Board and Google: Connecting Data, Planning and Decisions

Over the past few years, many organizations have established a clear cloud and data strategy around the Google ecosystem. Google BigQuery often plays a central role in that architecture, providing a scalable foundation for bringing together large volumes of operational and analytical data.

For enterprise planning, this creates an important opportunity: How can organizations extend their existing Google data strategy into planning, forecasting and decision-making without introducing another data silo or unnecessary architectural complexity?

Google as the data foundation, Board as the planning and decision layer

One straightforward architecture pattern is to keep the existing Google data architecture in place and build enterprise planning processes on top of it.

Google BigQuery can continue to provide actuals, operational information and other data required for planning. Board complements this architecture with capabilities designed for integrated enterprise planning, including planning, forecasting, simulation, workflow and business logic.

The principle is simple:

Google Data Ecosystem ↔ Board → Planning, Forecasting & Decisions

There is no need to rethink a data strategy that already works. Board becomes an integrated planning and decision layer within the existing architecture.

Connecting Board with the Google ecosystem

Board supports Google BigQuery as a cloud data source through its cloud connectivity capabilities. This allows data held in BigQuery to be incorporated directly into planning and analytical processes in Board.

BigQuery does not have to be the only integration point. Depending on the architecture, Google Cloud Storage can support file-based data exchange, while REST APIs provide additional options for API-driven integration scenarios.

The appropriate pattern depends on the use case, data volumes and an organization’s existing architecture standards – allowing companies to build on their Google investments rather than replace them.

Planning is not a one-way flow

Modern planning architectures do more than consume information. Planning itself creates valuable data: forecasts, scenarios, budgets, allocations and operational decisions.

Capabilities such as writeback and drill-through therefore become important parts of the overall architecture. Drill-through can provide access to detailed information held in underlying data sources, while writeback can make planning and calculation results available to downstream processes.

This creates a connected flow between enterprise data, planning and decisions instead of an isolated planning silo.

Proven in practice

This architecture is already used in real-world enterprise environments. Conrad Electronic, for example, uses Google BigQuery as its data warehouse together with Board for integrated planning processes.

Board supports processes including financial planning, sales budgeting, inventory management and investment planning, while planning results can be written back to BigQuery.

It is a practical example of how a Google-centric data strategy and a specialized enterprise planning platform can work together within one connected architecture.

Keep your Google strategy. Extend it with enterprise planning.

Keep your Google strategy. Extend it with enterprise planning.

Introducing an enterprise planning platform should not require redesigning a cloud and data strategy that already works.

If Google already plays a central role in an organization’s technology landscape, Board can complement that environment as the enterprise planning and decision layer – connecting governed enterprise data with business logic, workflows, forecasts and scenarios.

The result is not a competing architecture, but a clear separation of responsibilities:

Google provides the data foundation. Board turns data into plans, forecasts and better business decisions.

For organizations, this means protecting their existing investment in the Google ecosystem while adding enterprise planning where it creates the greatest business value.