GCP – Build, use and share data with data products in BigQuery

In today’s data-driven world, teams struggle with siloed data, lack of business context, data reliability concerns, and inconsistent governance that hinders actionable insights. But what if there was a way that could transform your data landscape, unlocking the true value of your information?

That’s the problem we aim to solve with the experimental launch of data products in BigQuery, announced at Google Cloud Next. 

Data products in BigQuery offers an approach to organizing, sharing, and leveraging your most valuable asset by treating data as the product. Imagine a ‘Customer Sales’ data product: a curated bundle of BigQuery views combining customer order details and regional sales data. The Sales Analytics team, as the data product owner, provides business context for campaign analysis, along with data freshness guarantees and a dedicated point of contact. With this context and guarantees, data consumers can now effectively use this data product to make informed business decisions related to customer sales.

A data product in BigQuery simplifies the transaction between data producers and consumers by allowing data producers to bundle one or more BigQuery tables or views that address a use case, and distribute them as a logical block to data consumers. While BigQuery already provides a powerful way to share data through datasets listed in data exchanges, data products go beyond this by offering a higher level of abstraction and richer context on the business case the data addresses. Data products are available within the BigQuery experience, allowing data consumers to search and discover relevant assets as one consumable unit.

A data product allows data producers to manage their data as product, which entails the following:

• Build for use cases: Identify the customer, use case, and build a data product with one or more assets that addresses the use case.
• Establish ownership: Define the owner and contact information for the data product, helping to ensure accountability and provide trust for consumers.
• Democratize context: Distribute valuable context about the problems the product addresses, usage examples and expectations. 
• Streamline contracts: Provide data consumers the ability to annotate details on data freshness and quality to provide trust and cut down time to insight. 
• Govern assets: Control who can view the product and regulate access to the data that’s distributed via the data product. 
• Discover data: Provide data consumers the ability to easily discover and search data products.
• Distribute data: Distribute the data product beyond the organization’s boundaries into private consortiums or to the public via a data exchange.
• Evolve offerings: Iterate and evolve the product to address consumer needs.

When data producers build assets that address use cases and manage data as a product, it allows data teams to be more efficient, with:

• Reduced redundancy: By creating standardized and reusable data products, data teams avoid building the same datasets or pipelines repeatedly for different users or purposes. This frees up their time and resources.
• Better prioritization: Treating data as a product helps data teams prioritize their work based on the value and impact of each data product, aligning their efforts with business needs.
• Demonstrable ROI: By tracking the usage and the impact of a data product, data teams can better measure and communicate the value of their work to the organization.
• Built-in data governance: In the future, data products will be able to incorporate governance policies and compliance workflows, helping to ensure that data is managed responsibly and consistently.

Finally, all of these translate to efficiency for the data consumer by reducing the toil involved in finding the right asset. Data consumers get faster access to insight, since anyone within the organization can search, browse, and discover data products, as well as subscribe to the data product. They also get increased trust, because when data is well-defined, reliable, and properly documented, it’s easier to select the right data for a given use case.

Data products in BigQuery provide the building blocks and controls you need to manage data as a product. It leads to faster access to insights for data consumers through business-outcome-driven data management, maximizing value to the organization. 

Are you ready to unlock the untapped potential of your data? Sign up for the experimental preview here.