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Google Cloud announces Datashare to simplify the exchange of financial services data

2 Mins read

According to Google News, Google Cloud announces Datashare to simplify the exchange of financial services data. DataShare solutions for financial services can be used by data publishers and consumers to securely exchange copyrighted data sets.

Google has announced the launch of DataShare for Financial Services. A new Google Cloud solution that allows data publishers and data consumers to exchange data in one place. Datashare organizes third-party financial information to access and use data publishers and consumers.

Financial information is communicated globally through cloud technology. At the same time, Google noted that the pattern of global financial data has also changed due to the addition of other data sources, such as social media, weather data, and satellite images. Exchanges and market data publishers now need to add these new data sets to increase the competitiveness of their products.

DataShare provides a flexible data publishing and consumption method for the data market in the cloud. Data publishers and consumers can safely and efficiently process authorized data sets on DataShare. Google said that they open-source the entire DataShare solution. Allowing market data publishers to load authorized data sets in the Google Cloud. Whereas data consumers can use their preferred data tools to use data as a service.

There are three ways to publish and consume data in DataShare. The first batch is data delivery. DataShare provides a batch data delivery mechanism to data publishers. Which can distribute their reference data and substitute market data through BigQuery. This reduces the burden of analyzing data for consumers.

The second is real-time data streaming delivery. Through the event data distribution channel, prices, scale data, orders and other information can be quickly changed by pub / sub. Data consumers can process a single message reliably. Or may return at a specific time. Point to re-run market conditions and test model changes. The ultimate is to allow data publishers to upload copyright data and use it to pay for other consumers through the Google Cloud Marketplace.

For data publishers, this is the advantage of DataShare. That it does not need to maintain the distribution and authorization infrastructure itself, and SQL can be used to package and distribute data products. For data consumers, this is the advantage. That it can use off-the-shelf analysis and machine learning. There is no need to manually maintain the ETL pipeline to load data, load files, and convert data, and there is no need to pay the costs and burden of maintaining multiple copies of large data files.

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