Access to the cloud has advanced the distribution and consumption of financial information on a global scale. In parallel, the global financial data landscape has been transformed by an influx of alternative data sources, including social media, meteorological data, satellite imagery, and other data. Exchanges and market data providers now find they need to include these new datasets to enrich their products and compete, which has meant they now must consider cloud-based models to keep up with the demands of their customers who expect easy, quick, flexible and cost-efficient ways to consume market data.
To address these needs, today we’re announcing the general availability of Datashare for financial services, a new Google Cloud solution that brings together the entire capital markets ecosystem—data publishers, and data consumers—to exchange market data securely and easily.
Datashare helps organize third-party financial information, making it accessible and useful to market data publishers and data consumers. We open-sourced the entire Datashare solution so market data publishers can now onboard their licensed datasets to Google Cloud securely, quickly and easily, while data consumers can consume that data as a service in tools of their preference, such as BigQuery.
Three ways to distribute and consume your data
Batch data delivery
Datashare provides a batch data delivery mechanism for data publishers to deliver their reference data, historical tick data, alternative market data sources and more via BigQuery, reducing the administrative burden on data consumers to extract insights from data.
Real-time data streaming delivery
By using this event-based data delivery channel for rapidly changing instrument prices, tick data, orders, news and others via Pub/Sub, data consumers can reliably process individual messages or rewind to a point in time to replay a prior market scenario and test model changes.
Monetizing licensed datasets
Market data publishers can onboard their licensed datasets to Google Cloud and make them available via a one-stop-shop on Google Cloud Marketplace, enabling a new sales channel to expand market reach.
Check out the diagram below to see how you can share your batch and real-time data directly to your Google Cloud customers with BigQuery and Pub/Sub.
As you can see in the above reference architecture, both publishers and consumers can derive several benefits from the solution:
Benefits for data publishers
You no longer have to maintain your own delivery and licensing infrastructure.
You can easily package and deliver granular data products and experiments with SQL.
You can have a solution that scales with your business as data volumes and number of customers grow.
Benefits for data consumers
Your data is ready for analysis and machine learning (ML)— you no longer have to maintain extract, transform, and load (ETL) pipelines to load files and transform data.
You can avoid the expense and burden of maintaining multiple copies of large data files.
You can be more targeted with consumption of data using BigQuery queries, improving performance, and compliance, and reducing cost.
Accessing the datasets
Google Cloud has been working with multiple industry firms on innovating in the market data space. By using Datashare for publishing, data publishers can make their entire datasets available on Google Cloud. Early adopters of Datashare include firms such as OneTickand Accern. OneTick’s datasets include reference and historical futures data (that can be accessed in our console with your login). Accern’s datasets include alternative data such as market sentiment and credit analysis data (that can be accessed in our console with your login).
To make it more helpful, we partnered with Accern to create a hypothetical scenario to describe the data acquisition and analytics process step-by-step.
Accern use case
As a sustainability analyst, you require an economic, social and governance (ESG) dataset to determine which sector is the most widely covered ESG sector by analysts, and to also identify the sector with the lowest ESG sentiment score. Now, you can discover and acquire an ESG dataset in Google Cloud.
Step 2. Click a dataset, for example Accern AI-Generated ESG Insights, then review the overview details, plans and pricing, documentation and support information. To view the available pricing tiers, click ‘View All Plans’. Once you’ve decided on a tier that you would like to subscribe to, click ‘Select’, choose a billing account and review and accept the terms of service to complete the subscription. Once the steps are complete, click ‘Subscribe’ at the bottom. An overlay window will appear, click ‘Register with Accern’ to activate and complete the subscription.
Step 3. Once activation is complete, you’ll be directed to the Datashare ‘My Products’ screen. Voila! You are now subscribed to Accern’s ESG Scores dataset and can access it in your Google Cloud instance using BigQuery. To access the data, click the hour glass icon on the corresponding ‘My Products’ record that you just purchased. An overlay will present you with the details on the dataset and/or table. Click the ‘Navigate to Table’ button to navigate through to the BigQuery console.
Step 4. Now that you have access and are in the BigQuery console, it’s time to generate data insights.
For this example, we’ve eliminated the company identifying information that is included as part of the subscription and aggregated company ESG in a view where each row represents a day, an industry sector, a specific identified ‘ESG Issues’ (event_group and event) and the respective ‘ESG Sentiment’ per issue.
For example, row 1 indicates that within the ‘Healthcare’ sector, there was a ‘Social – Civil Society’ issue identified and it had a negative ESG sentiment score of -15.35.
Step 5. Generate a report by exporting it to Data Studio to build visualizations and conduct additional analysis on the ESG data.
Select ‘Export’ and ‘Explore with Data Studio’.
Step 6. Build a simple/basic report.
Now that the ESG data appears in Data Studio, you can start by building a simple chart to help you understand which industry sectors have the highest volume of discussions around ESG and the overall ESG Sentiment per industry sector.
To build the chart:
Select the chart type ‘Table’.
Include Entity_Sector as your dimension to aggregate results by ‘Industry Sector.’
Include Signal_ID as a measure to count the number of ESG passages identified per ‘Industry Sector.’
Include AVG(Event_Sentiment) as a measure to display the overall ESG Sentiment per ‘Industry Sector’ across ESG Issues.
You can see sectors that are most discussed when it comes to ESG related topics and their corresponding ‘ESG Sentiment’ scores.
Step 7. Build your final report in Data Studio.
As a next step you can further drill into the data to understand ESG data specific to each ‘Industry Sector’ and identify positive and negative ESG practices.
Accern has built a more complex sample dashboard and made it available publicly here. You can interact with this report and play around with the data. The dashboard can help to identify material ESG insights for each sector to inform your investment and risk processes. If you have additional questions, you can reach out to Accern directly.
Discovering, accessing and analyzing licensed datasets is quick and easy. Stay tuned for more updates on new licensed datasets.
Publishing your data via Datashare
If you are a publisher of market data, alternative, or exotic data, you can use Datashare to get it published on Google Cloud Marketplace.
Start by joining the Partner Advantage program by registering for the Partner Advantage Portal and applying for the Partner Advantage Build Model engagement. Visit our getting started guide for information to get started on publishing licensed datasets in the Marketplace. Stay tuned for a future blog post about using Datashare to publish datasets in the Marketplace.
More solutions for capital markets
Check out other Google Cloud solutions for capital markets.
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