“Keeping customer information safe and secure is of paramount importance in our business. Pythian had the BigQuery expertise to create a data architecture and permission model to share data between departments, while protecting personally identifiable information.”

Large Personal Finance Company Secures Data Sharing With Pythian Big Data and Data Warehouse Modernization Services

 

Business Challenge

A large personal finance company’s IT Data Integration team needed to build a modern data warehouse using Google BigQuery as a centralized data hub and analytics engine for data from their customized applications—as well as data from public and commercial providers. To protect consumers’ personally identifiable information, employees in one business unit normally cannot view or use data assets from other business units. However, two separate business units needed to find a secure and controllable way to share data assets for auditing purposes. The access to data assets needed to meet strict legal and security compliance requirements—or risk substantial fines or even termination of the company’s business. The process also had to be efficient, without data duplication. It also needed to be easy to revoke this access without any traces, including cross-pollination products. The company required expert advice on a permissions model and project structure for Google BigQuery that would meet their need to allocate data storage costs by department, and to meet their stringent access, permissions and audit requirements.
 

We Provided

Because Google BiqQuery is a relatively new offering on the Google Cloud Platform, there isn’t yet an established community of experts. The Pythian Big Data consulting team have been working with Google BigQuery since it came to market, and were able to provide the unique expertise and skill sets that the large personal finance company required. After legal review and consent, two business units were granted access to subsets of each other’s data to augment their own data sets. Pythian enabled the required permissions, using their big data and data warehouse modernization skills. Pythian also ensured that each resulting data zone and data set had a clear heritage and audit trail. Master data could not be polluted with the other unit’s data. In addition, all products of cross-pollination were restricted to an isolated area, separated from the original master data—even after legal consent for sharing was given. Pythian ensured that making consented data available was a straightforward process without data duplication and made it easy to revoke this access without leaving a trace. Google BigQuery did not have the built-in user and permissions management facilities required by the company, and Pythian was able to come up with some creative workarounds to achieve the desired outcomes.
 

Result

Pythian’s big data and data warehouse modernization expertise enabled the secure multi-tenancy access that the company needed while meeting the company’s stringent legal and security requirements. Data sharing is efficient, and enabling and revoking access is quick and easy. Most important, consumer information is safe.
 

Technologies

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