams (up to 80%), leaving little time for data analysis. Goldman may seize a big market by obtaining a patent for a device that can perform all the laborious work for you.

Not just Goldman is interested in making data simpler to grasp. Rival JPMorgan Chase is attempting to patent no-code machine learning, which essentially consumes customer data and produces an AI model for business intelligence that is ready for use.

Although the businesses’ approaches differ greatly, the objective is the same: to clean up the data so that their customers – and therefore, themselves – can more rapidly turn their money into more money.

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